SINTAKSIS SPSS
Transcript of SINTAKSIS SPSS
BAHASA SINTAKSIS DALAM IBM SPSS STATISTICSBAGIAN KESATU
Oleh :Abdullah M. Jaubah
BAHASA SINTAKSIS DALAM IBM SPSS STATISTICSBAGIAN KESATUOleh :Abdullah M. Jaubah
PendahuluanBeberapa dokumen dari University of California Los Angles dipakai di sini untuk menyusun sintaksis gabungan yang terkandung dalam beberapa dokumen tersebut. Sebagian besar contoh yang disajikan di sini memakai arsip data hsb2.sav. Arsip data ini sangat terkenal dan merupakan arsip data mengenai sekolah menengah atas. Arsip data ini mengandung 200 observasi dari suatu sampel siswa sekolah menengah atas dengan informasi demografi tentang para siswa, seperti jenis kelamin, status sosial-ekonomi, dan latar belakang suku bangsa. Arsip data ini juga mengandung skor atas ujian-ujian terstandar dan mencakup pengujian tentang bacaan, tulisan, matematika, pengetahuan umum, dan studi-studi sosial. Beberapa dokumen ini dipakai karena pembahasan yang terkandung adalah sangat penting karena dapat dipakai untuk melakukan pengembangan lebih lanjut. Beberapa dokumen ini dapat dipakai untuk beberapa penelitian misalkan penelitian mengenai skor para mahasiswa Program Studi Administrasi Negara Universitas Swasta dan skor para mahasiswa Program Studi Administrasi Negara Universitas Negeri, skor para mahasiswa Program Studi Hubungan Internasional Universitas Swasta dan skor para mahasiswa Program Studi Hubungan Internasional Universitas Negeri, skor para mahasiswa Program Studi Akuntansi Universitas Swasta dan skor para mahasiswa Program Studi Akuntansi Universitas Negeri, skor para mahasiswa Program Studi Manajemen Universitas Swasta dan skor para mahasiswa Program Studi Manajemen Universitas Negeri, dan beberapa program studi lain. Beberapa dokumen yang dipakai itu mencakup dokumen Annotated Output. Dokumen ini mengandung contoh-contoh program, hasil-hasil, dan penjelasan makna dari hasil-hasil tersebut. Dokumen ini mencakup pembahasan mengenai Descriptive Statistics, Correlation, Regression, T-Test, Logistic Regression, Multinomial Logistic Regression, Ordinal Logistic Regression, Probit Regression, Poisson Regression, Principal Components Analysis, Factor Analysis, One Way Manova, Discriminant Function Analysis, dan Canonical Correlation Analysis.Dokumen kedua yang dipakai di sini adalah Statistical analyses using SPSS dan dokumen ketiga adalah statistical tests using SPSS. Kedua dokumen ini mengandung pembahasan mengenai One sample t-test, One sample median test, Binomial test, Chi-square goodness of fit, Two independent samples t-test, Wilcoxon-Mann-Whitney test, Chi-square test, One-way ANOVA, Kruskal Wallis test, Paired t-test, Wilcoxon signed rank sum test, McNemar test, One-way repeated measures ANOVA, Repeated measures logistic regression, Factorial ANOVA, Friedman test, Ordered logistic regression, Factorial logistic regression, Correlation, Simple linear regression, Non-parametric correlation, Simple logistic regression, Multiple regression, Analysis of covariance, Multiple logistic regression, Discriminant analysis, One-way MANOVA, Multivariate multiple regression, Canonical correlation, Factor analysis, One sample t-test, One sample median test, Binomial test, Chi-square goodness of fit, Two independent samples t-test, Wilcoxon-Mann-Whitney test, Chi-square test, One-way ANOVA, Kruskal Wallis test, Paired t-test, Wilcoxon signed rank sum test, McNemar test, One-way repeated measures ANOVA, Repeated measures logistic regression, Factorial ANOVA, Friedman test, Ordered logistic regression, Factorial logistic regression, Simple linear regression, Non-parametric correlation, Simple logistic regression, Multiple regression, Analysis of covariance, Multiple logistic regression, Discriminant analysis, One-way MANOVA, Multivariate multiple regression, Canonical correlation, dan pembahasan mengenai Factor analysis.
Ketiga dokumen tersebut tidak memakai cara point and click akan tetapi memakai bahasa sintaksis SPSS. Bahasa Sintaksis dalam IBM SPSS Statistics memainkan peranan penting dan mempunyai hubungan yang sangat erat dengan cara pemakaian menu SPSS. Sintaksis gabungan disusun di sini berdasar atas sintaksis mandiri yang terkandung dalam ketiga dokumen di atas.Pembahasan ini terdiri dari dua bagian. Bagian kesatu adalah bagian penciptaan bahasa sintaksis dan penyajian hasil pelaksanaan bahasa sintaksis tersebut. Bagian kedua adalah bagian interpretasi hasil-hasil pelaksanaan bahasa sintaksis tadi. Bagian ini merupakan bagian kesatu. Penciptaan bahasa sintaksis ini akan mencakup sintaksis mengenai descriptives, explore, correlation, nonparametric correlation, t-test, paired test, independent group test, one sample madian test, binomial test, chi-squared goodness of fit, two independent samples t-test, Wilcoxon-Mann-Whitney test, chi-squared test, one way Anova, Kruskal Wallis test, paired t-test, Wilcoxon signed rank sum test, McNemar Test, Friedman test, simple lienar regression, multiple regression, multivariate multiple regression, analysis of covariance, simple logistic regression, logistic regression, multiple logistic regression, crosstabs dan logistic regression, ordered logistic regression, factorial logistic regression, factor analysis, factor analysis, discriminant analysis, one way manova, canonical correlation, dan one way repeated measures anova.Penyusunan sintaksis dapat dilakukan secara acak, dapat dilakukan secara mandiri, dan dapat pula dilakukan secara gabungan. Peluang penyusunan secara gabungan dipilih di sini.Arsip DataArsip data yang dipakai di sini dinamakan Citra.sav. Arsip data ini terdiri dari 10 variabel, tiga variabel berjenis nominal, satu variabel berjenis ordinal, dan enam variabel berjenis scale. Hal ini berarti bahwa 4 variabel merupakan variabel bersifat kualitatif dan 6 variabel bersifat kuantitatif. Variabel honcom dicipta sebagai variabel berjenis nominal. Nama-nama variabel adalah X1 sampai dengan X10, dan variabel honcom.Variabel X1 adalah Nomor Induk Mahasiswa, variabel X2 adalah jenis kelamin para mahasiswa, variabel X3 adalah variabel tempat kelahiran para mahasiswa, variabel X4 adalah variabel status sosial keluarga para mahasiswa, variabel X5 adalah variabel konsentrasi yang dipilih oleh tiap mahasiswa, variabel X6 adalah nilai matakuliah Manajemen Produtivitas, Variabel X7 adalah nilai matakuliah Manajemen Produksi, variabel X8 adalah variabel nilai matakuliah Sumberdaya Manusia, variabel X9 adalah variabel nilai matakuliah Prakiraan Bisnis, variabel X10 adalah variabel nilai matakuliah Manajemen Keuangan. Jenis kelamin memakai kode 0 untuk mahasiswa Laki-laki dan kode 1 untuk mahasiswa Perempuan. Variabel tempat kelahiran mengandung kode 1 = Jawa, 2 = Sumatera, 3 = Kalimantan, 4 =Sulawesi-Papua. Status sosial mengandung kode 1 = Rendah, 2 = Menengah, dan 3 = Tinggi. Konsentrasi mencakup kode 1 = Pemasaran, 2 = Keuangan, dan 3 = Sumberdaya Manusia. Jumlah kasus atau jumlah observasi adalah 200 responden. Arsip data dalam SPSS ditampung dalam Data View dan Variable View. Penyajian arsip data dalam Data View dan Variable View disajikan di bawah ini :
Data View
Variable ViewVariable View mengandung spesifikasi dari arsip data. Spesifikasi ini mencakup Type, Name, Width, Decimals, Label, Values, Missing, Columns, Align, Measure, dan Role. Variabel-variabel yang dipakai adalah NIM (X1), Jenis Kelamin (X2), Tempat Kelahiran (X3), Status Sosial (X4), Jenis Universitas (X5), Konsentrasi (X6), nilai ujian matakuliah Manajemen (X6), Manajemen Produksi (X7), Manajemen Pemasaran (X8), Manajemen Keuangan (X9), Manajemen Kepegawaian (X10), dan variabel Honcom (X11). Arsip data ini dinamakan Citra.sav. Arsip data Citra1 dapat dicipta dengan cara mengganti nilai ujian matakuliah Ekonomi Manajerial (X6), Manajemen Keuangan Internasional(X7), Manajemen Pemasaran Internasional (X8), Manajemen Produktivitas (X9), dan Prakiraan Bisnis (X10). Arsip data Citra1.sav dapat memakai sintaksis yang sama hanya mengganti sedikit perintah FILE='D:\AAMUL\CITRA.SAV'. menjadi perintah FILE='D:\AAMUL\CITRA1.SAV'. Hal ini berarti bahwa bahasa sintaksis SPSS adalah sangat tangguh jika dibanding dengan cara point and click. Data View adalah sebagai berikut :
Bahasa SintaksisPenyusunan bahasa sintaksis tidak teratur seperti uraian di atas akan tetapi secara acak dan mandiri. Bahasa sintaksis ini adalah sebagai berikut :Descriptives****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** DESCRIPTIVES*************************************************
DESCRIPTIVES VARIABLES=X8 /STATISTICS=MEAN SUM MIN MAX.
