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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.

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