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Title

Academic Session: 2010 l20Ll

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DECI-A,RATION OF TT{ESIS ANID COPYRIGIIT

: DODI ARDIANTO

: o6ftDEcEwER 1978

: ANALYSIS OF FACTORS AFFECTING THE ACCI]RACYOF EARLY COST ESTIMATE IN CONSTRUCTIONPROJECTS

COI\TFIDENTIAL (Contains confidential information under the Official SecretAct 1972)*

(Contains restricted information as specified by theorganization where research was done)*

OPEN ACCESS I agree that my thesis to be published as online open access(tull text)

I acknowledged that Universiti Teknologi lvlalaysia reserves the rights as follows:

1. The thesis is the property of Universiti Teknologi Malaysia.

2. The Library of Unive,niti Teknologi Malaysia has the rightto make copies for thepurpose of research only.

3. Ttr Library has tlrc right to make copia tresis for academic exchange.

No KP/IC: 201071VI1fi t61

D#19lry2011

"I he,reby declue thatI have readthisthesis and inmy

opinion this thesis is sufficient in terms of scope and quality for the award

the degre oftdaster ofConsfnrction Contract I\danage, ent

Sigrrdtr€Nmrc of SupervisorDate

SigndrcName of Second R€aderDate

ffi: PROF. A}il,IAD ROSDAN RAZAK

' I ql'.tt bo/f

JI.JLY 2011

AI{ALY$S OF FACTOR,S AFFECfiNG TTIE ACCI.'RACY OF EARLY COST

ESTIT{ATE IN CONSTRUCTION PROIECTS

DODIARDIANTO

A thesis submitted in ftlfihent of the

requimens for thE award offte &gree ofI\daster of Soienoe (Cmshrctim Cmnact Adamg€m€nQ

Facnilty of Built EnvirmeffiUnivereiti Teknolqgi Ldslaysia

JTJLY 2011

DECLARATION

I declarc that this thesis entitled "Atulysis Of Faetors Affecting ITu Accuracy A Early

Cost Ectlmate In Constructl.sn Projects" is the reult of my onm research except as cited

in the re&nences. The thesis has not bm accepted fr any degr€es and is nd concumetrly

submitted in candidffirc of any otrfr dep.

SigrtfircNameIhte

tu: 19 JL]LY2011

DEDICATION

o'To my beloved wife, brother, sister, mother, and late father

lv

ACKNOWLEDGMENT

Many thanks to my supervisor, Assoc. Prof. DR. Razali bin Abdul Hami{ for his kind and

helpful comments in the preparation of this thesis. Without that, this thesis would not have

been the same as presented here. I am also thanks to Prof. Ahmad Rosdan Razak for

correction this thesis in order to become more with quality.

I am also indebted to Ministry of Public Works Indonesia for funding my master study.

Credit should be given to all respondent for tlreir contributing in admission filling

questionnaire. My fellow postgraduate students should also be recognized for their support.

My sincere appreciation also extends to all my colleagues and others who have provided

assistance at various occasions. Their views and tips are useful indeed.

Finalty, tlnnk you to my beloved parents, brother, sister, my beloved one and whole family

who always support me.

v

ABSTRACT

Quality early cost estimate can be measured from its level of accuracy. Early

cost estimates prepared at the early stage of project inceptions, therefore early cost

estimates have an important function as a starting point and a benchmark for project

planning and controling in the future project stages. Early cost estimates are prepared

based on limited information and supporting data, it couses in early cost estimates

has the lowest level of accuracy than any other types of cost estimates.

From the perspective of the important function of an early cost estimate, in

contrary the low level of accuracy that is produced is a condition of stark contrast.

This condition is often encountered during the preparation of early cost estimates of

construction projects that why this topic became the basis of this research. This

research aims to make an analysis of the relationship factors that affect the accuracy

of the early cost estimate. Research data obtained from surveys of construction

projects that have been completed in the period 2006-2011. Survey data were

analyzed quantitatively to obtain significant variables and formulate a regression

model of factors affecting the accuracy of early cost estimates.

Quality of cost estimates associated with the accuracy and completeness of

the supporting elements depends on: nature of the project, the level of data and

information available, techniques and methods used, ability of estimator, and other

factor considered while preparing the estimate. The the factors were developed into

54 variables as the basic elements of the preparation of early cost estimates. From the

results of multiple linear regression analysis obtained significant factors (<0.05)

which affects the level of accuracy of the early cost estimates, as follows.:

Geographical location / Site location, Quality level of the estimator / Estimator

Expertise; Availability project information / Documents used in Preparing the

estimate; the availability of scope of the project; the availability of project documents

(preliminary and Size of Project / Scope of the project.

v

ABSTRAK

Kualiti anggaran kos pendahuluan boleh diukur dari tingkat ketepatan yang dihasilkan. Anggaran kos pendahuluan disusun pada peringkat awal projek bermula, sehingga anggaran kos pendahuluan mempunyai fungsi penting sebagai titik tolak dan tolak ukur perancangan dan pengurusan projek pada tahap-tahap berikutnya. Anggaran kos pendahuluan umumnya disusun mengikut maklumat dan data pendukung yang masih terbatas, hal tersebut menyebabkan anggaran kos pendahuluan mempunyai tahap ketepatan yang terendah berbanding jenis anggaran kos lain.

Dilihat dari fungsi penting suatu anggaran kos pendahuluan di satu sisi, dan di sisi lain rendahnya tahap ketepatan yang dihasilkan merupakan suatu keadaan yang sangat kontras bertolakbelakang. Keadaan tersebut sering dijumpai pada saat penyusunan anggaran kos pendahuluan projek pembinaan sehingga menjadi dasar dilakukannya kajian ini. Kajian ini bertujuan untuk membuat analisis mengenai hubungan faktor-faktor yang mempengaruhi ketepatan anggaran kos pendahuluan terhadap ketepatan yang dihasilkan. Data penelitian didapati daripada kajian terhadap projek-projek pembinaan bangunan yang telah selesai pada kurun waktu tahun 2006-2011. Data hasil kajian dianalisis secara kuantitatif untuk mendapatkan variabel signifikan dan merumuskan model regresi terhadap faktor-faktor yang mempengaruhi ketepatan anggaran kos pendahuluan.

Kualiti anggaran kos yang berkaitan dengan ketepatan dan kelengkapan unsur-unsur pendukungnya bergantung pada: sifat projek, ketersediaan data dan maklumat, teknik dan kaedah yang digunakan, kualiti dan pengalaman estimator, serta faktor lain yang dipertimbangkan saat menyiapkan anggaran kos. Dari faktor-faktor tersebut dikembangkan menjadi 54 variabel sebagai unsur-unsur dasar penyusunan anggaran kos pendahuluan. Dari hasil analisis regresi linier berganda didapati 4 faktor bermakna (<0.05) yang berpengaruh terhadap ketepatan anggaran kos pendahuluan, iaitu: lokasi projek, kualiti / pengalaman penganggar, ketersediaan data dan maklumat projek, dan lingkup projek.

vi

TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGMENT iv

ABSTRACT v

TABLE OF CONTENTS vi

LIST OF FIGURE ix

LIST OF TABLE x

LIST OF APPENDIX xi

1 INTRODUCTION 1

1.1 Background Of The Study 1

1.2 Problem Statement 3

1.3 Objectives Of The Research 4

1.4 Scope Of The Research 4

1.5 Important Of The Research 4

1.6 Organization Of Thesis 5

2 LITERATURE REVIEW 7

vii

2.1 Construction Project 7

2.2 Project Cost Estimate 8

2.3 Cost Estimate Classification System and Accuracy Ranges 9

2.4 Accuracy Of Early Cost Estimate 15

2.5 Early Cost Estimate 16

2.6 Factor Affecting Quality of Cost Estimate 19

3 RESEARCH METHODOLOGY 24

3.1 Method of Research 24

3.3 Research Variables 27

3.4 Collection Of Data 28

3.4.1 Questionnaire Research 29

3.5 Data Analysis 30

3.5.1 Type Of Data 31

3.5.2 Analysis Correlation 31

3.5.3 Regression Analysis 32

3.5.4 F Test 35

3.5.5 t Test 35

3.5.6 Auto Test Correlation (Durbin Watson Test) 36

3.5.7 Multicolinearity test 36

4 ANALYSIS AND DISCUSSION 37

4.1 Preparation Research 37

4.2 Data Analysis Questionnaires 40

4.2.1 Analysis Correlation 41

4.2.2 Regression Analysis 47

4.2.3 Model Test 54

viii

4.2.3.1 Linearity Test ( F Test ) 54

4.2.3.2 t Test 55

4.2.3.3 Autocorrelation Test (Durbin Watson Test) 55

4.2.3.4 Multicollinearity Test 56

4.3 Result of Research 56

5 CONCLUSION AND RECOMMENDATIONS 57

5.1 Introduction 57

5.2 Conclusion 57

5.3 Limitation of the research 58

5.4 Recommendation for future research 59

REFERENCES 60

ix

LIST OF FIGURE

FIGURE NO TITLE PAGE

1.1 Typical life cycle profile (Risk Versus Amount At Stake) 3

2.1 Project Cost Estimate Process (Oberlander, 2001) 9

2.2 The Stages of Project Estimated Cost (Oberlander, 2000) 9

2.3 AACE Classification System 15

2.4 Design Process 17

2.5 Effect of skill and experience of the estimator of the The

accuracy of the estimated project costs (Oberlander, 2001) 20

3.1 Research Methodology 24

3.2 Correlation Analysis Diagram 32

3.3 Regression Analysis Diagram 34

4.1 Scatter plot - Regression Standardized Predicted Value 50

4.2 Scatter plot - Regression Standardized Predicted Value (end) 53

x

LIST OF TABLE

TABLE NO. TITLE PAGE

2.1 Cost Estimate Overview Chart 14

2.2 General concept stages of cost estimate process 16

2.3 Factor Affecting Accuracy of Early Cost Estimate 23

3.1 Likert scale level of accuracy early cost estimate 30

4.1 Factor affecting the accuracy of early cost estimate

after interview with expert 40

4.2 Profile of respondents 41

4.3 Coeficient Correlation and significant levels of variables 45

4.4 Factors that have a significant correlation of early cost

estimate accuracy 46

4.5 Model Summary 47

4.6 Diagnostic collinearity 47

4.7 Coefficient 48

4.8 Model Summary 1 48

4.9 Diagnostic collinearity 1 49

4.10 Coefficients 1 50

4.11 Model Summary 2 51

4.12 Diagnostic collinearity 2 51

4.13 Coefficients 2 51

4.14 Model Summary (End) 52

4.15 Coefficients (End) 52

4.16 ANOVA 54

xi

LIST OF APPENDIX

FIGURE NO TITLE PAGE

A Expert Interview 63

B Questionnaire 70

C Table of F Statistical and t Table 76

D Data Questionnaire 78

E Summary Respondent 82

1

CHAPTER 1

INTRODUCTION

1.1 Background of the studies

Nowadays the construction sector in Indonesia is experiencing rapid growth.

The development of these construction projects marked by numerous large-scale

construction projects built by government or private parties.