DESCRIPTIVES VARIABLES=X8 /STATISTICS=STDDEV VARIANCE RANGE.
DESCRIPTIVES VARIABLES=X8 /STATISTICS=KURTOSIS SKEWNESS.
DESCRIPTIVES VARIABLES=X7 /STATISTICS=MEAN SUM MIN MAX.
DESCRIPTIVES VARIABLES=X7 /STATISTICS=STDDEV VARIANCE RANGE.
DESCRIPTIVES VARIABLES=X7 /STATISTICS=KURTOSIS SKEWNESS.
DESCRIPTIVES VARIABLES=X8 X7 X9 X10 X11 /STATISTICS=MEAN SUM MIN MAX.
DESCRIPTIVES VARIABLES=X8 X7 X9 X10 X11 /STATISTICS=STDDEV VARIANCE RANGE.
DESCRIPTIVES VARIABLES=X8 X7 X9 X10 X11 /STATISTICS=KURTOSIS SKEWNESS.
Pelaksanaan sintaksis ini akan menghasilkan informasi sebagai berikut :
Descriptive Statistics
NMinimumMaximumSumMean
X820031.0067.0010555.0052.7750
Valid N (listwise)200
Descriptive Statistics
NRangeStd. DeviationVariance
X820036.009.4785989.844
Valid N (listwise)200
Descriptive Statistics
NSkewnessKurtosis
StatisticStd. ErrorStatisticStd. ErrorStatisticStd. Error
X8200-.482.172-.750.342
Valid N (listwise)200
Descriptive Statistics
NMinimumMaximumSumMean
X720028.0076.0010446.0052.2300
Valid N (listwise)200
Descriptive Statistics
NRangeStd. DeviationVariance
X720048.0010.25294105.123
Valid N (listwise)200
Descriptive Statistics
NSkewnessKurtosis
StatisticStd. ErrorStatisticStd. ErrorStatisticStd. Error
X7200.196.172-.623.342
Valid N (listwise)200
Descriptive Statistics
NMinimumMaximumSumMean
X820031.0067.0010555.0052.7750
X720028.0076.0010446.0052.2300
X920033.0075.0010529.0052.6450
X1020026.0074.0010370.0051.8500
X1120026.0071.0010481.0052.4050
Valid N (listwise)200
Descriptive Statistics
NRangeStd. DeviationVariance
X820036.009.4785989.844
X720048.0010.25294105.123
X920042.009.3684587.768
X1020048.009.9008998.028
X1120045.0010.73579115.257
Valid N (listwise)200
Descriptive Statistics
NSkewnessKurtosis
StatisticStd. ErrorStatisticStd. ErrorStatisticStd. Error
X8200-.482.172-.750.342
X7200.196.172-.623.342
X9200.287.172-.649.342
X10200-.189.172-.556.342
X11200-.382.172-.525.342
Valid N (listwise)200
Explore****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** EXPLORE*************************************************
EXAMINE X8 /PLOT BOXPLOT STEAMLEAF HISTOGRAM /PERCENTILES(5,10,25,50,75,90,95,99).
Case Processing Summary
Cases
ValidMissingTotal
NPercentNPercentNPercent
X8200100.0%00.0%200100.0%
Descriptives
StatisticStd. Error
X8Mean52.7750.67024
95% Confidence Interval for MeanLower Bound51.4533
Upper Bound54.0967
5% Trimmed Mean53.1389
Median54
Variance89.844
Std. Deviation9.47859
Minimum31
Maximum67
Range36
Interquartile Range14.75
Skewness-0.4820.172
Kurtosis-0.750.342
Percentiles
Percentiles
510255075909599
Weighted Average(Definition 1)X835.053945.255460656567
Tukey's HingesX845.55460
X8 Manajemen Produksi
Manajemen Produksi Stem-and-Leaf Plot
Frequency Stem & Leaf
4.00 3 . 1111 4.00 3 . 3333 2.00 3 . 55 5.00 3 . 66777 6.00 3 . 899999 13.00 4 . 0001111111111 3.00 4 . 223 13.00 4 . 4444444444445 11.00 4 . 66666666677 11.00 4 . 99999999999 2.00 5 . 00 16.00 5 . 2222222222222223 20.00 5 . 44444444444444444555 12.00 5 . 777777777777 25.00 5 . 9999999999999999999999999 8.00 6 . 00001111 22.00 6 . 2222222222222222223333 16.00 6 . 5555555555555555 7.00 6 . 7777777
Stem width: 10.00 Each leaf: 1 case(s)
Correlation****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** CORRELATION*************************************************
CORRELATIONS /VARIABLES = X7 X8 X9 X10 X2 /PRINT = NOSIG.
GRAPH /SCATTERPLOT(BIVAR) = X8 WITH X7.
CORRELATIONS /VARIABLES = X7 X8 X9 X10 X2 /PRINT = NOSIG /MISSING = LISTWISE.
Correlations
X7X8X9X10X2
X7Pearson Correlation1.597**.662**.630**-.053
Sig. (2-tailed).000.000.000.455
N200200200200200
X8Pearson Correlation.597**1.617**.570**.256**
Sig. (2-tailed).000.000.000.000
N200200200200200
X9Pearson Correlation.662**.617**1.631**-.029
Sig. (2-tailed).000.000.000.680
N200200200200200
X10Pearson Correlation.630**.570**.631**1-.128
Sig. (2-tailed).000.000.000.071
N200200200200200
X2Pearson Correlation-.053.256**-.029-.1281
Sig. (2-tailed).455.000.680.071
N200200200200200
**. Correlation is significant at the 0.01 level (2-tailed).
Correlationsb
X7X8X9X10X2
X7Pearson Correlation1.597**.662**.630**-.053
Sig. (2-tailed).000.000.000.455
X8Pearson Correlation.597**1.617**.570**.256**
Sig. (2-tailed).000.000.000.000
X9Pearson Correlation.662**.617**1.631**-.029
Sig. (2-tailed).000.000.000.680
X10Pearson Correlation.630**.570**.631**1-.128
Sig. (2-tailed).000.000.000.071
X2Pearson Correlation-.053.256**-.029-.1281
Sig. (2-tailed).455.000.680.071
**. Correlation is significant at the 0.01 level (2-tailed).
b. Listwise N=200
Nonparametric correlation ****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** NONPARAMETRIC CORRELATION*************************************************
NONPAR CORR /VARIABLES = X7 X8 /PRINT = SPEARMAN.
Correlations
X7X8
Spearman's rhoX7Correlation Coefficient1.000.617
Sig. (2-tailed)..000
N200200
X8Correlation Coefficient.6171.000
Sig. (2-tailed).000.
N200200
T-test
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** T-TEST*************************************************
T-TEST /TESTVAL=50 /MISSING=ANALYSIS /VARIABLES=X8 /CRITERIA=CI(.95).
One-Sample Statistics
NMeanStd. DeviationStd. Error Mean
X820052.77509.47859.67024
One-Sample Test
Test Value = 50
tdfSig. (2-tailed)Mean Difference95% Confidence Interval of the Difference
LowerUpper
X84.140199.0002.775001.45334.0967
Paired test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** PAIERD TEST*************************************************
T-TESTPAIRS=X8 WITH X7 (PAIRED).
Paired Samples Statistics
MeanNStd. DeviationStd. Error Mean
Pair 1X852.77502009.47859.67024
X752.230020010.25294.72499
Paired Samples Correlations
NCorrelationSig.
Pair 1X8 & X7200.597.000
Paired Samples Test
Paired DifferencestdfSig. (2-tailed)
MeanStd. DeviationStd. Error Mean95% Confidence Interval of the Difference
Pair 1X8 - X70.5458.886670.62838-0.6941.784140.8671990.387
Independent group test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** INDEPENDENT GROUP TEST*************************************************
T-TEST GROUPS=X2(0 1)/VARIABLES=X8.
Group Statistics
X2NMeanStd. DeviationStd. Error Mean
X8.00 Laki-laki9150.120910.305161.08027
1.00 Perempuan10954.99088.13372.77907
Independent Samples Test
Levene's Test for Equality of Variancest-test for Equality of Means
FSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference
LowerUpper
X8Equal variances assumed11.130.001-3.7341980-4.869951.30419-7.4418-2.298
Equal variances not assumed-3.656169.710-4.869951.33189-7.4992-2.241
One sample madian test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** ONE SAMPLE MEDIAN TEST*************************************************
NPTESTS/ONESAMPLE TEST (X8) WILCOXON(TESTVALUE = 50).
