Data Mining Predictive

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DATA MINING PREDICTIVE Disusun oleh: Hendy Jati S. 112081054 Norman Akbar 112090116 Tiara I. Pratiwi 112090205

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Page 1: Data Mining Predictive

DATA MINING PREDICTIVE

Disusun oleh:Hendy Jati S. 112081054Norman Akbar 112090116Tiara I. Pratiwi112090205

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Defi-nition

Damin &

Busi-ness

Intelli-gence

Damin

Metho-dology

Appli-cation

on Mar-

keting&CRM

Pro-blem Sol-

vable with

Damin

Study Case

Soft-ware

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1DEFINITION

DATA MINING

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Sekumpulan Data Pola Informasi

Data Mining

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2DATA MINING &

BUSINES

S INTELLIGE

NCE

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Damin & Business Intelligence

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3Data Mining

Methodology

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4Application onMarketing &

CRM

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APPLICATION ON MARKETING & CRM

Mengidentifikasi calon pelanggan yang baik (good prospect)

Memilih saluran komunikasi untuk mecapai calon pelanggan

Memilih pesan yang tepat untuk berbagai kelompok calon pelanggan

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Data Mining to Choose the Right Place to Advertise

Data Mining to Improve Direct Marketing Campaigns

Using Current Customers to Learn About Prospects

Data Mining for Customer Relationship Management

FUNGSI

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5Problem Solvable

With Damin

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PREDIKTIF

CLASIFICATION

ESTIMATION

PREDICTION

DESKRIPTIF

CLUSTERING

ASSOCIATION RULE DISCOVERY

SEQUENTIAL PATTERN DISCOVERY

Problem Solvable

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Prediktif

Data Variabel

Unknown Value

Future

Value

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CLASSIFICATION

ModelData

Kelas

Periksa karakteristik

Input ke kelas yg sudah terdefinisi

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Input

Training Data Set

Classifier Output

Model Teknik-teknik yang digunakan

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CLASSI-FICATION

Decision Tree

Neural Networks

Rule-based Method

Naive Bayes & Bayesian Belief

networks

CLASSIFICATION TECHNIQUE

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Decision Tree

+ -

Mudah

Hemat

Biaya

Hemat

waktu

Tidak untuk

data

kompleks

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Neural Networks

(+) (-)

Akurasi tinggi

Paralel

Mudah diupdate

Untuk data yg

kompleks

Sulit untuk

diimplementasikan

Mahal

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Rule based method

Pola data Unknown Value

Frekuensinya Besar

Kelemahan:Suksesnya klasifikasi data, bergantung pada banyaknya data yang tersimpan

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Naive Bayes & Bayesian Belief Network

Minimasi Cost

Mudah diimplementasi

Minimasi kebutuhan data training

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Estimation

• Data

Input• Nilai

kontinu

Output

Proses pengolahan

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Prediction

Data Classification Future Value

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6STUDY CASE

TARGET

CORPORATION

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Let’s enjoy this Video !!!

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Retail Industry

1st Place

2nd Place

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History

• Founded by George Dayton

• Dayton Dry Goods Company

1902

• First Store, in Roseville Minnesota

1962

• Renamed as Target Corporation

2000

• Total 1357 Store

2005

• Expansion to Canada

2011

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Problem

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Solve

Data Mining

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7Software

Karma

CRM

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Why KarmaCRM?

No more miss moment

Good karma, anywhere

perfect balance

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Feature

Symple contact

management

Team management

Third party integration

Flexible reporting

Manage your sales Process

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System Requirements

• Hanya memerlukan web browser seperti firefox, chrome, Opera

• Juga dapat digunakan via mobile dengan dengan web browser yang ada di smartphone

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