A project has essentially been born from a decision to invest. The decision to

make an investment involves a number of funds in hopes to get the benefits that often

will have a major impact for the survival of a company. One of the decisions that

must be taken to initiate an investment project is to determine what will be built and

how much does it cost to build the project. Physical development costs and other

expenses are fixed capital for building construction projects.

Cost estimate according to the National Estimating Society-USA is the art of

estimating (the art of approximating) the possibility of total costs required for an

activity of which is based on information available at that time. Based on the

function and its relationship to the level of accuracy, there are several types of cost

estimates in each stage of the project. For example in the early stages of project

concept development, note the estimated how much it cost to build a project,

therefore, developed a preliminary cost estimate. Preliminary cost estimate is one

important factor that should be considered in decisions to invest in development

projects because of the value that result from a process of preparing the preliminary

cost estimate is the approximate amount of initial capital needed for the project

owner.

2

Evaluation of the feasibility of building projects, and decisions on design and

construction issues are usually based on a series of approximate estimates (pre-bid

forecasts) that are considered against initial plans and budgets (Betts and Gunner,

1993). Approximate estimates are also required for funding decisions and cost

control. Over-estimation or over-provision of funds for one project means lesser

funds are available for other business opportunities. In difficult times, estimations of

profit margins are likely to be conservative and construction costs are over-

estimated, otherwise viable projects may be shelved. Estimates form the basis for

tender comparison or negotiation, and under-estimation may lead to difficulty in

award decisions, or in some cases unrealistic negotiation targets. Projects may be

delayed whilst more funding is arranged or even shelved if additional funds are not

available. To proceed with insufficient funds will likely lead to payment problems

and hefty finance costs for overdrafts or emergency loans during construction. It is

therefore necessary for quantity surveyors (QS) to improve the accuracy of their

estimates to ensure that clients are satisfied with their services.

Accurate, early cost estimates for engineering and construction projects are

extremely important to the sponsoring organization and the project team. For the

sponsoring organization, early cost estimates are vital for business unit decisions that

include strategies for asset development, potential project screening, and resource

commitment for further project development. Inaccurate early estimates can lead to

lost opportunities, wasted development effort, and lower than expected returns.

For the project team, performance and overall project success are often

measured by how well the actual cost compares to the early cost estimate. Initial cost

estimates are the basis on which all future estimates are compared. Future estimates

are often expected to agree with (i.e., be equal to or less than) the initial estimates.

However, final cost often exceeds the initial estimate.

Estimated project cost is generally a systematic steps and through the same

process between one project and previous projects of its kind. Various literatures

provide guidance on the process in calculating the project cost estimates using

various methods and approaches used. The availability of data and information, time

limit, techniques and methods used, skills and abilities an estimator is a factor that

determine the quality of the project cost estimate.

3

(Source : Budi Manan, 2007)

Another factor affecting the quality of the project cost estimate is uncertainty

which is one of the unique characteristics of a construction project. Limitations of

data and information in the development stage preliminary cost estimate is one

source of uncertainty containing the risk that causes low levels of accuracy. Risk is

an unavoidable problem of every construction project. Therefore it is necessary to

planning and managing the risk integratedly in every stage of the project, including

in the development stage preliminary cost estimate project.

1.2 Problem statement

Early cost estimate is a type of cost estimates in the earliest stage of

construction projects. With a high degree of uncertainty (see figure 1.1) because of

the limited information available to cause the accuracy of cost estimates has the

lowest degree of accuracy than any other cost estimates. But on the other hand the

value of projects resulting from the calculation of the preliminary cost estimate is

critical to the continuation phase of your next project. That amount will be used as a

basis for decision making project implementation and will be used as a reference

estimate of the cost at a later stage.

Because of the importance of preliminary cost estimation, as a starting point

for the commencement of the project and as a basic reference for the next stage, then

the accuracy of the preliminary cost estimate is an important thing that should be

considered in the process of preparing the preliminary cost estimates.

Figure 1.1 Typical life cycle profile (Risk Versus Amount At Stake)

4

1.3 Objective of the research

The objectives to be achieved in this study are:

a. Identifying factors that affect the accuracy of early cost estimates of

construction projects.

b. Identifying relationship between the factor and the accuracy of early cost

estimates.

1.4 Scope of the research

Scope of the research are:

a. Early cost estimates that has been mention in this research is initial cost

estimates on construction projects in Jakarta, Indonesia.

b. Types of projects to be taken as a sample are building construction

project

c. The process of preparing the preliminary cost estimates made during the

feasibility study lasted until just before the detailed design is completed.

1.5 Important of the research

In general, the author hopes this research can contribute to the development

of construction industry in Indonesia, especially in the sector of Construction

Management. The important of the research are:

a. Providing an explanation of how the availability of data and information,

methods and systems used and the experience and skills related to the

process estimator estimates the cost could affect the accuracy of

preliminary cost estimates.

b. Provide input in the application process preliminary cost estimates

associated with the things that need to be prepared, techniques and

5

methods used, the necessary procedures and other matters involved in the

process preliminary cost estimate in order to produce a preliminary cost

estimate is accurate.

1.6 Organization of Thesis

This thesis consists of five chapters, among others:

Chapter I Introduction

In this chapter explained the background of this study, formulation of

problem statement , objective of the research, scope of the research,

importance of the research, research methodology and organization of thesis.

Chapter II Literature Review

In This section described the basic theory associated with the overall project

cost estimates and preliminary cost estimates in particular. Sources literature

drawn from several references in the form of books or journals that have

published research.

Chapter III Research Methodology

This section describes the methods and procedures used in this research.

Systematic research is illustrated by the flow chart that explains each step that

passed from this research. The basis of the steps in quantitative research and

data collection system described in this section.

6

Chapter IV Analysis and Discussion

Analysis of data obtained and the discussion until drawn a conclusion

described in this section. Every step analysis used and the discussion related

to the findings generated are described to obtain a clear picture of the results

obtained from this research.

Chapter V Conclusion and Suggestion

This section contains the conclusions that can be drawn from the results of

research undertaken. The suggestions that if can be used and further

recommendations can be used in the development of subsequent research

provided in this section.

7

CHAPTER 2

LITERATURE REVIEW

2.1. Construction Projects

Projects can be defined as a series of activities that must be implemented with

a limited period, with an allocation of specific funds, and are intended to produce a

product or deliverable the quality criteria outlined clearly. Project implementation

involves many parties including the owner /owner, Consultants (planners, inspectors,

construction management, quantity surveyor), Contractors, subcontractors, suppliers,

etc.. With attachment and certain forms of cooperation of each party is working for

the implementation of the project. Construction project is one type of project that

aims to build a physical building of residential buildings, commercial buildings,

industrial buildings.

The project has unique characteristics, is always different in terms of

complexity, size, and resources necessary. The intensity of the dynamic nature of

project activities, the dynamics is characterized by ups and downs of resource

requirements throughout the project cycle. Because of the complexity and dynamics

of the intensity of the project, the project is divided into several stages. There is no

standard that is used in the division of stages in a project cycle, this staging is

generally based on the type of activities that take place during these stages. PMI

(Project Management Institute) Divide the project into phases: Conceptual Stage,

Stage Development Planning (PP / Definition), Implementation and Termination.

The purpose of the division of stages in one cycle of this project is to facilitate in

identifying and tracking changes in the activities so that project management system

can be effectively done.

8

The initial phase of the project begins with the conceptual development plan

project. This stage is considered a very important stage in the project cycle, because

in this stage that the decision to begin or whether a project or investment is made. At

this stage determined some important things like the development of initial plans of

the basic concepts and outline the project scope, plan product capacity, financing

plan, plan schedules, determining the location, etc. Therefore this stage is the stage

which has a major influence in determining the success of a project in terms of

quality, cost and project schedule. Over the project when implementation of the

project has been running, which has defined the project scope, budget and project

implementation has been assigned the project completion time has been determined,

it will be very difficult and it will be too late to make significant changes to improve

quality, optimize cost and schedule changes project.

2.2. Project Cost Estimate

Estimating project cost is an important element in managing the project,

because one of the parameters of project success is considered from the aspect of

cost performance. Basically, the project cost estimate done to find out how much it

cost to build a project or investment. Furthermore, cost estimates have a function

with a very broad spectrum, namely planning and controlling resources.

National Estimating Society-USA defined estimated cost cost estimate as the

art of approximating possibility of total costs required for an activity based on

information available at that time. From the above definition, the process of

preparing an estimate of project costs associated with activities to analyze costs

based on available information and estimated costs to be and may occur in the future.

Cost analysis and discussion focuses on the assessment of costs based on information

available to our times and the past. While cost estimates are meant to see the future

taking into account and make an estimate of the things that will and might happen in

the future.

9

Estimating project cost is generally a step-by-step through the process of

systematic and relatively the same between one project and previous projects of its

kind. Project cost estimate process depicted in Figure 2.1 below:

Figure 2.1 Project Cost Estimate Process Source : (Oberlander, 2001)

2.3. Cost Estimate Classification System and Accuracy Ranges

The process of cost estimates made during the project cycle, some types of

cost estimates are developed based on the stage in a project cycle (Figure 2.2),

beginning with preliminary cost estimates at this early stage conceptual continued to

expand in the next stage until all the stages of construction in progress (Oberlander,

2000)

Figure 2.2 The Stages of Project Estimated Cost Source : (Oberlander, 2000)

10

A variety of terms used by some literature to classify and define the type of

project cost estimates. Based on its function and the stages through which as well as

supporting elements, Barrie (1992) classify the types of cost estimates as follows:

a) Preliminary Cost Estimates / Conceptual and Preliminary Estimate.

Preliminary cost estimate are cost estimates prepared in the early stages

of planning the project before the completion of engineering design is

made.

b) Estimated Cost Details / Detailed Estimate

Detailed cost estimates are prepared cost estimates based on planning

documents and technical specifications of engineering that has been

made.

c) Definitive Cost Estimates / Definitive Estimate

The estimated cost is definitive cost estimates used to predict the cost of

the project (The project cost forecasting) Based on constraints derived

from the estimated cost of which was made earlier.

The American National Standards Institute (ANSI, 1991) defines three

types of estimates: order-of-magnitude, budget, and definitive.

a. Order-of-magnitude estimates have an expected accuracy between +50%

and -30%. They are generally based on cost-capacity curves and cost-

capacity ratios and do not require any preliminary design work.

b. Budget estimates are based on flowsheets, layouts, and preliminary

equipment descriptions and specifications and have an accuracy range

of +30% to -15%. Design generally must be 5 to 20% complete to

permit such an estimate to be performed.

c. Definitive estimates require defined engineering data, such as site

data, specifications, basic drawings, detailed sketches, and equipment

quotations. Design is generally 20 to 100% complete, and estimate

accuracy should be within +15% to -5%.

Definitions of these estimate types were developed by AACE International.

AACE International has proposed an expansion of the ANSI estimate

11

classifications to five types with expected accuracy levels based upon the amount

of project definition available when the estimate is prepared (AACE, 1997). The

accuracy of each class of estimate depends on the technological complexity of the

project, appropriate reference information, and inclusion of an appropriate

contingency determination. In all cases, accuracy ranges could exceed the ranges

indicated below in unusual circumstances.