Binomial test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** BINOMIAL TEST*************************************************
NPAR TESTS /BINOMIAL (.5) = X2.
Binomial Test
CategoryNObserved Prop.Test Prop.Exact Sig. (2-tailed)
X2Group 1.00 Laki-laki91.46.50.229
Group 21.00 Perempuan109.54
Total2001.00
Chi-squared goodness of fit****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** CHI-SQUARED GOODNESS OF FIT*************************************************
NPAR TEST /CHISQUARE = X3 /EXPECTED = 10 10 10 70.X3 Tempat Kelahiran
Observed NExpected NResidual
1.00 Sumatera2420.04.0
2.00 Kalimantan1120.0-9.0
3.00 Sulawesi-Papua2020.0.0
4.00 Jawa145140.05.0
Total200
Test Statistics
X3
Chi-Square5.029a
df3
Asymp. Sig..170
a. 0 cells (0.0%) have expected frequencies less than 5. The minimum expected cell frequency is 20.0.
Two independent samples t-test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** TWO INDEPENDENT SAMPLES T-TEST*************************************************
T-TEST GROUPS = X2(0 1) /VARIABLES = X8.
Independent Samples Test
Levene's Test for Equality of Variancest-test for Equality of Means
FSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference
LowerUpper
X8Equal variances assumed11.130.001-3.7341980-4.869951.30419-7.4418-2.298
Equal variances not assumed-3.656169.710-4.869951.33189-7.4992-2.241
Group Statistics
X2NMeanStd. DeviationStd. Error Mean
X8.00 Laki-laki9150.120910.305161.08027
1.00 Perempuan10954.99088.13372.77907
Wilcoxon-Mann-Whitney test
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** WILCOXON-MANN-WHITNEY TEST*************************************************
NPAR TEST /M-W = X8 BY X2(0 1).
Ranks
X2NMean RankSum of Ranks
X8.00 Laki-laki9185.637792.00
1.00 Perempuan109112.9212308.00
Total200
Test Statisticsa
X8
Mann-Whitney U3606.000
Wilcoxon W7792.000
Z-3.329
Asymp. Sig. (2-tailed).001
a. Grouping Variable: X2
Chi-squared test
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** CHI-SQUARE TEST*************************************************
CROSSTABS /TABLES = X5 BY X2 /STATISTIC = CHISQ.
CROSSTABS /TABLES = X2 BY X4 /STATISTIC = CHISQ.
Case Processing Summary
Cases
ValidMissingTotal
NPercentNPercentNPercent
X5 * X2200100.0%00.0%200100.0%
X5 Jenis Universitas * X2 Jenis Kelamin Crosstabulation
Count
X2Total
.00 Laki-laki1.00 Perempuan
X51.00 Negeri7791168
2.00 Swasta141832
Total91109200
Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)Exact Sig. (1-sided)
Pearson Chi-Square.047a1.828
Continuity Correctionb.0011.981
Likelihood Ratio.0471.828
Fisher's Exact Test.849.492
Linear-by-Linear Association.0471.829
N of Valid Cases200
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 14.56.
b. Computed only for a 2x2 table
Case Processing Summary
Cases
ValidMissingTotal
NPercentNPercentNPercent
X2 * X4200100.0%00.0%200100.0%
X2 Jenis Kelamin * X4 Status Sosial Crosstabulation
Count
X4Total
1.00 Rendah2.00 Menengah3.00 Tinggi
X2.00 Laki-laki15472991
1.00 Perempuan324829109
Total479558200
Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square4.577a2.101
Continuity Correction
Likelihood Ratio4.6792.096
Linear-by-Linear Association3.1101.078
N of Valid Cases200
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 21.39.
One way Anova
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** ONE-WAY ANOVA*************************************************
ONEWAY X8 BY X6.MEANS TABLES = X8 BY X6.
ANOVA
X8
Sum of SquaresdfMean SquareFSig.
Between Groups3175.69821587.84921.275.000
Within Groups14703.17719774.635
Total17878.875199
Case Processing Summary
Cases
IncludedExcludedTotal
NPercentNPercentNPercent
X8 * X6200100.0%00.0%200100.0%
Report
X8
X6MeanNStd. Deviation
1.00 Kepegawaian51.3333459.39778
2.00 Pemasaran56.25711057.94334
3.00 Keuangan46.7600509.31875
Total52.77502009.47859
Kruskal Wallis test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** KRUSKAL WALLIS TEST*************************************************
NPAR TESTS /K-W = X8 BY X6 (1,3).
Ranks
X6NMean Rank
X81.00 Kepegawaian4590.64
2.00 Pemasaran105121.56
3.00 Keuangan5065.14
Total200
Test Statisticsa,b
X8
Chi-Square34.045
df2
Asymp. Sig..000
a. Kruskal Wallis Test
b. Grouping Variable: X6
Paired t-test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** PAIRED T-TEST*************************************************
T-TEST PAIRS = X7 WITH X8 (PAIRED).
Paired Samples Statistics
MeanNStd. DeviationStd. Error Mean
Pair 1X752.230020010.25294.72499
X852.77502009.47859.67024
Paired Samples Correlations
NCorrelationSig.
Pair 1X7 & X8200.597.000
Paired Samples Test
Paired DifferencestdfSig. (2-tailed)
MeanStd. DeviationStd. Error Mean95% Confidence Interval of the Difference
LowerUpper
Pair 1X7 - X8-0.5458.886670.62838-1.784140.69414-0.8671990.387
Wilcoxon signed rank sum test****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** WILCOXON SIGNED RANK SUM TEST*************************************************
NPAR TEST /WILCOXON = X8 WITH X7 (PAIRED).
NPAR TEST /SIGN = X7 WITH X8 (PAIRED).
Ranks
NMean RankSum of Ranks
X7 - X8Negative Ranks97a95.479261.00
Positive Ranks88b90.277944.00
Ties15c
Total200
a. X7 < X8
b. X7 > X8
c. X7 = X8
Test Statisticsa
X7 - X8
Z-.903b
Asymp. Sig. (2-tailed).366
a. Wilcoxon Signed Ranks Test
b. Based on positive ranks.
Frequencies
N
X8 - X7Negative Differencesa88
Positive Differencesb97
Tiesc15
Total200
a. X8 < X7
b. X8 > X7
c. X8 = X7
Test Statisticsa
X8 - X7
Z-.588
Asymp. Sig. (2-tailed).556
a. Sign Test
McNemar Test
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** MCNEMAR TEST*************************************************
COMPUTE HIX9 = (X9>60).COMPUTE HIX7 = (X7>60).EXECUTE.
CROSSTABS /TABLES=HIX9 BY HIX7 /STATISTIC=MCNEMAR /CELLS=COUNT.
Case Processing Summary
Cases
ValidMissingTotal
NPercentNPercentNPercent
HIX9 * HIX7200100.0%00.0%200100.0%
HIX9 * HIX7 Crosstabulation
Count
HIX7Total
.001.00
HIX9.0013521156
1.00182644
Total15347200
Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)
McNemar Test.749a
N of Valid Cases200
a. Binomial distribution used.
Friedman test
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** FRIEDMAN TEST*************************************************
NPAR TESTS /FRIEDMAN = X7 X8 X9.
Ranks
Mean Rank
X71.96
X82.04
X92.01
Test Statisticsa
N200
Chi-Square.645
df2
Asymp. Sig..724
a. Friedman Test
Analysis of covariance****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** ANALYSIS OF COVARIANCE*************************************************
GLM X8 WITH X7 BY X6.
Between-Subjects Factors
Value LabelN
X61.00Kepegawaian45
2.00Pemasaran105
3.00Keuangan50
Tests of Between-Subjects Effects
Dependent Variable: X8
SourceType III Sum of SquaresdfMean SquareFSig.
Corrected Model7017.681a32339.22742.213.000
Intercept4867.96414867.96487.847.000
X73841.98313841.98369.332.000
X6650.2602325.1305.867.003
Error10861.19419655.414
Total574919.000200
Corrected Total17878.875199
a. R Squared = .393 (Adjusted R Squared = .383)
Regression Analysis
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** REGRESSION ANALYSIS*************************************************
REGRESSION /STATISTICS COEFF OUTS R ANOVA CI /DEPENDENT X10 /METHOD = ENTER X9 X2 X11 X7.
Variables Entered/Removeda
ModelVariables EnteredVariables RemovedMethod
1X7, X2, X11, X9b.Enter
a. Dependent Variable: X10
b. All requested variables entered.
Model Summary
ModelRR SquareAdjusted R SquareStd. Error of the Estimate
1.699a.489.4797.14817
a. Predictors: (Constant), X7, X2, X11, X9
ANOVAa
ModelSum of SquaresdfMean SquareFSig.
