Uji Normalitas Uji Heteroskedastisitas Uji Multikolinearitas

Data Hasil Pengolahan SPSS 1. Asumsi Klasik

a. Uji Normalitas

Universitas Sumatera Utara One-Sample Kolmogorov-Smirnov Test Universitas Sumatera Utara

b. Uji Heteroskedastisitas

Unstandardized Residual N 60 Normal Parameters a Mean .0000000 Std. Deviation .11948496 Most Extreme Differences Absolute .121 Positive .121 Negative -.072 Kolmogorov-Smirnov Z .934 Asymp. Sig. 2-tailed .347 a. Test distribution is Normal. One-Sample Kolmogorov-Smirnov Test Unstandardized Residual N 60 Normal Parameters a Mean .0000000 Std. Deviation .26236232 Most Extreme Differences Absolute .095 Positive .073 Negative -.095 Kolmogorov-Smirnov Z .737 Asymp. Sig. 2-tailed .650 a. Test distribution is Normal. Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant .209 .185 1.132 .263 DER -.010 .005 -.289 -1.995 .051 UkuranPerusahaan .000 .005 -.019 -.140 .889 KomisarisIndependen .029 .164 .025 .180 .858 KomiteAudit -.018 .015 -.153 -1.171 .247 kepInsti -.063 .054 -.160 -1.174 .245 a. Dependent Variable: absut_ROA Coefficients a Universitas Sumatera Utara c. Uji Autokorelasi Runs Test Unstandardized Residual Test Value a -.01233 Cases Test Value 30 Cases = Test Value 30 Total Cases 60 Number of Runs 32 Z .260 Asymp. Sig. 2-tailed .795 a. Median

d. Uji Multikolinearitas

Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant .495 .377 1.314 .195 DER .008 .010 .122 .840 .404 UkuranPerusahaan -.006 .011 -.075 -.559 .579 KomisarisIndependen .251 .333 .105 .753 .455 KomiteAudit -.062 .032 -.259 -1.976 .053 kepInsti -.023 .110 -.029 -.214 .832 a. Dependent Variable: absut_ROE Runs Test Unstandardized Residual Test Value a .05465 Cases Test Value 30 Cases = Test Value 30 Total Cases 60 Number of Runs 32 Z .260 Asymp. Sig. 2-tailed .795 a. Median Universitas Sumatera Utara Model Unstandardized Coefficients Standardiz ed Coefficients T Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1 Constant -.643 .280 -2.291 .026 DER -.016 .007 -.289 -2.157 .035 .783 1.277 UkuranPerusahaan .025 .008 .367 2.987 .004 .928 1.077 KomisarisIndependen .163 .248 .084 .657 .514 .850 1.177 KomiteAudit -.027 .023 -.140 -1.162 .250 .966 1.036 kepInsti .101 .082 .156 1.238 .221 .880 1.137 a. Dependent Variable: ROA

2. Analisis Statistik Deskriptif

Coefficients a Model Unstandardized Coefficients Standardized Coefficients T Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1Constant -.996 .616 -1.617 .112 DER -.089 .016 -.644 -5.600 .000 .783 1.277 UkuranPerusahaan .043 .018 .252 2.383 .021 .928 1.077 KomisarisIndependen .092 .545 .019 .170 .866 .850 1.177 KomiteAudit -.023 .052 -.046 -.442 .660 .966 1.036 kepInsti .021 .179 .012 .115 .909 .880 1.137 a. Dependent Variable: ROE Universitas Sumatera Utara Descriptive Statistics N Minimum Maximum Mean Std. Deviation ROA 60 -.223 .583 .07418 .137352 ROE 60 -1.799 .745 .08155 .350951 DER 60 -4.406 17.754 1.54460 2.526997 UkuranPerusahaan 60 23.151 32.105 2.86753E1 2.033464 KomisarisIndependen 60 .220 .500 .36467 .071057 KomiteAudit 60 3 6 3.33 .705 kepInsti 60 .052 .986 .60923 .212284 Valid N listwise 60

3. Analisis Regresi Linear Berganda a. Uji-F

ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression .271 5 .054 3.471 .009 a Residual .842 54 .016 Total 1.113 59 a. Predictors: Constant, kepInsti, KomisarisIndependen, KomiteAudit, UkuranPerusahaan, DER b. Dependent Variable: ROA ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression 3.206 5 .641 8.525 .000 a Residual 4.061 54 .075 Total 7.267 59 a. Predictors: Constant, kepInsti, KomisarisIndependen, KomiteAudit, UkuranPerusahaan, DER b. Dependent Variable: ROE Universitas Sumatera Utara

b. Uji-t