The revised classifications are:

a. Class 5 estimates: These estimates are generally based on very

limited information. They may be prepared within a very limited

amount of time and with little effort expended—sometimes less than

one hour. Often little more is known than the proposed plant type,

location, and capacity. This class of estimate falls into the ANSI

order-of-magnitude classification. The required level of project

definition is 2% or less and the expected accuracy is -20% to -50%

on the low side and +30% to +100% on the high side.

b. Class 4 estimates: Class 4 estimates also are generally prepared based

upon limited information and also have fairly wide accuracy

ranges. They are typically used for project screening, feasibility

determinations, concept evaluation, and preliminary budget approval.

Engineering is only 1% to 5% complete and comprises, at a minimum,

plant capacity, block schematics, indicated plant layout, process flow

diagrams (PFDs) for the main process systems, and preliminary lists

of engineered process and utility equipment. Typical accuracy ranges

for this class of estimate are -15% to -30% on the low side, and

+20% to +50% on the high side. This class of estimate falls into the

ANSI budget estimate classification.

c. Class 3 estimates: These are estimates which form the basis for budget

authorization, appropriation, and/or funding. These estimates

typically form the initial control estimate against which all actual

costs and resources will be monitored. The required level of

project definition (i.e., completed engineering) is 10% to 40% and

12

includes at a minimum: process flow diagrams, utility flow

diagrams, preliminary piping and instrument diagrams, plot plans,

developed layout drawings, and essentially complete engineering

process and utility equipment lists. Accuracy ranges for this class

of estimate are -10% to -20% on the low side, and +10% to +30%

on the high side. This class of estimate also falls into the ANSI budget

estimate classification.

d. Class 2 estimates: This class of estimate falls into the ANSI definitive

estimate category. Class 2 estimates are generally prepared to form

detailed control baselines against which all project work is monitored

in terms of cost and progress control. For contractors, this class of

estimate is often used as the “bid” estimate. Typically engineering

is 30% to 70% complete and comprises, at a minimum: process flow

diagrams, utility flow diagrams, piping and instrument diagrams

(P&IDs), heat and material balances, final plot plans, final layout

drawings, complete lists of engineered process and utility equipment,

single line electrical diagrams, electrical equipment and motor

schedules, vendor quotations, detailed project execution plans,

resourcing and work force plans, etc. Accuracy ranges are much

improved over the prior classes of estimates. On the low side they are -

5% to -15%. On the high side, the ranges are +5% to +20%.

e. Class 1 estimates: Also included in the ANSI definitive estimate category,

this is the most accurate classification of estimates. Class 1 estimates

are generally prepared for discrete parts or sections of the total

project rather than for the entire project. The parts of the project

estimated at this level of detail are typically used by subcontractors

for bids, or by owners for check estimates. The updated estimate is

often referred to as the current control estimate and becomes the new

baseline for cost/schedule control of the project. This type of estimate is

often made to evaluate and/or dispute claims. Typically engineering is

50% to 100% complete and comprises virtually all engineering and

design documentation of the projects, and complete project

13

execution and commissioning plans. Typical accuracy ranges are -

3% to -10% on the low side and +3% to +15% on the high side.

Another associated cost estimating reporting and formatting reference

document is the ASTM E2516 – Standard Classification for Cost Estimate

Classification System for Building Projects, General Construction Projects, and

Infrastructure Projects. In general, this system is intended to be used for projects

where the main purpose of the project pertains to a building or facility. This shall

also include general site construction and infrastructure projects, where a

building or infrastructure project is the majority of the overall scope of the

project.

Table 2-1 below is an overview chart that combines tables from AACE

18R-97 and ASTM E2516 – Cost Estimating Classification System (see

recommended practices for more information):

14

Table 2-1 Cost Estimate Overview Chart Primary Characteristic Secondary Characteristic

EXPECTED ACCURACY RANGE [a] LEVEL OF PROJECT

DEFINIITION END USAGE METHODOLOGY PREPARATION

EFFORT [b]

Estimate Class

Expressed as % of Complete Definition

Typical Purpose of Estimate

Typical Estimating Method

Typical degree of effort relative to least cost

index of 1 [b] Process Industry (AACE 18R-97)

Building and General Construction Industry

(ASTM E2516)

Class 5 0% to 2% Concept Screening

or Feasibility

Capacity Factoring, Parametric Models,

Judgment, or Analogy 1 Low: -20% to -50%

High: +30% to 100% Low: -20% to - 30% High: +30% to +50%

Class 4 1% to 15% Concept Study or

Feasibility

Equipment Factored, Parametric Models, ,

Assembly Drive Models 2 to 4

Low: -15% to -30% High: +20% to 50%

Low -10% to -20% High: +20% to +30%

Class 3 10% to 40%

Budget, Authorization or

Control

Semi-Detailed Unit Costs with Assembly

Level Line Items 3 to 10 Low: -10% to 20% High: +10% to 30%

Low: -5% to -15% High: +10% to +20%

Class 2 30% to 70% Control or Bid/Tender

Detailed Unit Cost with Forced Detailed Take-

off 4 to 20 Low: -5% to -15% High: +5% to +20%

Low: -5% to -10% High: +5% to +15%

Class 1 Up to 100% Check Estimate or

Bid/Tender Detailed Unit Cost with

Detailed Take-off 5 to 100 Low: -3% to -10% High: +3% to +15%

Low: -3% to -5% High: +3% to +10%

Notes: [a] The state of proecess technogy and availibility of applicable reference cost data affect the range markedly.

The +/- value reprsents typical percentage variation of actual cost from the cost estimate after application of the contingency (typically at a 50% level of confidence) for given scope.

[b] If the range index value of '1' repesents 0.005% of project costs, then an index value of 100 represents .05%. Estimate preparation effort is highly dependent upon the size of the project and the quality of estimating data and tools.

Sources: 1. AACE International Recommended Practice 18R-97 Cost Estimate Classification System - As Applied in Engineering, Procurement, and

Construction For The Process Industry, Morganton, VA, 1997 2. ASTM, Standard Classification For Cost Estimate Classification System, E2516-06, West Conshohocken, PA, 2006

15

Figure 2.3., shows the various ranges of the AACE 18R-97 Recommended Practice

– Cost Estimate Classification System – As Applied In Engineering, Procurement,

and Construction For The Process Industries:

Source : AACE International Recommended Practice

2.4. Accuracy Of Early Cost Estimate

Early stage cost estimation is the forecasting of the cost of a project during

the planning and design stage (Serpell, 2005). Skitmore (1991) describes the

accuracy of early stage estimation as comprising two aspects, namely, bias and

consistency of the estimate when compared with the contract or accepted tender

price. Bias is concerned with ‘the average of differences between actual tender price

and estimate’ while consistency of estimates is concerned with ‘the degree of

variation around the average’. Aibunu and Pasco (2008) describes bias (inaccuracies)

in the estimate of a project may arise from two sources, namely, bias associated with

the project itself (will be the same regardless of the estimator) and bias associated

with the estimating technique used and the environment (which would change

depending on the estimator).

16

2.5. Early Cost Estimate

Estimated project cost is a dynamic activity conducted throughout the project

cycle stages, starting from the beginning of the project and ends when the projects

are handed over to the project owner (Gould, 2009). Viewed from the process in the

project cycle, early cost estimates are cost estimates prepared during the feasibility

study phase until just before detail design has been completed (Oberlander, 2000). So

basically the cost estimates are preliminary cost estimates are compiled based on data

and information from an initial concept in the form of an outline of the scope of a

project. Various terms of some of the literature used to explain the preliminary cost

estimates, such as: early cost estimate (Oberlander, 2000), Conceptual estimate

(CMAA, 2001), Preliminary estimate, parametric estimate (Hegazy 2002),

Feasibility estimate, an order of magnitude estimate (Kerzner, 2005), screening

estimate (Ritz, 1994), pre-tender estimate (Ashworth) etc..

Preliminary Estimates are employed in the early planning phases of a

proposed project to match an owner's needs (see table 2.2 ), expressed as written

requirements, with budget constraints in order to establish its overall scope (size) and

quality expectations. (Rosdan, 2010)

Table 2.2 General concept stages of cost estimate process

Source : (Rosdan, 2010)

17

Prelininary Estimates based only on guide prices : (Unit, Superficial, Cube, Storey

enclosure, Approximate quantities, Resource analysis, Cost models. (Rosdan, 2010)

Early stages at project development clearly define in figure 2.4 below :

Figure 2.4 Design process

Source : (Rosdan, 2010)

In the early stages of the project, a concept will be formulated in the form of a

project outline project scope and conceptual design and preliminary project

development programs. Based on the data and information that form the initial

concept of a project, preliminary cost estimates have been prepared to give an idea of

how big the budget should be spent to make it happen and provide guidance in

project development at a later stage. Under conditions limited data and information,

the biggest challenge in preparing the preliminary cost estimate is to interpret the

data and information into a value of the cost of a project.

Furthermore, based on the results obtained from the preliminary cost

estimates and with a certain accuracy to decided level, conceptual budget

(conceptual budget) Project assigned. This conceptual budget will then be used as a

basis for consideration in determining the strategy to be applied to subsequent stages.

18

Preliminary cost estimates is part of a project feasibility study whose results

will be used as one basis in decisions about the steps that will be done next, for

example in terms of planning and development of corporate strategy, screening of

projects wherever potential harm to the company's business continuity and

determination of policy in terms of the use of company resources.

In terms of availability of budget funds that are owned by the owner of the

project and how much budget is needed to build the project, the results obtained from

the preliminary cost estimates will be used as a reference for comparison against the

budget funds that are owned by the project owner. So the preliminary cost estimate is

kind of the first cost estimates produced in a project cycle which made reference to

check if the budget funds /budget in accordance with the cost needed to realize the

project (Barrie, 1992). When assessed the cost is too great to budget funds /budget

available (overbudget), Then the alternative concept will be developed to suit the

available resources.

At this stage of the Planning and Development (PP / Definition), preliminary

cost estimates used by the project team as one of the considerations in formulating

strategy and management of projects as the basis of stats and technical design

development projects.

Preliminary cost estimates are also used as a basis for preparing the outline of

the project schedule (Barrie, 1992). In the outline of the schedule is set to determine

when the planning phase of design and implementation procurement can be

implemented.

Usefulness of the preliminary cost estimates by Iman Soeharto (2001) is as

follows:

a. Assessing the economic and financial feasibility of the project.

b. Determining the order of priority (ranking) Of several projects.

c. Determining whether continued or not efforts further assess the

feasibility of the project.

From the above explanation can be concluded on the importance of a

preliminary cost estimate, but the limited data and information available is one of the

19

causes of type preliminary cost estimates have the lowest degree of accuracy than

any other cost estimates. The more complete information available, the better the

resulting accuracy. Therefore it needs to do the right approach in preparing the

preliminary cost estimates to generate cost estimates that have a good degree of

accuracy.

2.6. Factor Affecting Quality of Cost Estimate

Skitmore and Stradling (1990) describes five primary factors affecting quality

of cost estimating. These concern (1) the nature of the project, (2) the information

used, (3) the estimating technique used, (4) the feedback mechanism used and, (5)

the person providing the forecasts. This section provides a review of the literature

that has been examined to date on the subject.