1Regression9543.72142385.93046.695.000b
Residual9963.77919551.096
Total19507.500199
a. Dependent Variable: X10
b. Predictors: (Constant), X7, X2, X11, X9
Coefficientsa
ModelUnstandardized CoefficientsStandardized CoefficientstSig.95.0% Confidence Interval for B
BStd. ErrorBetaLower Bound
1(Constant)12.3253.1943.85906.027
X90.3890.0740.3685.25200.243
X2-2.011.023-0.101-1.9650.051-4.027
X110.050.0620.0540.8010.424-0.073
X70.3350.0730.3474.60700.192
a. Dependent Variable: X10
Simple linear regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** SIMPLE LINEAR REGRESSION*************************************************
REGRESSION VARIABLES = X8 X7 /DEPENDENT = X8 /METHOD = ENTER.
Variables Entered/Removeda
ModelVariables EnteredVariables RemovedMethod
1X7b.Enter
a. Dependent Variable: X8
b. All requested variables entered.
Model Summary
ModelRR SquareAdjusted R SquareStd. Error of the Estimate
1.597a.356.3537.62487
a. Predictors: (Constant), X7
ANOVAa
ModelSum of SquaresdfMean SquareFSig.
1Regression6367.42116367.421109.521.000b
Residual11511.45419858.139
Total17878.875199
a. Dependent Variable: X8
b. Predictors: (Constant), X7
ModelUnstandardized CoefficientsStandardized CoefficientstSig.
BStd. ErrorBeta
1(Constant)23.9592.8068.5390
X70.5520.0530.59710.4650
Multiple regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** MULTIPLE REGRESSION*************************************************
REGRESSION VARIABLE = X8 X2 X7 X9 X10 X11 /DEPENDENT = X8 /METHOD = ENTER.
Variables Entered/Removeda
ModelVariables EnteredVariables RemovedMethod
1X11, X2, X10, X9, X7b.Enter
a. Dependent Variable: X8
b. All requested variables entered.
Model Summary
ModelRR SquareAdjusted R SquareStd. Error of the Estimate
1.776a.602.5916.05897
a. Predictors: (Constant), X11, X2, X10, X9, X7
ANOVAa
ModelSum of SquaresdfMean SquareFSig.
1Regression10756.92452151.38558.603.000b
Residual7121.95119436.711
Total17878.875199
a. Dependent Variable: X8
b. Predictors: (Constant), X11, X2, X10, X9, X7
Coefficientsa
ModelUnstandardized CoefficientsStandardized CoefficientstSig.
BStd. ErrorBeta
1(Constant)6.1392.8082.1860.03
X25.4930.8750.2896.2740
X70.1250.0650.1361.9310.055
X90.2380.0670.2353.5470
X100.2420.0610.2533.9860
X110.2290.0530.264.3390
a. Dependent Variable: X8
Multivariate multiple regression ****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** MULTIVARIATE MULTIPLE REGRESSION*************************************************
GLM X8 X7 WITH X2 X9 X10 X11.
Multivariate Testsa
EffectValueFHypothesis dfError dfSig.
InterceptPillai's Trace0.033.019b21940.051
Wilks' Lambda0.973.019b21940.051
Hotelling's Trace0.0313.019b21940.051
Roy's Largest Root0.0313.019b21940.051
X2Pillai's Trace0.1719.851b21940
Wilks' Lambda0.8319.851b21940
Hotelling's Trace0.20519.851b21940
Roy's Largest Root0.20519.851b21940
X9Pillai's Trace0.1618.467b21940
Wilks' Lambda0.8418.467b21940
Hotelling's Trace0.1918.467b21940
Roy's Largest Root0.1918.467b21940
X10Pillai's Trace0.16619.366b21940
Wilks' Lambda0.83419.366b21940
Hotelling's Trace0.219.366b21940
Roy's Largest Root0.219.366b21940
X11Pillai's Trace0.22127.466b21940
Wilks' Lambda0.77927.466b21940
Hotelling's Trace0.28327.466b21940
Roy's Largest Root0.28327.466b21940
a. Design: Intercept + X2 + X9 + X10 + X11
b. Exact statistic
Tests of Between-Subjects Effects
SourceDependent VariableType III Sum of SquaresdfMean SquareFSig.
Corrected ModelX810620.092a42655.02371.3250
X712219.658b43054.91568.4740
InterceptX8202.1171202.1175.430.021
X755.107155.1071.2350.268
X2X81413.52811413.52837.9730
X712.605112.6050.2830.596
X9X8714.8671714.86719.2040
X71025.67311025.67322.990
X10X8857.8821857.88223.0460
X7946.9551946.95521.2250
X11X81105.65311105.65329.7020
X71475.8111475.8133.0790
ErrorX87258.78319537.225
X78699.76219544.614
TotalX8574919200
X7566514200
Corrected TotalX817878.875199
X720919.42199
a. R Squared = .594 (Adjusted R Squared = .586)
b. R Squared = .584 (Adjusted R Squared = .576)
Simple logistic regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** SIMPLE LOGISTIC REGRESSION*************************************************
LOGISTIC REGRESSION X2 WITH X7.
Case Processing Summary
Unweighted CasesaNPercent
Selected CasesIncluded in Analysis200100.0
Missing Cases0.0
Total200100.0
Unselected Cases0.0
Total200100.0
a. If weight is in effect, see classification table for the total number of cases.
Dependent Variable Encoding
Original ValueInternal Value
.00 Laki-laki0
1.00 Perempuan1
Block 0: Beginning Block
Classification Tablea,b
ObservedPredicted
X2Percentage Correct
.00 Laki-laki1.00 Perempuan
Step 0X2.00 Laki-laki091.0
1.00 Perempuan0109100.0
Overall Percentage54.5
a. Constant is included in the model.
b. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 0Constant0.180.1421.61610.2041.198
Variables not in the Equation
ScoredfSig.
Step 0VariablesX7.5641.453
Overall Statistics.5641.453
Block 1: Method = Enter
Omnibus Tests of Model Coefficients
Chi-squaredfSig.
Step 1Step.5641.453
Block.5641.453
Model.5641.453
Model Summary
Step-2 Log likelihoodCox & Snell R SquareNagelkerke R Square
1275.073a.003.004
a. Estimation terminated at iteration number 3 because parameter estimates changed by less than .001.
Classification Tablea
ObservedPredicted
X2Percentage Correct
.00 Laki-laki1.00 Perempuan
Step 1X2.00 Laki-laki4874.4
1.00 Perempuan510495.4
Overall Percentage54.0
a. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 1aX7-0.010.0140.56210.4530.99
Constant0.7260.7420.95810.3282.067
a. Variable(s) entered on step 1: X7.
Logistic regression
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** LOGISTIC REGRESSION*************************************************
COMPUTE HONCOMP = (X8 GE 60).EXE.
LOGISTIC REGRESSION HONCOMP WITH X7 X10 X4/CATEGORICAL X4.
Case Processing Summary
Unweighted CasesaNPercent
Selected CasesIncluded in Analysis200100.0
Missing Cases0.0
Total200100.0
Unselected Cases0.0
Total200100.0
a. If weight is in effect, see classification table for the total number of cases.
Dependent Variable Encoding
Original ValueInternal Value
.000
1.001
Categorical Variables Codingsa
FrequencyParameter coding
(1)(2)
X41.00 Rendah471.000.000
2.00 Menengah95.0001.000
3.00 Tinggi58.000.000
a. This coding results in indicator coefficients.
Block 0: Beginning BlockClassification Tablea,b
ObservedPredicted
HONCOMPPercentage Correct
.001.00
Step 0HONCOMP.001470100.0
1.00530.0
Overall Percentage73.5
a. Constant is included in the model.
b. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 0Constant-1.020.1640.54100.361
Variables not in the Equation
ScoredfSig.
Step 0VariablesX747.9061.000
X1034.8621.000
X414.7832.001
X4(1).3021.582
X4(2)8.6661.003
Overall Statistics58.6444.000
Block 1: Method = Enter
Omnibus Tests of Model Coefficients
Chi-squaredfSig.
Step 1Step65.5884.000
Block65.5884.000
Model65.5884.000
Model Summary
Step-2 Log likelihoodCox & Snell R SquareNagelkerke R Square
1165.701a.280.408
a. Estimation terminated at iteration number 6 because parameter estimates changed by less than .001.
Classification Tablea
ObservedPredicted
HONCOMPPercentage Correct
.001.00
Step 1HONCOMP.001321589.8
1.00262750.9
Overall Percentage79.5
a. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 1aX70.0980.02515.199101.103
X100.0660.0275.86710.0151.068
X46.6920.035
X4(1)0.0580.5320.01210.9131.06
X4(2)-1.0130.4445.21210.0220.363
Constant-9.5611.66233.112100
a. Variable(s) entered on step 1: X7, X10, X4.
Multiple logistic regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
***************************************************** MULTIPLE LOGISTIC REGRESSION*************************************************
LOGISTIC REGRESSION X2 WITH X7 X8.
Case Processing Summary
Unweighted CasesaNPercent
Selected CasesIncluded in Analysis200100.0
Missing Cases0.0
Total200100.0
Unselected Cases0.0
Total200100.0
a. If weight is in effect, see classification table for the total number of cases.
