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Normalitas Multikolineritas Heterokedastisitas Autokorelasi

89 LAMPIRAN 4 DATA HASIL PENGOLAHAN SPSS 1. Analisis Statistik Deskriptif a. Deskriptive Descriptive Statistics N Minimum Maximum Mean Std. Deviation LN_DPK 145 21,43 33,95 29,2406 3,37674 LDR 145 8,11 889,26 84,0866 69,08342 CAR 145 3,29 48,00 17,4652 7,33237 NPL 145 ,14 27,90 3,1210 4,02934 ROA 145 -12,90 5,15 1,7486 2,13934 SBI 145 5,80 7,50 6,4600 ,59060 LN_KREDIT 145 21,19 33,79 28,9960 3,42658 Valid N listwise 145 b. Frequence Statistics LN_DPK LDR CAR NPL ROA SBI LN_KREDIT N Valid 145 145 145 145 145 145 145 Missing

2. Pengolahan Data

a. Normalitas

● Histrogram dan grefik Normal P- 90 • Hasil Uji Normalitas K-S Tabel 4.6 Hasil Uji Normalitas K-S One-Sample Kolmogorov-Smirnov Test Unstandardize d Residual N 78 Normal Parameters a,b Mean ,0000000 Std. Deviation 1,12498977 Most Extreme Differences Absolute ,128 Positive ,090 Negative -,128 Kolmogorov-Smirnov Z 1,132 Asymp. Sig. 2-tailed ,154 a. Test distribution is Normal. b. Calculated from data. 91

b. Multikolineritas

Model Collinearity Statistics Tolerance VIF 1 Constant DPK ,609 1,641 LDR ,934 1,071 CAR ,491 2,036 NPL ,495 2,019 ROA ,732 1,366 SBI ,753 1,328 Correlations Correlations Control Variables DPK LDR CAR NPL ROA SBI KRED IT LN_K REDIT DPK Correlation 1,000 -,055 ,024 -,087 ,415 ,385 ,996 Significance 2- tailed . ,637 ,838 ,449 ,000 ,001 ,000 Df 75 75 75 75 75 75 LDR Correlation -,055 1,000 ,136 ,143 ,057 ,037 -,026 Significance 2- tailed ,637 . ,237 ,215 ,622 ,751 ,821 Df 75 75 75 75 75 75 CAR Correlation ,024 ,136 1,000 ,698 -,147 ,026 ,065 Significance 2- tailed ,838 ,237 . ,000 ,202 ,820 ,573 Df 75 75 75 75 75 75 NPL Correlation -,087 ,143 ,698 1,000 -,120 ,055 -,041 Significance 2- tailed ,449 ,215 ,000 . ,298 ,635 ,724 Df 75 75 75 75 75 75 ROA Correlation ,415 ,057 -,147 -,120 1,000 -,064 ,428 Significance 2- tailed ,000 ,622 ,202 ,298 . ,580 ,000 Df 75 75 75 75 75 75 92 SBI Correlation ,385 ,037 ,026 ,055 -,064 1,000 ,415 Significance 2- tailed ,001 ,751 ,820 ,635 ,580 . ,000 Df 75 75 75 75 75 75 KRE DIT Correlation ,996 -,026 ,065 -,041 ,428 ,415 1,000 Significance 2- tailed ,000 ,821 ,573 ,724 ,000 ,000 . Df 75 75 75 75 75 75 a. Dependent Variable : LN_KR

c. Heterokedastisitas

93

d. Autokorelasi

Tabel 4.10 Uji Autokorelasi DW Test Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Durbin- Watson 1 ,983 a ,966 ,964 1790015574 0083,24000 1,827 a. Predictors: Constant, SBI, CAR, ROA, LDR, DPK, NPL b. Dependent Variable: KREDIT • Uji Lagrange Multiplier LM Test • Uji Run Test Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error Beta 1 Constant 28,262 1,882 15,020 ,000 DPK 1,069E-013 ,000 ,577 4,849 ,000 LDR ,028 ,009 ,303 3,156 ,002 CAR -,032 ,026 -,163 -1,227 ,224 NPL ,087 ,056 ,207 1,566 ,122 ROA -,084 ,064 -,144 -1,326 ,189 SBI -,269 ,280 -,103 -,959 ,341 a. Dependent Variable: Unstandardized Residual Coefficients a Model Unstandardized Coefficients Standardized Coefficients T Sig. Std. Error Beta 1 Constant 28,262 1,882 15,020 ,000 DPK 1,069E-013 ,000 ,577 4,849 ,000 LDR ,028 ,009 ,303 3,156 ,002 94

3. Analisis Regresi

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