Similar with Skitmore, Iman Soeharto (2001) describes the quality of cost

estimates depend on the following matters:

a. Availability of data and information

b. Techniques and methods used

c. Proficiency and experience of the estimator.

d. The purpose of the use of cost estimates.

The availability of information about the scope of the project is an important

factor in the quality of the resulting cost estimates. According to Oberlander (2000),

the accuracy of the estimated project cost is a function of the availability of

information (definition of project scope). The further progress of the project,

estimated cost or budget, the better prepared and sharp accuracy, because the

availability of input data and information needed (Iman Soeharto, 2001). For

example, in the early formulation of the scope of the project, because most of the

data and information is not available or can not be determined, prepared a

preliminary cost estimate with accuracy that is still rough (order of magnitude.)

Therefore, the increasing availability of data and information along with the progress

of the project are known several types of costs during the project cycle.

20

Techniques and methods used affect the quality of the resulting cost

estimates. However, the selection of techniques and methods do not stand alone, but

closely related to the purpose of the use of cost estimates and information available.

Due to the nature of work within the estimated cost of requiring various

assessment and judgment especially in the preparation of preliminary cost estimates

where data and information available is still limited, the skill and experience

compiler cost estimate (estimator) is very influential to produce quality cost estimate.

Figure 2.5 illustrates the influence of skills and experience of the estimator,

procedures and methods used to estimate the accuracy of a cost.

Figure 2.5 Effect of skill and experience of the estimator of the accuracy of

the estimated project costs

Source : (Oberlander, 2001)

In one known term project cycle cost of the project cycle (cost engineering)

which includes the cost estimates, cost budgeting, and cost control. So a person who

served in one cycle cost engineering must have experienced, because the cost aspect

is very important benchmark in the success of the project.

Besides the above factors, the quality of cost estimates is also determined by

the purpose of use. For example, preliminary cost estimates used in assessing the

feasibility of the project does not need to be prepared outlining the scope of work

21

(work breakdown structure) To detail as in the process of developing a definitive

cost estimates used in preparing the project budget control.

Based on the explanation and reviews from several literature above, the

authors make a grouping of factors that affecting the accuracy of early cost estimate

into 5 groups:

No. VARIABLES LITERATURE

I. NATURE OF THE PROJECT

1. Type of the project Skitmore (1999); Ogunlana and Thorpe (1991)

2. Size of project / scope of project Skitmore (1999; Ogunlana and Thorpe (1991)

3. Complexity of project Ogunlana and Thorpe (1991)

4. Other project characteristics Skitmore (1990)

5. Geographical location / Site location Skitmore (1990); Ogunlana and Thorpe (1991); Oberlander (2003)

6. The contract procurement system Skitmore (1990)

7. The prevailing economic climate Skitmore (1990)

II. THE LEVEL OF DATA AND INFORMATION AVAILABLE

8. Completeness of cost information Oberlander (2003)

9. Quality of information Babalola (2006)

10. Accuracy and reliability of cost information Oberlander (2003)

11. Aplicability of cost information Oberlander (2003)

12. Project information/Documents used in preparing the estimate Babalola (2006)

13. Capacities of project Oberlander (2003); Babalola (2006)

14. Time allowed for preparing the estimate Oberlander (2003)

15. Technology; Method of construction Oberlander (2003); Babalola (2006)

16. Processes project Oberlander (2003)

17. Piping & Instrumentation Diagrams Oberlander (2003)

18. Amount of special work likely production time Babalola (2006)

19. Project design criteria Oberlander (2003)

20. Complexity of design and construction Babalola (2006); Ogunlana and Thorpe (1991)

21. Utility resources and supply conditions Oberlander (2003)

22. Heat and material balances Oberlander (2003)

22

23. Mechanical equipment list Oberlander (2003)

24. Lead time for delivery of materials Babalola (2006)

25. Project Schedule Oberlander (2003); Babalola (2006)

26. The form of procurement and contractual aggrement Babalola (2006)

27. Project strategy Oberlander (2003)

28. The extent of completion of pre-contract decision Babalola (2006)

29. Frequency of construction variations Babalola (2006)

30. Client’s financial situation Babalola (2006)

31. Owner’s cost Oberlander (2003)

32. Purpose and intended use of estimate Oberlander (2003)

33. Owner’s experience level Oberlander (2003)

34. Engineer/Designer’s experience level Oberlander (2003)

35. Enviromental assesment and workforce Oberlander (2003); Babalola (2006)

36. The type of structure Babalola (2006)

III. THE ESTIMATING TECHNIQUE AND METHOD USED

37. Alligment of estimate methodology with available project information Oberlander (2003)

38. Is the estimate work process formally define and followed? Oberlander (2003)

39. Formal structure to categorized and prepare the estimate Oberlander (2003)

40. Utilization of checklist to ensure completeness and technical basis Babalola (2006)

41. Standard procedure to update cost data of project Oberlander (2003); Babalola (2006)

42. Documentation of information used in preparing the estimate Oberlander (2003)

43. Involvement of other resources in preparing the estimates Oberlander (2003)

44. Level of involvement of the project manager Oberlander (2003)

45. Level of team integration and aligment Oberlander (2003)

46. Review and acceptance of estimate by appropriate parties Oberlander (2003)

47. Attitude/culture forward changes Oberlander (2003)

48. Method used to determine contingency Oberlander (2003); Babalola (2006)

49. the conference estimate, Ashworth and Skitmore (1986)

50. comparison estimate, Ashworth and Skitmore (1986)

51. graphical relationships, Ashworth and Skitmore (1986)

52. unit techniques, Ashworth and Skitmore (1986)

53. functional approach, Ashworth and Skitmore (1986)

54. resource estimate Ashworth and Skitmore (1986)

23

55. factor estimate Ashworth and Skitmore (1986)

56 exponent estimate Ashworth and Skitmore (1986)

IV. ABILITY OF ESTIMATOR

57. Estimator expertise Iman Soeharto (2001) ; Babalola (2006)

58. Relevant experience of the estimating team Oberlander (2003); Ogunlana and Thorpe (1991)

59. Quality level of Estimator Skitmore (1990)

60. Attributes of Estimator Skitmore (1990)

61. Acquisition and application of expertise Skitmore (1990)

V. OTHER FACTOR CONSIDERED WHILE PREPARING THE ESTIMATE

62. Impact of project type Oberlander (2003)

63. Impact of contract type Oberlander (2003)

64. Impact of project schedule Oberlander (2003)

65. Impact of govermental requirements Oberlander (2003)

66. Work force Oberlander (2003)

67. Labour productivity Oberlander (2003)

68. Tax and insurence Oberlander (2003); Babalola (2006)

69. Money factors (currency, inflation, Oberlander (2003)

70. Bidding climate Oberlander (2003)

71. The nature of the competition / Bidding Competitiveness

Skitmore (1990); Babalola (2006)

72. Logistic for engineering and constructions Oberlander (2003)

Table 2.3. Factor Affecting Accuracy of Early Cost Estimate Source : (Skitmore, Ashworth, Ogunlana, Thorpe, Oberlander, Babalola, Iman Suharto)

24

CHAPTER 3

RESEARCH METHODOLOGY

3.1. Method Of Research

In general, the research methodology is a step-by-step or series of activities

starting from the beginning of the study until the final report of a study. The research

method is indispensable in providing guidelines for researchers to achieve the goals

and objectives of the study. The research method is closely related to procedures,

tools and research designs used. Research design, procedures and equipment used in

research must comply with the research method used. Based on the rules in scientific

research, following the steps used in this study (Figure 1.1).

Figure 3.1: Research Methodology

Source : (Nazir, 2005)

25

In this research method used is survey method, the research conducted to

obtain the facts from the existing symptoms and seek factual descriptions, whether of

social institutions, economics, or politics of a group or region. Survey methods to

dissect and skinning as well as recognize the problems and get the justification of the

status and practices that are in progress. (Nazir, 2005). Research conducted at the

same time against a number of individuals or units using sample.

The first step in doing research is to formulate the problem to be solved. To

remove any doubt the matter should be clearly identified, namely by defining the

extent the scope and limitations of the problem and research objectives to be

achieved. Scope / limitations of the problem and research objectives should be

consistent with the formulation and definition of the problem.

After the formulation of the problem, then proceed by searching for data

related to the topic of research. Study literature conducted to gain a deeper

understanding on the aspects studied. The data obtained from books and research

journals and the search for information via the Internet. In the field of science that

already have strong theories, it is necessary to formulate a theoretical framework or

conceptual framework which can then be derived in the form of hypotheses to be

tested.

After the data obtained in accordance with the problems to be solved, the next

step is to formulate a research hypothesis. The hypothesis is tentative conclusions

about the relationship between variables has to do anything to or phenomena in the

study. The hypothesis is a tentative conclusion that acceptable while before the test.

After the hypothesis set, the next step is to formulate ways to test the hypothesis.

Hypothesis testing based on a framework of analysis (analytical framework) which

has been set.

The hypothesis test requires data, the data can be primary data and secondary

data related to research problems. The data collected is in the form of facts that will

be used to test the hypothesis that has been formulated previously. Data collection

techniques vary depending on the problem to be solved and the research techniques

26

used. In this research a survey involving interviews of experts who are experts in cost

engineering. It is important to validate the data obtained through the study of

literature, so in accordance with the conditions of construction projects in Indonesia.

Then, based on information obtained from the literature and input from experts,

developed a questionnaire as a tool for collecting research data.

After the data collected, the data is arranged in advance to facilitate analysis.

Compilation of data can be in the form of tables and make coding which will then be

analyzed with the help of computer software. In this study, an analysis aimed at

identifying risk factors significant happens during the preparation of cost estimates

that affect the accuracy of preliminary cost estimates. A mathematical model of the

analytical results generated to reflect the relationship between phenomena that are

implicit contained in the hypothesis, which will then be tested by several statistical

techniques.

The analysis result obtained then interpreted and made generalizations based

on findings that there is, so few conclusions can be drawn. This conclusion should be

related to the research hypothesis that has been formulated previously. What is the

correct hypothesis to be accepted, or whether the hypothesis was rejected. What is

the relationship between the phenomena obtained will be applied generally or only

apply to the particular conditions only. What suggestions can be drawn from the

research and how their implications for adoption.

After the formulation of the problem, then proceed by searching for data

related to the topic of research. Study literature conducted to gain a deeper

understanding on the aspects studied. The data obtained from books, research

journals and other source that related to the topic of research.

Study literature conducted to gain a deeper understanding on the aspects

studied. In the study of theories of literature related to research topics collected. This

is done to obtain a broader orientation on the problems to be solved, and avoiding

duplication is undesirable. Aside from being a source of secondary data, literature

27

studies are also needed to know to which science-related research topics and to

develop where there are conclusions and degeralisasi ever made before.

Studies on the research literature discusses several topics related to the early

cost estimates of construction projects. The estimated cost of the project outline

discussed from the start definition, the process is done until the type and function of

the estimated project cost. In this section, early cost estimates discussed in more

depth, with respect to the functions and processes that must be passed. Explained

about some essential functions of a preliminary project cost estimates as cost

estimates were first made at an early stage where a new project starts.