Dependent Variable Encoding
Original ValueInternal Value
.00 Laki-laki0
1.00 Perempuan1
Block 0: Beginning BlockClassification Tablea,b
ObservedPredicted
X2Percentage Correct
.00 Laki-laki1.00 Perempuan
Step 0X2.00 Laki-laki091.0
1.00 Perempuan0109100.0
Overall Percentage54.5
a. Constant is included in the model.
b. The cut value is .500
Variables in the EquationBS.E.WalddfSig.Exp(B)
Step 0Constant0.180.1421.61610.2041.198
Variables not in the Equation
ScoredfSig.
Step 0VariablesX7.5641.453
X813.1581.000
Overall Statistics26.3592.000
Block 1: Method = EnterOmnibus Tests of Model Coefficients
Chi-squaredfSig.
Step 1Step27.8192.000
Block27.8192.000
Model27.8192.000
Model Summary
Step-2 Log likelihoodCox & Snell R SquareNagelkerke R Square
1247.818a.130.174
a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.
Classification Tablea
ObservedPredicted
X2Percentage Correct
.00 Laki-laki1.00 Perempuan
Step 1X2.00 Laki-laki543759.3
1.00 Perempuan307972.5
Overall Percentage66.5
a. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 1aX7-0.0710.0213.125100.931
X80.1060.02223.075101.112
Constant-1.7060.9233.41410.0650.182
a. Variable(s) entered on step 1: X7, X8.
Crosstabs dan logistic regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** CROSSTABS DAN LOGISTIC REGRESSION*************************************************
CROSSTABS X2 BY HONCOM /STATISTICS RISK.
LOGISTIC REGRESSION HONCOM WITH X2 /PRINT = CI(95).
Case Processing Summary
Cases
ValidMissingTotal
NPercentNPercentNPercent
X2 * honcom200100.0%00.0%200100.0%
X2 Jenis Kelamin * honcom Crosstabulation
Count
honcomTotal
.001.00
X2.00 Laki-laki731891
1.00 Perempuan7435109
Total14753200
Risk Estimate
Value95% Confidence Interval
LowerUpper
Odds Ratio for X2 (.00 Laki-laki / 1.00 Perempuan)1.918.9973.689
For cohort honcom = .001.1821.0021.393
For cohort honcom = 1.00.616.3751.011
N of Valid Cases200
Case Processing Summary
Unweighted CasesaNPercent
Selected CasesIncluded in Analysis200100.0
Missing Cases0.0
Total200100.0
Unselected Cases0.0
Total200100.0
a. If weight is in effect, see classification table for the total number of cases.
Dependent Variable Encoding
Original ValueInternal Value
.000
1.001
Block 0: Beginning Block
Classification Tablea,b
ObservedPredicted
honcomPercentage Correct
.001.00
Step 0honcom.001470100.0
1.00530.0
Overall Percentage73.5
a. Constant is included in the model.
b. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 0Constant-1.020.1640.54100.361
Variables not in the Equation
ScoredfSig.
Step 0VariablesX23.8711.049
Overall Statistics3.8711.049
Block 1: Method = Enter
Omnibus Tests of Model Coefficients
Chi-squaredfSig.
Step 1Step3.9351.047
Block3.9351.047
Model3.9351.047
Model Summary
Step-2 Log likelihoodCox & Snell R SquareNagelkerke R Square
1227.354a.019.028
a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.
Classification Tablea
ObservedPredicted
honcomPercentage Correct
.001.00
Step 1honcom.001470100.0
1.00530.0
Overall Percentage73.5
a. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 1aX20.6510.3343.81110.0511.918
Constant-1.40.26328.305100.247
Ordered logistic regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** ORDERED LOGISTIC REGRESSION*************************************************
IF X8 GE 30 AND X8 LE 48 X83 = 1.IF X8 GE 49 AND X8 LE 57 X83 = 2.IF X8 GE 58 AND X8 LE 70 X83 = 3.EXECUTE.
PLUM X83 WITH X2 X7 X11/LINK = LOGIT/PRINT = PARAMETER SUMMARY TPARALLEL.
PLUM X4 WITH X2 X10 X11/LINK = LOGIT/PRINT = PARAMETER SUMMARY TPARALLEL.
Case Processing Summary
NMarginal Percentage
X831.006130.5%
2.006130.5%
3.007839.0%
Valid200100.0%
Missing0
Total200
Model Fitting Information
Model-2 Log LikelihoodChi-SquaredfSig.
Intercept Only376.226
Final252.151124.0753.000
Link function: Logit.
Pseudo R-Square
Cox and Snell.462
Nagelkerke.521
McFadden.284
Link function: Logit.
Parameter Estimates
EstimateStd. ErrorWalddfSig.95% Confidence Interval
Lower Bound
Threshold[X83 = 1.00]9.7041.20365.109107.347
[X83 = 2.00]11.81.31280.868109.228
LocationX21.2850.32215.887100.653
X70.1180.02229.867100.076
X110.080.01917.781100.043
Link function: Logit.
Test of Parallel Linesa
Model-2 Log LikelihoodChi-SquaredfSig.
Null Hypothesis252.151
General250.1042.0473.563
The null hypothesis states that the location parameters (slope coefficients) are the same across response categories.
a. Link function: Logit.
Case Processing Summary
NMarginal Percentage
X41.00 Rendah4723.5%
2.00 Menengah9547.5%
3.00 Tinggi5829.0%
Valid200100.0%
Missing0
Total200
Model Fitting Information
Model-2 Log LikelihoodChi-SquaredfSig.
Intercept Only365.736
Final334.17631.5603.000
Link function: Logit.
Pseudo R-Square
Cox and Snell.146
Nagelkerke.166
McFadden.075
Link function: Logit.
Parameter Estimates
EstimateStd. ErrorWalddfSig.95% Confidence Interval
Lower Bound
Threshold[X4 = 1.00]2.7550.86110.24310.0011.068
[X4 = 2.00]5.1050.92330.623103.297
LocationX2-0.4820.279310.083-1.028
X100.030.0163.58410.058-0.001
X110.0530.01512.777100.024
Link function: Logit.
Test of Parallel Linesa
Model-2 Log LikelihoodChi-SquaredfSig.
Null Hypothesis334.176
General331.9872.1893.534
The null hypothesis states that the location parameters (slope coefficients) are the same across response categories.
a. Link function: Logit.
Factorial logistic regression****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** FACTORIAL LOGISTIC REGRESSION*************************************************
LOGISTIC REGRESSION X2 WITH X6 X5 X6 BY X5 /CONTRAST(X6) = INDICATOR(1).
Case Processing Summary
Unweighted CasesaNPercent
Selected CasesIncluded in Analysis200100.0
Missing Cases0.0
Total200100.0
Unselected Cases0.0
Total200100.0
a. If weight is in effect, see classification table for the total number of cases.
Dependent Variable Encoding
Original ValueInternal Value
.00 Laki-laki0
1.00 Perempuan1
Categorical Variables Codings
FrequencyParameter coding
(1)(2)
X61.00 Kepegawaian45.000.000
2.00 Pemasaran1051.000.000
3.00 Keuangan50.0001.000
Block 0: Beginning Block
Classification Tablea,b
ObservedPredicted
X2Percentage Correct
.00 Laki-laki1.00 Perempuan
Step 0X2.00 Laki-laki091.0
1.00 Perempuan0109100.0
Overall Percentage54.5
a. Constant is included in the model.
b. The cut value is .500
Variables in the Equation
BS.E.WalddfSig.Exp(B)
Step 0Constant0.180.1421.61610.2041.198
Variables not in the Equation
Block 1: Method = Enter
ScoredfSig.
Step 0VariablesX6.0532.974
X6(1).0491.826
X6(2).0071.935
X5.0471.828
X6 * X5.0312.985
X6(1) by X5.0041.950
X6(2) by X5.0111.917
Overall Statistics2.9235.712
Omnibus Tests of Model Coefficients
Chi-squaredfSig.
Step 1Step3.1475.677
Block3.1475.677
Model3.1475.677
Model Summary
Step-2 Log likelihoodCox & Snell R SquareNagelkerke R Square
1272.490a.016.021
a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.
Classification Tablea
ObservedPredicted
X2Percentage Correct
.00 Laki-laki1.00 Perempuan
Step 1X2.00 Laki-laki325935.2
1.00 Perempuan317871.6
Overall Percentage55.0
a. The cut value is .500
Variables in the Equation
BS.E.Walddf
Step 1aX62.5952
X6(1)2.2591.4072.5781
X6(2)2.0461.9871.0611
X51.6611.1412.1171
X6 * X52.4742
X6(1) by X5-1.9341.2332.4611
X6(2) by X5-1.8281.840.9861
Constant-1.7121.2691.821
a. Variable(s) entered on step 1: X6, X5, X6 * X5 .
Factor analysis****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** FACTOR ANALYSIS*************************************************
FACTOR /VARIABLES X7 X8 X9 X10 X11 /CRITERIA FACTORS(2) /EXTRACTION PC /ROTATION VARIMAX /PLOT EIGEN.
Communalities
InitialExtraction
X71.000.736
X81.000.704
X91.000.750
X101.000.849
X111.000.900
Extraction Method: Principal Component Analysis.
Total Variance Explained
ComponentInitial EigenvaluesExtraction Sums of Squared Loadings
Total% of VarianceCumulative %Total% of Variance
13.38167.61667.6163.38167.616
20.55711.14878.7640.55711.148
30.4078.13686.9
40.3567.12394.023
50.2995.977100
Extraction Method: Principal Component Analysis.
Component Matrixa
Component
12
X7.858-.020
X8.824.155
X9.844-.195
X10.801-.456
X11.783.536
Extraction Method: Principal Component Analysis.
a. 2 components extracted.
Rotated Component Matrixa
Component
12
X7.650.559
X8.508.667
X9.757.421
X10.900.198
X11.222.922
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
Component Transformation Matrix
Component12
1.742.670
2-.670.742
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Factor Analysis
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** FACTOR ANALYSIS*************************************************
FACTOR /VARIABLES X8 X7 X9 X10 X11 /PRINT INITIAL DET KMO REPR EXTRACTION ROTATION FSCORE UNIVARATIATE /FORMAT BLANK(.30) /PLOT EIGEN ROTATION /CRITERIA FACTORS(3) /EXTRACTION PAF /ROTATION VARIMAX /METHOD = CORRELATION.
Descriptive Statistics
MeanStd. DeviationAnalysis N
X852.77509.47859200
X752.230010.25294200
X952.64509.36845200
X1051.85009.90089200
X1152.405010.73579200
Correlation Matrixa
a. Determinant = .082
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy..861
Bartlett's Test of SphericityApprox. Chi-Square492.437
df10
Sig..000
Communalities
InitialExtraction
X8.521.687
X7.589.765
X9.560.646
X10.500.639
X11.477.649
Extraction Method: Principal Axis Factoring.
Total Variance Explained
FactorInitial EigenvaluesExtraction Sums of Squared Loadings
Total% of VarianceCumulative %Total% of Variance
13.38167.61667.6163.06161.211
20.55711.14878.7640.2054.09
30.4078.13686.90.1212.427
40.3567.12394.023
50.2995.977100
Extraction Method: Principal Axis Factoring.
Factor Matrixa
Factor
123
X8.786
X7.839
X9.794
X10.752
X11.737.318
Extraction Method: Principal Axis Factoring.
a. 3 factors extracted. 14 iterations required.
Reproduced Correlations
X8X7X9X10X11
Reproduced CorrelationX8.687a.597.617.570.604
X7.597.765a.662.629.621
X9.617.662.646a.631.545
X10.570.629.631.639a.466
X11.604.621.545.466.649a
ResidualbX8-.001-2.661E-005.001.001
X7-.001-2.050E-006.001.001
X9-2.661E-005-2.050E-006.000.000
X10.001.001.000-.001
X11.001.001.000-.001
Extraction Method: Principal Axis Factoring.
a. Reproduced communalities
b. Residuals are computed between observed and reproduced correlations. There are 0 (0.0%) nonredundant residuals with absolute values greater than 0.05.
Rotated Factor Matrixa
Factor
123
X8.487.646
X7.538.354.592
X9.624.397.315
X10.704
X11.619.450
Extraction Method: Principal Axis Factoring. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 13 iterations.
Factor Transformation Matrix
Factor123
1.668.583.462
2-.710.685.162
3.222.437-.872
Extraction Method: Principal Axis Factoring. Rotation Method: Varimax with Kaiser Normalization.
Factor Score Coefficient Matrix
Factor
123
X8.110.546-.323
X7.138-.178.705
X9.318.021-.034
X10.494-.146-.110
X11-.303.455.276
Extraction Method: Principal Axis Factoring. Rotation Method: Varimax with Kaiser Normalization.
Factor Score Covariance Matrix
Factor123
1.598.196.193
2.196.540.168
3.193.168.444
Extraction Method: Principal Axis Factoring. Rotation Method: Varimax with Kaiser Normalization.
Factorial Anova****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** FACTORIAL ANOVA*************************************************
GLM X8 BY X2 X4.
Between-Subjects Factors
Value LabelN
X2.00Laki-laki91
1.00Perempuan109
X41.00Rendah47
2.00Menengah95
3.00Tinggi58
Tests of Between-Subjects Effects
Dependent Variable: X8
SourceType III Sum of SquaresdfMean SquareFSig.
Corrected Model2278.244a5455.6495.666.000
Intercept473967.4671473967.4675893.972.000
X21334.49311334.49316.595.000
X41063.2532531.6266.611.002
X2 * X421.431210.715.133.875
Error15600.63119480.416
Total574919.000200
Corrected Total17878.875199
a. R Squared = .127 (Adjusted R Squared = .105)
Discriminant analysis
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** DISCRIMINANT ANALYSIS*************************************************
DISCRIMINATE GROUPS = X6(1, 3) /VARIABLES = X7 X8 X9.
Analysis Case Processing Summary
Unweighted CasesNPercent
Valid200100.0
ExcludedMissing or out-of-range group codes0.0
At least one missing discriminating variable0.0
Both missing or out-of-range group codes and at least one missing discriminating variable0.0
Total0.0
Total200100.0
Group Statistics
X6Valid N (listwise)
UnweightedWeighted
1.00 KepegawaianX74545.000
X84545.000
X94545.000
2.00 PemasaranX7105105.000
X8105105.000
X9105105.000
3.00 KeuanganX75050.000
X85050.000
X95050.000
TotalX7200200.000
X8200200.000
X9200200.000
Eigenvalues
FunctionEigenvalue% of VarianceCumulative %Canonical Correlation
1.356a98.798.7.513
2.005a1.3100.0.067
a. First 2 canonical discriminant functions were used in the analysis.
Wilks' Lambda
Test of Function(s)Wilks' LambdaChi-squaredfSig.
1 through 2.73460.6196.000
2.995.8882.641
Standardized Canonical Discriminant Function Coefficients
Function
12
X7.273-.410
X8.3311.183
X9.582-.656
Structure Matrix
Function
12
X9.913*-.272
X7.778*-.184
X8.775*.630
Pooled within-groups correlations between discriminating variables and standardized canonical discriminant functions Variables ordered by absolute size of correlation within function.
*. Largest absolute correlation between each variable and any discriminant function
Functions at Group Centroids
X6Function
12
1.00 Kepegawaian-.312.119
2.00 Pemasaran.536-.020
3.00 Keuangan-.844-.066
Unstandardized canonical discriminant functions evaluated at group means
One way manova****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** ONE WAY MANOVA*************************************************
GLM X7 X8 X9 BY X6.
Between-Subjects Factors
Value LabelN
X61.00Kepegawaian45
2.00Pemasaran105
3.00Keuangan50
Multivariate Testsa
EffectValueFHypothesis dfError dfSig.
InterceptPillai's Trace.9782883.051b3.000195.000.000
Wilks' Lambda.0222883.051b3.000195.000.000
Hotelling's Trace44.3552883.051b3.000195.000.000
Roy's Largest Root44.3552883.051b3.000195.000.000
X6Pillai's Trace.26710.0756.000392.000.000
Wilks' Lambda.73410.870b6.000390.000.000
Hotelling's Trace.36111.6676.000388.000.000
Roy's Largest Root.35623.277c3.000196.000.000
a. Design: Intercept + X6
b. Exact statistic
c. The statistic is an upper bound on F that yields a lower bound on the significance level.
Tests of Between-Subjects Effects
SourceDependent VariableType III Sum of SquaresdfMean SquareFSig.
Corrected ModelX73716.861a21858.43121.282.000
X83175.698b21587.84921.275.000
X94002.104c22001.05229.279.000
InterceptX7447178.6721447178.6725120.994.000
X8460403.7971460403.7976168.704.000
X9453421.2581453421.2586634.435.000
X6X73716.86121858.43121.282.000
X83175.69821587.84921.275.000
X94002.10422001.05229.279.000
ErrorX717202.55919787.323
X814703.17719774.635
X913463.69119768.344
TotalX7566514.000200
X8574919.000200
X9571765.000200
Corrected TotalX720919.420199
X817878.875199
X917465.795199
a. R Squared = .178 (Adjusted R Squared = .169)
b. R Squared = .178 (Adjusted R Squared = .169)
c. R Squared = .229 (Adjusted R Squared = .221)
Canonical correlation
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** CANONICAL CORRELATION*************************************************
MANOVA X7 X8 WITH X9 X10 /DISCRIM.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -The default error term in MANOVA has been changed from WITHIN CELLS toWITHIN+RESIDUAL. Note that these are the same for all full factorial designs.
* * * * * * * * * * * * * * * * * A n a l y s i s o f V a r i a n c e * * * * * * * * * * * * * * * * *
200 cases accepted. 0 cases rejected because of out-of-range factor values. 0 cases rejected because of missing data. 1 non-empty cell.