3.2. Research Variables

After the research problem and research hypotheses are formulated and

carried out literature studies, further determined what variables to use in these

research. The variables that you want to use should be established, identified and

classified in accordance with the desired goals and objectives achieved (Nazir, 2005).

In this research, there are two research variable, is described as follows:

a. The independent variable or independent variable (Xi), ie the risk factors

that affect the accuracy of preliminary cost estimates, with i = 1,2,3, ...

b. Dependent variable or dependent variable (Y), namely the variable

measuring the level of accuracy of the preliminary cost estimates on

construction projects that are influenced by the variable X.

The variables of this research are the factors that affecting the accuracy of

early cost estimates. These factors were collected from various sources of literature

are used as secondary data used in evaluating the quality of early cost estimates

associated with the resulting level of accuracy. Research variables can see in chapter

2 table 2.2 Factor Affecting Accuracy of Early Cost Estimate

28

Research variables derived from a concept that needs to be clarified and

changed its shape so it can be measured and used operationally. Proper gauge for

measuring the variable or concept is very important. With the appropriate measuring

instruments, researchers can link an abstract concept to reality and to formulate and

test hypotheses without obtaining difficulty (Nazir, 2005). By using the size / scale of

the right of a concept or variable is qualitative, the concept or variable will have a

quantitative trait. In other words, the scale needed to change the attribute with the

qualitative characteristics into a quantitative variable.

3.4. Collection of Data

Data collections here mean a process of procurement of primary data and

secondary data for research purposes. Data collection is a very important step in the

scientific method, because the data collected is used to test the hypothesis that has

been formulated previously.

Variables obtained from the study of research literature to be seen again one

by one its relevance to the limits and scope of the research. Often these variables can

not be used because it does not comply with the limits that have been made

previously. Duplication of variables that mean the same should be avoided to get

good research data.

Interviews are one of the data collection techniques in the research process.

Data collected must be sufficiently valid to be used. In this study, variables derived

from prior literature study verified by experts through interviews with experts who

are competent, both from the practitioners and academicians. Interviews with experts

committed with intent to obtain or confirm a fact as well as to increase confidence

about the state of facts. Through interviews with experts, secondary data in the form

of risk variables that affect the accuracy of preliminary cost estimates obtained from

literature will be reduced or even be increasing in number. This is done to identify

the variables may not be found in the literature but significant happens in practice.

29

3.4.1 Questionnaire Research

Technique of primary data collection in this research is by distributing a list

of frequently called a questionnaire. The questionnaire contains questions based on

variables obtained through literature studies and inputs from experts who have done

previously. The questionnaire was divided into two parts, the first part contains data

on the background of the respondents and the second part is the core of the

questionnaire which contains the factors that affect the accuracy of preliminary cost

estimates.

In the survey questionnaire design, independent variables are arranged in a

list of questions about how the factors that affects the accuracy of preliminary cost

estimates that occurred in the project of the respondents. Answer the question made

in the form of options that have been prepared on a Likert scale with 5 (five) options.

The dependent variable in this study is the accuracy of preliminary cost

estimates as measured by comparing the cost estimates generated in the process of

project cost estimates with actual costs of the project, namely the costs incurred to

build the project / cost realization. The accuracy of preliminary cost estimates can be

measured in the formula:

Br - Be

Y = ----------------- x 100%

Be

Where: Y = The accuracy of the preliminary project cost estimate Br = Actual Cost Be = Cost Estimates

(Source : Ismed, 2008)

30

Choice accuracy was measured in the early cost estimate following scale:

Scale Quantitative Assessment Level Accuracy

1 - 50% ≤ Y ≤ - 30% or + 50% ≤ Y ≤ + 100%

Inaccurate

2 - 20% ≤ Y ≤ - 10 % or

+ 20% ≤ Y ≤ + 50% Less accurate

3 -10 % ≤ Y ≤ - 5 % or +10% ≤ Y ≤ + 20%

Fairly accurate

4 -5 % ≤ Y ≤ - 3 % or +5 % ≤ Y ≤ + 10%

Accurate

5 -3 % ≤ Y ≤ + 5% Very Accurate

Table 3.1 Likert scale level of accuracy early cost estimate

(Source : Analysis Result from AACE 18R-97 and ASTM E2516)

3.5. Data Analysis

From the data obtained and collated, it is necessary to look for patterns of

data analysis these factors. The analysis used should be a proper analysis of existing

data to manage, so the results are consistent with the objectives to be achieved.

The process of further analysis is to use the software help Microsoft Exel and

Statistical Product for Service Solution (SPSS). This analysis was conducted to

process data that has been distributed questionnaires to the respondents. SPSS

software is a computer application programs which are specifically used to analyze

statistical data. This analysis is done to see how much influence the risk variables on

the accuracy of preliminary cost estimates, which in turn acquired modeled

relationship model. Then do the test model in the form of quantitative analysis:

statistical analysis, correlation analysis, regression analysis, testing

heteroscedasticity, multicollinearity test, t test and F test.

31

3.5.1 Type of Data

The data to be used in the analysis of the questionnaire is interval data.

Interval data (also sometimes called integer) is measured along a scale in which each

position is equidistant from one another. This allows for the distance between two

pairs to be equivalent in some way. This is often used in psychological experiments

that measure attributes along an arbitrary scale between two extremes. In this case,

researcher determine level of accuracy, rate from 1 to 5 as a data. (ref :

changingminds.org)

3.5.2 Analysis Correlation

Correlation analysis is a numerical relationship between two random

variables. Correlation analysis aims to identify and find the relationship between

several variables that have been established for research. In the correlation test will

test how close the relationship between free variables and the dependent variable.

Correlation does not show any relationship, but merely gives an indication of

strength of the relationship between the variables.

The relationship of two variables declared with correlation coefficient (r).

The direction of the relationship between two variables can be divided into:

a. Direct correlation (positive correlation), namely a change in one variable

followed other changes regularly with the same direction of motion.

b. Inverse correlation (negative correlation), namely a change in one variable

followed by changes in other variables on a regular basis with movements in

the opposite direction.

c. Uncorrelated (No Correlation)

(1) Positive Correlation (2) Negative Correlation (3)Uncorrelated (No Correlation)

32

The relationship between variables produce positive or negative value with

the limit value of the coefficient correlation r (Pearson Correlation Coefficient) is 1

for positive correlation and -1 for negative correlation. If the value of correlation

coefficient close to zero, meaning there is no linear relationship between variables.

Diagram step of correlation analysis is as follows:

Input all variabel include accuracy into thevariables box . Correlation Coefficients : Pearson Test of significant : Two-tailed Flag significant correlation Options: Statistics : Means and standard deviations

Cross-product deviation and covariences Missing value : Exclude cases pairwise

Figure 3.2 Correlation Analysis Diagram

3.5.3 Regression Analysis

Correlation analysis is used to determine if there is a relationship between

two or more variables, while regression analysis is useful to predict how far the

influence of one or several independent variables on the dependent variable.

Regression analysis is one very important statistical analysis and mathematical

modeling related to the problem of a pair of observation data. Regression is a

statistical technique to determine the equation of a line or curve by minimizing the

deviation between observation data and the value of the regression equation. The

purpose of regression analysis in general is:

a. Determining the equation of the regression line based on the rate constants

and the resulting regression coefficients.

b. Finding correlations jointly between free and bound variables.

c. Testing the significance of independent variables affect the dependent

variable.

Correlate Bivariate OK

33

kk XaXaXaaY ++++= ...ˆ22110

Regression model generated from this regression analysis show quantitatively

the relationship between free variables X and Y, as follows:

Y = a + bX

(Sudjana 2005: 315).

Where:

a = Constant b = Regression coefficient X = Independent variable Y = Dependent Variable

This study uses multiple regression analysis that is a linear regression

analysis consists of a dependent variable and several independent variables. Multiple

linear regression analysis indicated the relationship between the regression equation:

(Sudjana 2005: 349).

( )2i

2i

iii2

ii

XXn )YX)(X()X)(Y(

a∑−∑

∑∑−∑∑=

( )2i

2i

iiii

XXn)Y)(X(-YXn b

∑−∑∑∑∑

=

∑ ∑ ∑∑ ∑ ∑ ∑

−

−= 2

212

22

1

22112

21

)())((

))(())((

iiii

iiiiiii

XXXX

YXXXYXXa

∑ ∑ ∑∑ ∑ ∑ ∑

−

−=

221

22

21

12122

12 )())((

))(())((

iiii

iiiiiii

XXXXYXXXYXX

a

22110 XaXaYa −−=

34

Where :

X1, X2, ..., Xk = Independent variable

Y = Dependent variable

0a = Constanta

kaaa ,...,, 21 = Regression coefficient

Diagram step of regression analysis is as follows:

d

Linear Regression :

Input variabel dependent

Input variabel independents

Method : Enter

Input Statistics

Input Plots

Figure 3.3. Regression Analysis Diagram

Regression model that has been obtained from regression analysis of model

validation should be qualified as follows:

1. Value Adjusted Square (R2) To measure the relationship between

independent variable X on variable Y has a minimum value of 0.5.

2. Value multi-collinearity has a maximum value of 18.

3. Regression coefficients must all be positive

In multiple regressions analysis is expected between the free variable (X)

there is no strong correlation because if this happens then the variable should not be

put into the equation. The existence of a strong correlation can be seen from the VIF

value > 10. If VIF < 10, then there is no strong correlations (multicolinearity).

Analyze Regression Linear OK

35

In practice, multiple regressions is more widely used because of the many

variables that need to be analyzed together, and also are generally more relevant

regression is used.

3.5.4 F test

F test used to test the null hypothesis (H0) that all coefficients of independent

variables Xi of the regression model is zero, and the alternative hypothesis is (Ha) is

that the entire value of the coefficient of variable X is not equal to zero. In other

words the ratio of F used to test the null hypothesis (H0), namely that free variables

together is not affected on the dependent variable, and alternative (Ha), namely that

the independent variables affect the dependent variable tehadap.

Good research data tend to come from the cause of the smaller of the result,

so there is clarity of contribution to the impacts generated. Variance is the difference

of each data with the average.

3.5.5 t test

t test used to test the null hypothesis (H0) that each coefficient of the regression

model is zero and the alternative hypothesis (Ha) is that if each coefficient of the

model is not equal to zero. If the null hypothesis is accepted means that the resulting

model can not be used to predict Y, otherwise if the hypothesis is rejected, then the

value of the resulting model can be used to predict the value of Y.

Criteria for testing this hypothesis is as follows:

H0 is rejected if t0 count > ta (n-k1) table

H0 is accepted if t0 count < ta (n-k-1) table

36

3.5.6 Auto Test Correlation (Durbin Watson Test)

Dubin Watson test was conducted to examine there is or there is no auto correlation

between the variables studied. Test the auto correlation with the value restriction

Durbin Watson (-2 < X < +2) to determine the presence or absence of residual

correlation or auto correlation of the resulting regression model.