1 design will be processed.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
* * * * * * * * * * * * * * * * * A n a l y s i s o f V a r i a n c e -- Design 1 * * * * * * * * * *
EFFECT .. WITHIN CELLS Regression Multivariate Tests of Significance (S = 2, M = -1/2, N = 97 )
Test Name Value Approx. F Hypoth. DF Error DF Sig. of F
Pillais .59783 41.99694 4.00 394.00 .000 Hotellings 1.48369 72.32964 4.00 390.00 .000 Wilks .40249 56.47060 4.00 392.00 .000 Roys .59728 Note.. F statistic for WILKS' Lambda is exact.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - EFFECT .. WITHIN CELLS Regression (Cont.) Univariate F-tests with (2,197) D. F.
Variable Sq. Mul. R Adj. R-sq. Hypoth. MS Error MS F Sig. of F
X7 .51356 .50862 5371.66966 51.65523 103.99081 .000 X8 .43565 .42992 3894.42594 51.21839 76.03569 .000
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Raw canonical coefficients for DEPENDENT variables Function No.
Variable 1
X7 .06326 X8 .04925
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Standardized canonical coefficients for DEPENDENT variables Function No.
Variable 1
X7 .64861 X8 .46681
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Correlations between DEPENDENT and canonical variables Function No.
Variable 1
X7 .92720 X8 .85389
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Variance in dependent variables explained by canonical variables
CAN. VAR. Pct Var DEP Cum Pct DEP Pct Var COV Cum Pct COV
1 79.44115 79.44115 47.44885 47.44885
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Raw canonical coefficients for COVARIATES Function No.
COVARIATE 1
X9 .06698 X10 .04824
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Standardized canonical coefficients for COVARIATES CAN. VAR.
COVARIATE 1
X9 .62752 X10 .47763
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Correlations between COVARIATES and canonical variables CAN. VAR.
Covariate 1
X9 .92878 X10 .87343
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Variance in covariates explained by canonical variables
CAN. VAR. Pct Var DEP Cum Pct DEP Pct Var COV Cum Pct COV
1 48.54417 48.54417 81.27499 81.27499
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Regression analysis for WITHIN CELLS error term --- Individual Univariate .9500 confidence intervals Dependent variable .. X7 Manajemen
COVARIATE B Beta Std. Err. t-Value Sig. of t Lower -95% CL- Upper
X9 .4812890849 .4397697696 .07008 6.86759 .000 .34308 .61949 X10 .3653243123 .3527804936 .06631 5.50914 .000 .23455 .49610 Dependent variable .. X8 Manajemen Produksi
COVARIATE B Beta Std. Err. t-Value Sig. of t Lower -95% CL- Upper
X9 .4328999977 .4278698341 .06978 6.20341 .000 .29528 .57052 X10 .2877496713 .3005699437 .06603 4.35777 .000 .15753 .41797
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
* * * * * * * * * * * * * * * * * A n a l y s i s o f V a r i a n c e -- Design 1 * * * * * * * * * *
EFFECT .. CONSTANT Multivariate Tests of Significance (S = 1, M = 0, N = 97 )
Test Name Value Exact F Hypoth. DF Error DF Sig. of F
Pillais .11544 12.78959 2.00 196.00 .000 Hotellings .13051 12.78959 2.00 196.00 .000 Wilks .88456 12.78959 2.00 196.00 .000 Roys .11544 Note.. F statistics are exact.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - EFFECT .. CONSTANT (Cont.) Univariate F-tests with (1,197) D. F.
Variable Hypoth. SS Error SS Hypoth. MS Error MS F Sig. of F
X7 336.96220 10176.08069 336.96220 51.65523 6.52329 .011 X8 1209.88188 10090.02312 1209.88188 51.21839 23.62202 .000
EFFECT .. CONSTANT (Cont.) Raw discriminant function coefficients Function No.
Variable 1
X7 .04081 X8 .12424
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Standardized discriminant function coefficients Function No.
Variable 1
X7 .29329 X8 .88913
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Estimates of effects for canonical variables Canonical Variable
Parameter 1
1 2.19609
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Correlations between DEPENDENT and canonical variables Canonical Variable
Variable 1
X7 .50372 X8 .95854
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
One way repeated measures anova.
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** ONE-WAY REPEATED MEASURES ANOVA*************************************************
GLM X8 X7 X9 X11 /WSFACTOR A(4).
Within-Subjects Factors
Measure: MEASURE_1
ADependent Variable
1X8
2X7
3X9
4X11
Multivariate Testsa
EffectValueFHypothesis dfError dfSig.
APillai's Trace.005.298b3.000197.000.827
Wilks' Lambda.995.298b3.000197.000.827
Hotelling's Trace.005.298b3.000197.000.827
Roy's Largest Root.005.298b3.000197.000.827
a. Design: Intercept Within Subjects Design: A
b. Exact statistic
Measure: MEASURE_1
Within Subjects EffectMauchly's WApprox. Chi-SquaredfSig.Epsilonb
Greenhouse-GeisserHuynh-FeldtLower-bound
A0.94211.85950.0370.9630.9780.333
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.
a. Design: Intercept
Within Subjects Design: A
b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.
Mauchly's Test of Sphericitya
Tests of Within-Subjects Effects
Measure: MEASURE_1
SourceType III Sum of SquaresdfMean SquareFSig.
ASphericity Assumed35.564311.855.302.824
Greenhouse-Geisser35.5642.88812.313.302.817
Huynh-Feldt35.5642.93512.116.302.820
Lower-bound35.5641.00035.564.302.583
Error(A)Sphericity Assumed23465.18659739.305
Greenhouse-Geisser23465.186574.76040.826
Huynh-Feldt23465.186584.12640.171
Lower-bound23465.186199.000117.916
Tests of Within-Subjects Contrasts
Measure: MEASURE_1
SourceAType III Sum of SquaresdfMean SquareFSig.
ALinear4.83014.830.130.718
Quadratic4.65114.651.106.746
Cubic26.082126.082.709.401
Error(A)Linear7372.02019937.045
Quadratic8771.59919944.078
Cubic7321.56819936.792
Tests of Between-Subjects Effects
Measure: MEASURE_1 Transformed Variable: Average
SourceType III Sum of SquaresdfMean SquareFSig.
Intercept2206155.15112206155.1517876.991.000
Error55735.099199280.076
Nonparametric Correlation****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** NONPARAMETRIC CORRELATION*************************************************
NONPAR CORR /VARIABLES = X7 X8 /PRINT = SPEARMAN.
Correlations
X7X8
Spearman's rhoX7Correlation Coefficient1.000.617
Sig. (2-tailed)..000
N200200
X8Correlation Coefficient.6171.000
Sig. (2-tailed).000.
N200200
Bahasa Sintaksis SPSS GabunganContoh-contoh di atas telah memakai bahasa sintaksis mandiri. Duplikasi perintah:
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
dipakai berulang-ulang. Hal ini akan membutuhkan waktu pemakaian komputer adalah kurang efisien jika dibanding dengan pemakaian sintaksis gabungan. Sintaksis mandiri adalah lebih efektif dan lebih efisien jika dibanding dengan cara point and click. Bahasa sintaksis SPSS gabungan ini adalah sebagai berikut :
****************************************************** ABDULLAH M. JAUBAH*************************************************
GET FILE='D:\AAMUL\CITRA.SAV'.
****************************************************** DESCRIPTIVES*************************************************
DESCRIPTIVES VARIABLES=X8 /STATISTICS=MEAN SUM MIN MAX.
DESCRIPTIVES VARIABLES=X8 /STATISTICS=STDDEV VARIANCE RANGE.
DESCRIPTIVES VARIABLES=X8 /STATISTICS=KURTOSIS SKEWNESS.
DESCRIPTIVES VARIABLES=X7 /STATISTICS=MEAN SUM MIN MAX.
DESCRIPTIVES VARIABLES=X7 /STATISTICS=STDDEV VARIANCE RANGE.
DESCRIPTIVES VARIABLES=X7 /STATISTICS=KURTOSIS SKEWNESS.
DESCRIPTIVES VARIABLES=X8 X7 X9 X10 X11 /STATISTICS=MEAN SUM MIN MAX.
DESCRIPTIVES VARIABLES=X8 X7 X9 X10 X11 /STATISTICS=STDDEV VARIANCE RANGE.
DESCRIPTIVES VARIABLES=X8 X7 X9 X10 X11 /STATISTICS=KURTOSIS SKEWNESS.
****************************************************** EXAMINE*************************************************
EXAMINE X8 /PLOT BOXPLOT STEAMLEAF HISTOGRAM /PERCENTILES(5,10,25,50,75,90,95,99).
****************************************************** CORRELATION*************************************************
CORRELATIONS /VARIABLES = X7 X8 X9 X10 X2 /PRINT = NOSIG.
GRAPH /SCATTERPLOT(BIVAR) = X8 WITH X7.
CORRELATIONS /VARIABLES = X7 X8 X9 X10 X2 /PRINT = NOSIG /MISSING = LISTWISE.
****************************************************** T-TEST*************************************************
T-TEST /TESTVAL=50 /MISSING=ANALYSIS /VARIABLES=X8 /CRITERIA=CI(.95).