3.5.7 Multicolinearity test

Multicollinearity is a condition in which independent variables in regression

equations have significant correlation with the other, or in other words there is a

correlation among independent variables (variables x). Parameters that can be used

as a benchmark whether or not multicollinearity is:

(a) Look at the correlation between pairs of variables: if the correlation

coefficients are greater than 0.80 (sometimes 0.90), the variables are strongly

correlated and should not be used.

(b) Use indicators that are calculated by SPSS

• Tolerance

The percentage of variance in a variable not associated with other

variables.

Tolerance has a range from zero to one. A value of near 1 indicates

independence.

If the tolerance value is close to zero, the variables are multicollinear.

As a rule of thumb, a tolerance of less than .20 indicates a problem

with multicollinearity.

• Variance inflation factor (VIF)

VIF is the inverse of the tolerance (1/tolerance). VIF has a range 1 to

infinity.

37

CHAPTER 4

ANALYSIS AND DISCUSSION

4.1. Preparation Research.

The approach taken in this research is through the methods of quantitative

statistical analysis of the correlation and regression analysis to determine significant

factors affecting the accuracy of early cost estimates.

The research data were collected from several sources of relevant literature.

By examining the duplication of variables-variables obtained from several sources of

literature and examine their relevance to the purpose and limitations of the study, the

factors that affect the accuracy of the preliminary cost estimate can be collected as

much as 72 variables.

Furthermore, to complement and verify the research variables is done by

interviews with experts. Three experts consisting of two practitioners and one

academic has reviewed and provided critical inputs in this study. Expert interview

process is focused on getting the factors that can not be obtained from literature

sources and confirmed based on their experience whether these factors are relevant to

the purposes and limitations of research that has been determined. Through expert

interviews obtained the factors that affect the accuracy of preliminary cost estimates

as many as 54 factors.

38

Here is a list of 54 factors that affect the accuracy of the preliminary cost

estimate after an interview with an expert who will then become the basis of

questions in the questionnaire:

I NATURE OF THE PROJECT

1. Type of the project

2. Size of Project / Scope of Project

3. Complexity of project

4. Geographical location / Site location

5. The contract procurement system

II THE LEVEL OF DATA AND INFORMATION AVAILABLE

6. Completeness of cost information

7. Accuracy and reliability of cost information

8. Applicability of cost information

9. Availability Project information / Documents used in Preparing the estimate

10. Capacities of project

11. Time allowed for Preparing the estimate

12. Technology: Method of construction

13. Project Processes

14. Project design criteria

15. Complexity of design and construction

16. Utility resources and supply conditions

17. Lead time for delivery of materials

18. Project Schedule

19. Project strategy

20. Frequency variations of construction

21. Client's financial situation

39

22. Owner's cost

23. Owner's experience level

24. Engineer / Designer 's experience level

25. The type of structure

III Techniques and Methods Used

26. Alignment of estimate methodologies, with available project information

27. Is the estimate work process formally define and Followed?

28. Categorized and a formal structure to prepare the estimate

29. Utilization of a checklist to Ensure completeness and technical base

30. Standard procedure is to update the cost data of the project

31. Documentation of information used in Preparing the estimate

32. Involvement of other resources in Preparing the estimates

33. Level of involvement of the project manager

34. Level of team integration and alignment

35. Review and acceptance of estimate by Appropriate parties

36. Attitude / culture forward changes

37. Method used to determine contingency

38. comparison estimate,

39. unit techniques,

40. functional approach,

41. resource estimate

42. factor estimate

IV ABILITY OF ESTIMATOR

43. Relevant experience of the estimating team

44. Quality level of Estimator / Estimator Expertise

45. Attributes of Estimator

40

46 Acquisition and application of expertise

V WHILE OTHER FACTOR Considered Preparing the Estimate

47. Impact of governmental requirements / regulation

48. Work force

49. Labour productivity

50. Tax and insurance

51. Money factors (currency, inflation, etc)

52. The prevailing economic climate


54. Logistic for engineering and Constructions

Table 4.1 Factor affecting the accuracy of early cost estimate after interview

with expert.

(Source : Analysis result expert questionnaire)

Collecting research data in the form of primary data done with the survey

method. The design of the questionnaire in the form of checklists factors that affect

the accuracy of preliminary cost estimates as the independent variable (variable X)

and dependent variable (variable Y) of the accuracy of preliminary cost estimates on

projects that have been addressed. Research questionnaire distributed 70

questionnaires to the respondent’s sebayak research. Respondents who became a

target for research data collection focused to the project owner, the contractor and the

project consulting Services Company that has been experienced in the preparation of

preliminary cost estimates of construction projects.

4.2. Data Analysis Questionnaires

The questionnaire collected as many as 50 samples. Category respondent is

cost estimator, project manager, construction manager, or site manager who have

experiences at least 5 (five) years in building construction project in Jakarta. Profile

of respondents can be seen in Table 4.1. From the questionnaire, the data collected

41

and then entered into the computer made the tabulation of data in Excel format to

facilitate the analysis process. The process is treated with assisted statistical analysis

software SPSS ver.17. The first analysis is the correlation analysis to measure the

strength of the relationship between variables X with variables Y And then proceed

with regression analysis to obtain regres model of the factors that affect the accuracy

of preliminary cost estimates.

Table 4.2. Profile of respondents

4.2.1 Analysis Correlation

Correlation analysis of the data obtained is performed to find the strength of

association between two variables, namely the factors of influence and level of

accuracy of the preliminary cost estimates. Data compiled by the survey results

tabulated in Microsoft Excel and then transpose into SPSS.

From the questionnaire data have been obtained, results of correlation

analysis can be seen in Table 4.3. as follows:

Variable

symbol Factors

THE EARLY

COST Accuracy

of Estimate

X1 Type of the project Pearson Correlation 0, 048

Sig. (2-tailed) 0, 742

N 50

X2 Size of Project / Scope of Project Pearson Correlation 0.279 *


N 50

X3 Complexity of project Pearson Correlation 0, 091


N 50

No. Type of Company Total

1. The project owner 3 2. Consultant 28 3. Contractor 19

42

X4 Geographical location / Site location Pearson Correlation 0.769 **


N 50

X5 The contract procurement system Pearson Correlation 0, 086


N 50

X6 Completeness of cost information Pearson Correlation 0, 182


N 50

X7 Accuracy and reliability of data /

information and document

Pearson Correlation 0, 105


N 50

X8 Applicability of cost information Pearson Correlation 0, 118


N 50

X9 Availability project information /

Documents used in Preparing the

estimate

Pearson Correlation 0.685 **


N 50

X10 Capacities of project Pearson Correlation -0, 115


N 50

X11 Time allowed for Preparing the estimate Pearson Correlation 0, 137


N 50

X12 Technology: Method of construction Pearson Correlation 0, 071


N 50

X13 Project Processes Pearson Correlation 0, 051


N 50

X 14 Project design criteria Pearson Correlation -0, 051


N 50

X15 Complexity of design and construction Pearson Correlation 0, 091


N 50

X16 Utility resources and supply conditions Pearson Correlation 0, 010


N 50

43

X17 Lead time for delivery of materials Pearson Correlation 0, 054


N 50

X18 Project Schedule Pearson Correlation -0, 078


N 50

X19 Project strategy Pearson Correlation 0, 056


N 50

X20 Frequency variations of construction Pearson Correlation -0, 048


N 50

X21 Client's financial situation Pearson Correlation 0, 069


N 50

X22 Owner's cost Pearson Correlation 0, 225


N 50

X23 Owner's experience level Pearson Correlation 0, 126


N 50

X24 Engineer / Designer 's experience level Pearson Correlation 0, 106


N 50

X25 The type of structure Pearson Correlation 0, 043


N 50

X26 Alignment of estimate methodologies,

with available project information



N 50

X27 Is the estimate work process formally

define and Followed?



N 50

X28 Categorized and a formal structure to

prepare the estimate



N 50

X29 Utilization of a checklist to Ensure

completeness and technical base



N 50

44

X30 Standard procedure is to update the cost

data of the project



N 50

X31 Documentation of information used in

Preparing the estimate



N 50

X32 Involvement of other resources in

Preparing the estimates



N 50

X33 Level of involvement of the project

manager



N 50

X34 Level of team integration and

alignment

Pearson Correlation 0.323 *


N 50

X35 Review and acceptance of estimate by

Appropriate parties



N 50

X36 Attitude / culture forward changes Pearson Correlation 0, 086


N 50

X37 Method used to determine contingency Pearson Correlation 0, 163


N 50

X38 comparison estimate, Pearson Correlation 0, 130


N 50

X39 unit techniques, Pearson Correlation 0, 010


N 50

X40 functional approach, Pearson Correlation 0, 060


N 50

X41 resource estimate Pearson Correlation -0, 008


N 50

X42 factor estimate Pearson Correlation 0, 121


N 50

45

X43 Relevant experience of the estimating

team



N 50

X44 Quality level of the estimator /

Estimator Expertise



N 50

X45 Attributes of Estimator Pearson Correlation 0, 264


N 50

X46 Acquisition and application of

expertise

Pearson Correlation 0.323 *


N 50

X47 Impact of governmental requirements /

regulation



N 50

X48 Work force Pearson Correlation 0, 117


N 50

X49 Labour productivity Pearson Correlation 0, 034


N 50

X50 Tax and insurance Pearson Correlation 0, 025


N 50

X51 Money factors (currency, inflation, etc) Pearson Correlation 0, 001


N 50

X52 The prevailing economic climate Pearson Correlation -0, 007


N 50

X53 The nature of the competition / Bidding

Competitiveness



N 50

X54 Logistic for engineering and

Constructions

Pearson Correlation -0, 233


N 50

* Correlation is significant at the 0:05 level (2-tailed). * * Correlation is significant at the 0:01 level (2-tailed).

Table 4.3. Coeficient Correlation and significant levels of variables

46

From the table 4.4. above can be seen which factors have a significant

correlation of early cost estimate accuracy indicated by the value significant level

<0.05.

The following variables-variables with correlation coefficient and a

significant degree of confidence:

Coef.

Correlation

Significant

Level

X2: Size of Project / Scope of Project 0.279 0.05

X4: Geographical location / Site location. 0.769 0.000

X9: Availability project information / Documents used

in Preparing the estimate. 0.685 0.000

X34: Level of team integration and alignment. 0.323 0.022

X43: Relevant experience of the estimating team. 0.447 0.001

X44: Quality level of the estimator / Estimator

Expertise. 0.437 0.001

X46: Acquisition and application of expertise. 0.323 0.022

X47: Impact of governmental requirements /

regulations. 0.749 0.000

Table 4.4. Factors that have a significant correlation of early cost estimate accuracy

(Source : Result of correlation analysis)

From the results of correlation analysis the correlation coefficient obtained

from the independent variable on the relationship with the dependent variable

showed a positive number (possitive / direct correlation), that is the change of

independent variable will cause a change in the dependent variable on a regular basis

and direction. So it can be concluded that if the performance of the variable X above

which are all factors that affect the accuracy of the preliminary cost estimate

increases, the accuracy of the preliminary cost estimate will increase.

47

4.2.2 Regression Analysis

Regression analysis conducted with the help of SPSS software ver. 17.