****************************************************** PAIERD TEST *************************************************
T-TEST PAIRS=X8 WITH X7 (PAIRED).
****************************************************** INDEPENDENT GROUP TEST*************************************************
T-TEST GROUPS=X2(0 1)/VARIABLES=X8.
****************************************************** ONE SAMPLE MEDIAN TEST*************************************************
NPTESTS/ONESAMPLE TEST (X8) WILCOXON(TESTVALUE = 50).
****************************************************** BINOMIAL TEST*************************************************
NPAR TESTS /BINOMIAL (.5) = X2.
****************************************************** CHI-SQUARED GOODNESS OF FIT*************************************************
NPAR TEST /CHISQUARE = X3 /EXPECTED = 10 10 10 70.
****************************************************** TWO INDEPENDENT SAMPLES T-TEST *************************************************
T-TEST GROUPS = X2(0 1) /VARIABLES = X8.
****************************************************** WILCOXON-MANN-WHITNEY TEST*************************************************
NPAR TEST /M-W = X8 BY X2(0 1).
****************************************************** CHI-SQUARE TEST*************************************************
CROSSTABS /TABLES = X5 BY X2 /STATISTIC = CHISQ.
CROSSTABS /TABLES = X2 BY X4 /STATISTIC = CHISQ.
****************************************************** ONE-WAY ANOVA*************************************************
ONEWAY X8 BY X6.
MEANS TABLES = X8 BY X6.
****************************************************** KRUSKAL WALLIS TEST*************************************************
NPAR TESTS /K-W = X8 BY X6 (1,3).
****************************************************** PAIRED T-TEST*************************************************
T-TEST PAIRS = X7 WITH X8 (PAIRED).
****************************************************** WILCOXON SIGNED RANK SUM TEST *************************************************
NPAR TEST /WILCOXON = X8 WITH X7 (PAIRED).
NPAR TEST /SIGN = X7 WITH X8 (PAIRED).
****************************************************** MCNEMAR TEST*************************************************
COMPUTE HIX9 = (X9>60).COMPUTE HIX7 = (X7>60).EXECUTE.
CROSSTABS /TABLES=HIX9 BY HIX7 /STATISTIC=MCNEMAR /CELLS=COUNT.
****************************************************** FRIEDMAN TEST*************************************************
NPAR TESTS /FRIEDMAN = X7 X8 X9.
****************************************************** ANALYSIS OF COVARIANCE*************************************************
GLM X8 WITH X7 BY X6.
****************************************************** REGRESSION ANALYSIS *************************************************
REGRESSION /STATISTICS COEFF OUTS R ANOVA CI /DEPENDENT X10 /METHOD = ENTER X9 X2 X11 X7.
****************************************************** SIMPLE LINEAR REGRESSION*************************************************
REGRESSION VARIABLES = X8 X7 /DEPENDENT = X8 /METHOD = ENTER.
****************************************************** MULTIPLE REGRESSION*************************************************
REGRESSION VARIABLE = X8 X2 X7 X9 X10 X11 /DEPENDENT = X8 /METHOD = ENTER.
****************************************************** MULTIVARIATE MULTIPLE REGRESSION *************************************************
GLM X8 X7 WITH X2 X9 X10 X11.
****************************************************** SIMPLE LOGISTIC REGRESSION*************************************************
LOGISTIC REGRESSION X2 WITH X7.
****************************************************** LOGISTIC REGRESSION *************************************************
COMPUTE HONCOMP = (X8 GE 60).EXE.
LOGISTIC REGRESSION HONCOMP WITH X7 X10 X4/CATEGORICAL X4
****************************************************** ORDERED LOGISTIC REGRESSION*************************************************
IF X8 GE 30 AND X8 LE 48 X83 = 1.IF X8 GE 49 AND X8 LE 57 X83 = 2.IF X8 GE 58 AND X8 LE 70 X83 = 3.EXECUTE.
PLUM X83 WITH X2 X7 X11/LINK = LOGIT/PRINT = PARAMETER SUMMARY TPARALLEL.
PLUM X4 WITH X2 X10 X11 /LINK = LOGIT /PRINT = PARAMETER SUMMARY TPARALLEL.
****************************************************** FACTORIAL LOGISTIC REGRESSION *************************************************
LOGISTIC REGRESSION X2 WITH X6 X5 X6 BY X5 /CONTRAST(X6) = INDICATOR(1).
****************************************************** FACTOR ANALYSIS*************************************************
FACTOR /VARIABLES X7 X8 X9 X10 X11 /CRITERIA FACTORS(2) /EXTRACTION PC /ROTATION VARIMAX /PLOT EIGEN.
****************************************************** FACTOR ANALYSIS*************************************************
FACTOR /VARIABLES X8 X7 X9 X10 X11 /PRINT INITIAL DET KMO REPR EXTRACTION ROTATION FSCORE UNIVARATIATE /FORMAT BLANK(.30) /PLOT EIGEN ROTATION /CRITERIA FACTORS(3) /EXTRACTION PAF /ROTATION VARIMAX /METHOD = CORRELATION.
****************************************************** FACTORIAL ANOVA*************************************************
GLM X8 BY X2 X4.
****************************************************** DISCRIMINANT ANALYSIS*************************************************
DISCRIMINATE GROUPS = X6(1, 3) /VARIABLES = X7 X8 X9.
****************************************************** ONE WAY MANOVA *************************************************
GLM X7 X8 X9 BY X6.
****************************************************** CANONICAL CORRELATION *************************************************
MANOVA X7 X8 WITH X9 X10 /DISCRIM.
****************************************************** ONE-WAY REPEATED MEASURES ANOVA *************************************************
GLM X8 X7 X9 X11 /WSFACTOR A(4).
****************************************************** NONPARAMETRIC CORRELATION************************************************* NONPAR CORR /VARIABLES = X7 X8 /PRINT = SPEARMAN. RangkumanPembahasan ini menekankan pada pemakaian sintaksis SPSS secara mandiri dan secara gabungan. Perbandingan antara cara mandiri dan cara gabungan perlu dilakukan. Bahasa sintaksis SPSS ini mencakup descriptives, explore, correlation, nonparametric correlation, t-test, paired test, independent group test, one sample madian test, binomial test, chi-squared goodness of fit, two independent samples t-test, Wilcoxon-Mann-Whitney test, chi-squared test, one way Anova, Kruskal Wallis test, paired t-test, Wilcoxon signed rank sum test, McNemar Test, Friedman test, simple lienar regression, multiple regression, multivariate multiple regression, analysis of covariance, simple logistic regression, logistic regression, multiple logistic regression, crosstabs dan logistic regression, ordered logistic regression, factorial logistic regression, factor analysis, factor analysis, discriminant analysis, one way manova, canonical correlation, dan one way repeated measures anova. Hasil-hasil pelaksanaan bahasa sintaksis SPSS juga disajikan akan tetapi belum diinterpretasikan. Hal ini mengakibatkan pembahasan tidak hidup. Interpretasi atas hasil-hasil ini akan dilakukan dalam bagian kedua. Langkah ini diambil atas pertimbangan bahwa interpretasi harus dilakukan secara teliti dan hati-hati karena kesalahan interpretasi akan mengakibatkan kesalahan-kesalahan lain jika hasil-hasil interpretasi ini dipakai oleh para pembaca.Arsip data yang dipakai merupakan arsip data hipotetis dan bukan arsip data hasil penelitian sesuai dengan kaidah-kaidah dan prosedur-prosedur penelitian ilmiah. Sintaksis di atas dapat dipakai untuk arsip data lain yang serasi dengan arsip data di atas.
Penulis mengharap kritik dari para pembaca karena kritik adalah penting sebagai bahan yang mungkin dapat dipakai untuk melakukan perbaikan isi tulisan ini.
Daftar KepustakaanJ. Supranto. 2004. Analisis Multivariat : Arti & Interpretasi. Jakarta : Penerbit Rineka Cipta.Nur Iriawan dan Septin Puji Astuti. 2006. Mengolah Data Statistik dengan Mudah Menggunakan Minitab 14. Yogyakarta : Penerbit Andi.Singgih Santoso. 2011. Mastering SPSS Versi 19. Jakarta : Penerbit PT Elex Media Komputindo Kompas Gramedia.-------------------.2002. Buku Latihan SPSS Statistik Multivariat. Jakarta : Penerbit PT Elex Media Komputindo Kelompok Gramedia.------------------.2014. Statistik Multivariat : Konsep dan Aplikasi dengan SPSS Edisi Revisi. Jakarta : Penerbit PT Elex Media Komputindo Kempas Gramedia.http://www.ats.ucla.edu/stat/AnnotatedOutput/http://www.ats.ucla.edu/stat/mult_pkg/whatstat/http://www.ats.ucla.edu/stat/spss/modules/stats.htmhttp://www.ats.ucla.edu/stat/spss/topics/logistic_regression.htmhttp://www.ats.ucla.edu/stat/dae/
Permata Depok Regency, 20 Juni 201526