Through regression analysis can be seen how the strength of the relationship between

one or several independent variables with a dependent variable via a regression

model produced.

In this study it is assumed that the relationship between variables,

independent variables and the dependent variable is the liner, so the regression

analysis conducted in this study were linear regression analysis. In this regression

analysis, significant variables (X2, X4, X9, X34, X43, X44, X46 and X47) that have

been generated through correlation analysis of determinants included as independent

variables to generate a regression model. With regard to the value Adjusted R Square

and Coefficient Index it will produce a regression model that can express the

relationship between the independent variables significantly to the dependent

variable.

Results of initial regression analysis, can be seen in the following table:

Table 4.5: Model Summary

Table 4.6: Diagnostic collinearity

48

Table 4.7: Coefficient

On table 4.5 model summary, See figure Adjusted R Square is 0.711, it

shows the numbers Adjusted R Square good enough (near to 1).

On Table 4.6 Diagnostic collinearity, See figure Condition Index The

biggest is 37,213. Terms of model validation (test multicollinearity), Condition Index

must be ≤ 18. Therefore there are four variables that must be removed in order to

qualify validation. How to remove the variable is to look at the value Sig on Table

4.7 coefficient. Remove the 4 (four) variables have the high value Sig X46: X34:

X47, and X43. Then repeated the regression with independent variables X4, X44,

X9, and X2.

The results of the subsequent regression analysis, can be seen in the following

table:

Table 4.8 : Model Summary 1

49

Table 4.9 : Diagnostic collinearity 1

Table 4.10: Coefficients 1

On Table 4.8. Model Summary 1, See figure Adjusted R Square is 0.713, this

suggests there is an increasing number Adjusted R Square become better. On Table

4.9. Collinearity Diagnostic 1, Looks Condition Index produced the largest is 17.013,

which it has been qualified test models so that we can make it to see the regression

model coefficient in column B in Table 4.10. Coefficients 1.

The resulting regression model is as follows:

Y = 0.326 + 0.355 X4 + 0.243 X9 + 0.174 X44+ 0.054 X2

In the research, the data collected are often biased data (outliers) so it needs

to be re-examined data dissemination through Scatter plot - Regression Standardized

Predicted Value. The data is the outlier can be seen from the position data that are

beyond the threshold regression line with Confidence interval 95%. Therefore the

50

initial data (raw data) Should be re-examined and the data that acts as outlier should

be removed and then re-regression analysis was repeated so that the final regression

model can be generated.

The process of removal of outlier data and by performing repeated regression

analysis will increase the value adjusted R Square so that means that the reliability of

the resulting regression model will be better. On Charts - Y1 by * zpred scatterplot

in the regression analysis output can be seen early regression scatter diagram as

shown in figure 4.1 follows:

Figure 4.1. Scatter plot - Regression Standardized Predicted Value

In Figure 4.1 shows that the respondent no. 29 (R29) are beyond the

threshold regression, meaning that this data should be released. After the data no. 29

issued, performed the regression again to get a better regression model. The results of

the subsequent regression analysis can be seen in the following table:

51

Table 4.11 : Model Summary 2

Table 4.12 : Table Diagnostic collinearity 2

Table 4.13 : Table Coefficients 2

On Table 4.11. Model Summary 2, See figure Adjusted R Square is 0.791,

meaning there is a significant improvement from the previous model by removing

data no. 29.

52

The resulting regression model is as follows:

Y = 0.099 + 0.382 X4 + 0.245 X9 + 0.194 X44 + 0.056 X2

The process of removing data outliers and regression analysis is repeated

until all variables were obtained within the limits of regression. Outlier data that

should be eliminated in addition to data no. 29 is a data No.30, no.6, no.25, no. 24

and no. 40, so the final regression analysis performed with data as much as 44 data.

Final data obtained from the process which will then be used in the regression model.

Here are the final results of regression analysis produced:

Table 4.14: Model Summary (End)

Table 4.15: Coefficients (End)

53

Figure 4.2. Scatter plot - Regression Standardized Predicted Value (End)

On Table 4.14. Model Summary (end), Can be seen the value of Adjusted R

Square into 0.854, this shows the increased value of the Adjusted R Square initial

(0711). On Figure 4.2, the spread variable in the scatter plot shows the variables

inside the threshold of the final regression model regression so that we can produce

are as follows:

Y = 0.108 + 0.411 X4 + 0.208 X44 + 0.156 X9 + 0.096 X2

Where:

Y : Accuracy of early cost estimate. X4 : Geographical location / Site location.

X9 : Availability project information / Documents used in Preparing

the estimate. X44 : Quality level of the estimator / Estimator Expertise. X2 : Size of Project / Scope of the project.

54

4.2.3 Model Test

4.2.3.1 Linearity Test ( F Test )

F Test or Analysis of Variance (ANOVA) Aimed to test whether the resulting

regression model is linear or not. F test is done by looking at the data in table

ANOVA below that obtained from the regression analysis output.

Table 4.16 : ANOVA

Hypothesis:

H0 = not a linear regression model

H1 = linear regression model

Based on the output ANOVA obtained the Sig = 0.000 = 0% less than α (5%)

or the value of F = 63.762 more than the F table = F (4; 39; 0.05) = 2.61, then H0

rejected and H1 accepted. Thus is a linear regression model and the resulting

regression model is highly significant.

55

4.2.3.2 t Test

t-test (Student-t Distribution) Aims to determine the trust level of each

independent variable in regression equations or models used in predicting the value

of Y. usually t test is also called coeffisient test.

Hypothesis:

H0: regression coefficients not significant

H1: Significant regression coefficients

On Table 4.15. coefficient (end), can be seen the value of Sig. range is 0.000

- 0.047 or smaller than 0.05, and the value of t ranged between 2.052-8.538 more

than value t table = t (39; 0.05) = 1.686. then H0 rejected or H1 accepted. So the

regression coefficient for independent variable is significant

4.2.3.3 Autocorrelation Test (Durbin Watson Test)

Auto correlation test done to measure whether there is autocorrelation

between variables in different samples. Autocorrelation test with thresholds Durbin

Watson -2 To +2 to determine the presence or absence of residual correlation or auto

correlation of the resulting regression model. Value Durbin Watson generated

through the output of regression analysis can be seen in table. 4.14. model summary

(end), namely 1.891. The values are still within the limits of the value terms Durbin

Watson ie on the interval -2 < Durbin Watson <+2, So it can be concluded that the

resulting regression model does not occur auto correlation.

56

4.2.3.4 Multicollinearity Test

Based on the output Coefficients earned value tolerance in the between 0.646

– 0.901 is less than 1 and value of VIF in the between 1.109 - 1.549 is less than 10. It

means there is no multicollinearity.

4.3 Result of Research

Based on the results of research conducted, some variable determine accuracy

of early cost estimate (Geographical location / Site location, Availability project

information / Documents used in Preparing the estimate, Quality level of the

estimator / estimator Expertise and Size of Project / Scope of project) on the project

construction is valid, to see the results of model testing on the F test, Q test,

autocorelation test and multicollinearity tests.

57

CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.1 Introduction

Early cost estimate are cost estimates prepared in the early stages of planning the

project before the completion of engineering design made, therefore early cost estimates

have an important function as a starting point and a benchmark for project planning and

controlling in the future project stages. Quality early cost estimate can be measured from

its level of accuracy. Early cost estimates are prepared based on limited information and

supporting data, it causes in early cost estimates has the lowest level of accuracy than

any other types of cost estimates.

In this research, researcher want to identifying factors that affect the accuracy of

early cost estimates of construction projects and identifying relationship between the

factors and the accuracy of early cost estimates.

5.2 Conclusion

From the literature review, researcher found 72 factor affecting the accuracy of

early cost estimate. These factors reduce to 54 factors after interview with expert,.

Expert interview process is focused on getting the factors that cannot be obtained from

literature sources and confirmed based on their experience whether these factors are

58

relevant to the purposes and limitations of research that has been determined. The 54

factors that has been determined will be a basic question in the questionnaire that will be

spread to the respondent that would later analyzed using correlation analysis and

regression analysis.

From the results of the analysis in chapter 4, obtained 4 (four) significant factors

that affecting the accuracy of early cost estimate. These factors based on level of

affecting on accuracy, the sequence is as follows:

1. Geographical location / Site location.

2. Quality level of the estimator / Estimator Expertise.

3. Availability project information / Documents used in Preparing the Estimate.

4. Size of Project / Scope of the project

The relationship between the variables determining the accuracy early cost

estimate can be seen in the regression model below:

Y = 0.108 + 0.411 X4 + 0.208 X44 + 0.156 X9 + 0.096 X2

The other variables considered less influence on early cost estimate accuracy, but

it does not mean no effect at all. Cost estimator should always take into account all the

variables that affect accuracy in making early cost estimate, with a focus on the factors -

the most influential factors as mentioned above.

59

5.3 Limitation Of Research

Result of this research valid when used to determine early cost estimate at

building-construction project or similar project in Jakarta, Indonesia.

5.4 Recommendation For Future Research

Significant factors resulting from this research can be used as reference for cost

estimator when they prepare an early cost estimate for the next project and that results

can be developed in subsequent research that is for different types of projects or for

other types of cost estimates i.e. analysis of factor affecting the accuracy of early cost

estimate in highway construction project.

59

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Classification System. AACE Inc.,

AACE International Recommended Practice No. 34R-05. (2008), Basis of Estimate.

AACE Inc.,

AACE International Recommended Practice No. 40R-08. (2008), Contingency

Estimating – General Principles. AACE Inc.,

Aibinu, A. A., and Pasco, T., (2008), The accuracy of pre-tender building cost estimates

in Australia, Construction Management and Economics, Melbourne, Australia.

Ashworth, A and Skitmore, R. M. (1982), Accuracy in Estimating, Occasional paper no.

27, chartered Institute of Building, London

Asiyanto. (2003), Construction Project Cost Management. PT. Pradnya Paramita.

Jakarta,.

David Baccarini. (2004), Accuracy in Estimating Project Cost Construction Contingency

– A Statistical Analysis. RICS Construction and Building Research Conference.

RICS. London,

Iman Soeharto. (1999.), Manajemen Proyek (Dari Konseptual Sampai Operasional), Jilid

1. Edisi Kedua, Erlangga, Jakarta,

Iman Soeharto. (2001), Manajemen Proyek (Dari Konseptual Sampai Operasional),

Jilid 2. Edisi Kedua, Erlangga, Jakarta,.

60

Martin Brook. (2004), Estimating and Tendering for Construction Work. Third Edition,

Elsevier, Amsterdam,.

Morris, M. R. (1990). Improving the accuracy of early cost-estimates for federal

construction projects, Building Research Board, National Research Council,

Washington, D.C.

Oberlender, G. D., et al. (1998a). ‘‘Improving early estimates.’’ Research Summary 131-

1, Construction Industry Institute, Austin, Texas.

Oberlender, G. D., et al. (1998b). ‘‘Improving early estimates—Best practices guide.’’

Implementation Resource 131-2, Construction Industry Institute, Austin, Texas.

Oberlender, G. D., et al. (1998c). ‘‘Improving early estimates source document.’’

Research Rep. 131-11, Construction Industry Institute, Austin, Texas.

Oberlander, G. D., and Trost, S. M. (2001). ‘‘Predicting accuracy of early cost estimates

based on estimate quality.’’ J. Constr. Eng. Manage.

Oberlender. G. D., (2000), Project Management for Engineering and Construction. 2nd

Edition. McGraw-Hill Book Company Inc. New York,

O. Babalola and O.Aladegbaiye. (2006), Determining Appropriate Sum for Building

Projects. RICS Construction and Building Research Conference. RICS. London,

Phillip F. Ostwald. (2001), Construction Cost Analysis and Estimating. Prentice Hall,

New Jersey,.

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Edition, Blackwell Science Ltd, Oxford, UK,.

Robert L. Peurifoy and Garold D. Oberlender. (2004), Estimating Construction Cost.

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Roger Flanagan and George Norman. (1993), Risk Management and Construction.

Blackwell Science Ltd. London UK,.

Skitmore, Martin and Stradling, Steve and Tuohy, Alan and Mkwezalamba, Harry

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of Approximate Projects”, Building Research and Information, Singapore

APPENDIX A

Expert Interview

Research Questionnaire

Y

Accuracy

Influence Factors X

INTRODUCTION

Early cost estimates are cost estimates prepared in the early stages of the project is at feasibility study stage until just before the detailed design completed. Early cost estimates based on data and information is still limited as the initial concept of an outline of the scope of the project work. The existence of the limited available data and information is one of the preliminary cost estimate has lower accuracy compared to other types of cost estimates.

Early cost estimate for the cost estimates made in the first phase of the project cycle, so that early cost estimates are a starting point and a benchmark in determining the steps to be done next, for example in terms of planning and strategy development, determining project funding strategies, filter out projects which are the potential of its business, determines strategy project will be implemented, as a reference for the development of cost estimates and the subsequent engineering design, etc..

In the process of preparing early cost estimate, views of the importance of early estimates as a basis for decision making on the one hand, and on the other side where the accuracy of early cost estimates lower than other types of cost estimates, creating a stark contrast to conditions that are often experienced in the early stages of development conceptual project. That condition underlying author conduct this research, Thus the title of research is : ANALYSIS OF FACTORS AFFECTING THE ACCURACY OF EARLY COST ESTIMATE IN CONSTRUCTION PROJECTS

The quality of cost estimates associated with the accuracy and completeness of its elements. The accuracy of the estimated project cost depend on: nature of project, the level of data and information available, techniques and methods used, ability of the estimator, and other factor considered while preparing the estimate. Relationship accuracy of the supporting elements can be described as follows.

This study aimed to identify factors that influence the accuracy of preliminary cost estimates for construction project will then be analyzed by quantitative methods in order to find the significant factors on the accuracy of preliminary cost estimates. These factors result from the analysis are expected to provide input on matters that need to be prepared, techniques and methods used, the required procedures and other matters related to the process of preliminary cost estimates in order to produce a preliminary cost estimate is accurate.

Sincerely, Researcher: Supervisor: Dodi Ardianto, ST Assoc. Prof. DR. Razali Abdul Hamid email: [email protected]

mailto:email:%[email protected]

DATA OF EXPERT

( .............................. )

1. Name :

2. Company :

3. Profession / Department :

4. Work Experience : Year

5. Project Name :

6. Project Locat ion :

7. Year Project Completed :

COMMENTS AND SUGGESTIONS

Jakarta, / / 2011

Questionnaire Instructions

1. Filling this questionnaire based on your experiences and perceptions.

2. Filling the questionnaire was done by answering the question: "Do You Agree

Variables Below Affecting Accuracy of Early Cost Estimate?"

3. Optional answers were: YES or NO

4. Filling an answer by providing the sign of [] In the column provided.

5. When there are other things that need to be added, please enter the last row in the table

"Do You Agree Variables Below Affecting Accuracy of Early Cost Estimate?"


Yes No


2. Size of project / Scope of project


4. Other project characteristics




Other factors that need to be added


Yes No


9. Quality of information



12. Availability Project information/Documents used in preparing the estimate


14. Time allowed for preparing the estimate

15. Technology; Method of construction

16. Processes project

17. Piping & Instrumentation Diagrams

18. Amount of special work likely production time




22. Heat and material balances

23. Mechanical equipment list



26. The form of procurement and contractual agreement


28. The extent of completion of pre-contract decision

29. Frequency of construction variations

30. Client’s financial situation

31. Owner’s cost

32. Purpose and intended use of estimate

33. Owner’s experience level

34. Engineer/Designer’s experience level

35. Environmental assessment and workforce




Yes No

37. Alignment of estimate methodology

38. Is the estimate work process formally define and followed?

39. Formal structure to categorized and prepare the estimate

40. Utilization of checklist to ensure completeness and technical basis

41. Standard procedure to update cost data of project

42. Documentation of information used in preparing the estimate

43. Involvement of other resources in preparing the estimates



46. Review and acceptance of estimate by appropriate parties

47. Attitude/culture forward changes


49. the conference estimate,


51. graphical relationships,




55. factor estimate

56 exponent estimate



Yes No

57. Estimator expertise


59. Quality level of Estimator




V OTHER FACTOR CONSIDERED WHILE PREPARING THE ESTIMATE

Yes No

62. Impact of project type

63. Impact of contract type

64. Impact of project schedule


66. Work force



69. Money factors

70. Bidding climate


72. Logistic for engineering and constructions


APPENDIX B

Questionnaire

Research Questionnaire

Y

Accuracy

Influence Factors X

INTRODUCTION

Early cost estimates are cost estimates prepared in the early stages of the project is at feasibility study stage until just before the detailed design completed. Early cost estimates based on data and information is still limited as the initial concept of an outline of the scope of the project work. The existence of the limited available data and information is one of the preliminary cost estimate has lower accuracy compared to other types of cost estimates.

Early cost estimate for the cost estimates made in the first phase of the project cycle, so that early cost estimates are a starting point and a benchmark in determining the steps to be done next, for example in terms of planning and strategy development, determining project funding strategies, filter out projects which are the potential of its business, determines strategy project will be implemented, as a reference for the development of cost estimates and the subsequent engineering design, etc..

In the process of preparing early cost estimate, views of the importance of early estimates as a basis for decision making on the one hand, and on the other side where the accuracy of early cost estimates lower than other types of cost estimates, creating a stark contrast to conditions that are often experienced in the early stages of development conceptual project. That condition underlying author conduct this research, Thus the title of research is : ANALYSIS OF FACTORS AFFECTING THE ACCURACY OF EARLY COST ESTIMATE IN CONSTRUCTION PROJECTS

The quality of cost estimates associated with the accuracy and completeness of its elements. The accuracy of the estimated project cost depend on: nature of project, the level of data and information available, techniques and methods used, ability of the estimator, and other factor considered while preparing the estimate. Relationship accuracy of the supporting elements can be described as follows.

This study aimed to identify factors that influence the accuracy of preliminary cost estimates for construction project will then be analyzed by quantitative methods in order to find the significant factors on the accuracy of preliminary cost estimates. These factors result from the analysis are expected to provide input on matters that need to be prepared, techniques and methods used, the required procedures and other matters related to the process of preliminary cost estimates in order to produce a preliminary cost estimate is accurate.

Sincerely, Researcher: Supervisor: Dodi Ardianto, ST Assoc. Prof. DR. Razali Abdul Hamid email: [email protected]

mailto:email:%[email protected]

RESPONDENT DATA & REFERENCE PROJECT

( .............................. )

1. Respondent Name :

2. Company Name :

3. Profession / Department :

4. Work Experience : Years

5. Project Name :

6. Project Locat ion :

7. Year Project Completed :

COMMENTS AND SUGGESTIONS

Jakarta, / / 2011

Questionnaire Research

In this questionnaire is expected to be completed by respondent under conditions where

the project is on early stages conceptual project before detail design produced, by

answering t h e q u e s t i o n : how the factors below on your project?

Check [ X] Or CLICK one time in the column provided on your answer to one of the

options. Please read carefully and thoroughly before giving answers.


What Was Known About The Project?

Answer (1) : Do not Know (2) : Little Bit Know (3) : Average Know (4) : Many Know (5) : Really Know

1 2 3 4 5


2. Size of project /Scope of Project





How is the availability of data and information below on your project?

Answer (1) : Not Available At All (2) : Few Available (3) : Fairly Available

(4) : Many Available (5) : Highly Available

1 2 3 4 5




9. Availability Project information/Documents used in preparing the estimate


11. Time allowed for preparing the estimate

12. Technology; Method of construction

13. Processes project







20. Frequency of construction variations

21. Client’s financial situation

22. Owner’s cost

23. Owner’s experience level

24. Engineer/Designer’s experience level



How the use of the techniques and methods of early cost estimates on your project?

Answer (1) : Not Used At All (2) : Sl ightly Used (3) : Used

(4) : Often Used (5) : Always Used

1 2 3 4 5

26. Alignment of estimate methodology with available project information

27. Is the estimate work process formally define and followed?

28. Formal structure to categorized and prepare the estimate

29. Utilization of checklist to ensure completeness and technical basis

30. Standard procedure to update cost data of project

31. Documentation of information used in preparing the estimate

32. Involvement of other resources in preparing the estimates



35. Review and acceptance of estimate by appropriate parties

36. Attitude/culture forward changes






42. factor estimate


How the skills and experience of estimator in your project?

Answer (1) : Very Bad (2) : Bad (3) : Average (4) : Good (5) : Very Good

1 2 3 4 5


44. Quality level of Estimator / Estimator Expertise



V OTHER FACTOR CONSIDERED WHILE PREPARING THE ESTIMATE

How the factors below related to the preparation of cost estimates on your project?

Answer (1) : Does not affect (2) : Little bit affect (3) : Affect (4) : Much Affect (5) : Very Affect

1 2 3 4 5


48. Work force



51. Money factors (currency, inflation, etc)



54. Logistic for engineering and constructions

Questionnaire part II:

1 2 3 4 5

VI How big is the accuracy of preliminary cost estimates generated in your project?

(Put a [X] Or CLICK one time in the column provided on one of your answer choices)

Charging indicators: 1. Criteria the accuracy of preliminary cost estimates:

Scale Quantitative Assessment Level Accuracy

1 - 50% ≤ Y ≤ - 30% or + 50% ≤ Y ≤ + 100% Inaccurate

2 - 20% ≤ Y ≤ - 10 % or + 20% ≤ Y ≤ + 50% Less accurate

3 -10 % ≤ Y ≤ - 5 % or +10% ≤ Y ≤ + 20% Fairly accurate

4 -5 % ≤ Y ≤ - 3 % or +5 % ≤ Y ≤ + 10% Accurate

5 -3 % ≤ Y ≤ + 5% Very Accurate

2. Calculating the accuracy of preliminary cost estimates can be measured by the formula:

Br - Be Y = ----------------- x 100%

Be

Where: Y = The accuracy of the preliminary project cost estimate Br = Actual Cost Be = Cost Estimates

APPENDIX C

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Accuracy of Early Estimate_Dodi

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