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1 Lampiran 1 : Pengolahan Data ROA Variabel bebas Variabel terikat : VAIC, Ukuran, dan Leverage : ROA EMITEN TAHUN ROA (%) VAIC (%) UKURAN CEKA DLTA INDF MYOR LEVERAGE (Rp) LnROA LnVAIC LnLEVERAGE MLBI LEVERAGE EMITEN TAHUN ROA (%) VAIC (%) UKURAN (Rp) LnROA LnVAIC LnLEVERAGE MLBI SKLT STTP ULTJ GGRM
2 HMSP DVLA LEVERAGE EMITEN TAHUN ROA (%) VAIC (%) UKURAN (Rp) LnROA LnVAIC LnLEVERAGE KAEF MERK PYFA TSPC TCID MRAT UNVR LEVERAGE EMITEN TAHUN ROA (%) VAIC (%) UKURAN (Rp) LnROA LnVAIC LnLEVERAGE UNVR KDSI
3 LMPI
4 Lampiran 2 : Pengolahan Data ATO Variabel bebas Variabel terikat : VAIC, Ukuran, dan Leverage : ATO EMITEN CEKA DLTA INDF MYOR MLBI EMITEN SKLT STTP ULTJ TAHUN ATO ( kali) VAIC (%) UKURAN LEVERAGE (Rp) Wt_VAIC Wt_LEVERAGE Wt_UKURAN Wt_ATO Wt_SQRO ATO LEVERAGE TAHUN (Kali) VAIC (%) UKURAN (Rp) Wt_VAIC Wt_LEVERAGE Wt_UKURAN Wt_ATO Wt_SQRO GGRM
5 HMSP DVLA EMITEN KAEF MERK PYFA TSPC TCID MRAT EMITEN UNVR KDSI ATO LEVERAGE TAHUN (Kali) VAIC (%) UKURAN (Rp) Wt_VAIC Wt_LEVERAGE Wt_UKURAN Wt_ATO Wt_SQRO ATO LEVERAGE TAHUN (Kali) VAIC (%) UKURAN (Rp) Wt_VAIC Wt_LEVERAGE Wt_UKURAN Wt_ATO Wt_SQRO
6 LMPI
7 Lampiran 3 Pengolahan Data MBR Variabel bebas Variabel terikat : VAIC, Ukuran, dan Leverage : MBR TEN TAHUN MBR (%) VAIC (%) UKURAN KA TA DF OR LEVERAGE (Rp) LN_MBR Wt_VAIC Wt_UKURAN Wt_LEVERAGE Wt_LN_MBR BI LEVERAGE TEN TAHUN MBR (%) VAIC (%) UKURAN (Rp) LN_MBR Wt_VAIC Wt_UKURAN Wt_LEVERAGE Wt_LN_MBR BI LT TP TJ RM
8 SP LA LEVERAGE TEN TAHUN MBR (%) VAIC (%) UKURAN (Rp) LN_MBR Wt_VAIC Wt_UKURAN Wt_LEVERAGE Wt_LN_MBR EF RK FA PC ID AT VR LEVERAGE TEN TAHUN MBR (%) VAIC (%) UKURAN (Rp) LN_MBR Wt_VAIC Wt_UKURAN Wt_LEVERAGE Wt_LN_MBR VR SI
9 PI
10 LAMPIRAN 4 HASIL PENGOLAHAN DATA ROA 1. HASIL ROA SEBELUM LN Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson a a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: ROA ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: ROA Coefficients a Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: ROA
11 One-Sample Kolmogorov-Smirnov Test ROA N 80 Normal Parameters a,,b Mean.1254 Std. Deviation Most Extreme Differences Absolute.211 Positive.211 Negative Kolmogorov-Smirnov Z Asymp. Sig. (2-tailed).002 a. Test distribution is Normal. b. Calculated from data.
12 UJI GLEJSER SEBELUM LN Coefficients a Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: ABS_RES HASIL ROA SETELAH LN
13 Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson a a. Predictors: (Constant), Ln_LEVERAGE, Ln_VAIC, UKURAN b. Dependent Variable: Ln_ROA ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), Ln_LEVERAGE, Ln_VAIC, UKURAN b. Dependent Variable: Ln_ROA Coefficients a Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) Ln_VAIC UKURAN Ln_LEVERAGE a. Dependent Variable: Ln_ROA One-Sample Kolmogorov-Smirnov Test Ln_ROA N 80 Normal Parameters a,,b Mean Std. Deviation Most Extreme Differences Absolute.074 Positive.074 Negative Kolmogorov-Smirnov Z.665 Asymp. Sig. (2-tailed).768
14 a. Test distribution is Normal. b. Calculated from data. UJI GLEJSER SETELAH LN
15 Coefficients a Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) Ln_VAIC UKURAN Ln_LEVERAGE a. Dependent Variable: ABS_RES
16 LAMPIRAN 5 HASIL PENGOLAHAN DATA ATO HASIL ATO SEBELUM WEIGHTING (PEMBOBOTAN) Model Summary b Adjusted R Std. Error of the Model R R Square Square Estimate Durbin-Watson a a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: ATO ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: ATO Coefficients a Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: ATO One-Sample Kolmogorov-Smirnov Test
17 ATO N 80 Normal Parameters a,,b Mean Std. Deviation Most Extreme Differences Absolute.083 Positive.083 Negative Kolmogorov-Smirnov Z.743 Asymp. Sig. (2-tailed).639 a. Test distribution is Normal. b. Calculated from data.
18 UJI GLEJSER SEBELUM WEIGHTING (PEMBOBOTAN) Coefficients a Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: ABS_RES HASIL ATO SETELAH WEIGHTING (PEMBOBOTAN) Model Summary c,d Std. Error of the Model R R Square b Adjusted R Square Estimate Durbin-Watson a a. Predictors: Wt_LEVERAGE, Wt_VAIC, Wt_UKURAN, Wt_SQROOT b. For regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept. c. Dependent Variable: Wt_ATO d. Linear Regression through the Origin
19 ANOVA c,d Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total b 80 a. Predictors: Wt_LEVERAGE, Wt_VAIC, Wt_UKURAN, Wt_SQROOT b. This total sum of squares is not corrected for the constant because the constant is zero for regression through the origin. c. Dependent Variable: Wt_ATO d. Linear Regression through the Origin Coefficients a,b Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 Wt_SQROOT Wt_VAIC Wt_UKURAN Wt_LEVERAGE a. Dependent Variable: Wt_ATO b. Linear Regression through the Origin One-Sample Kolmogorov-Smirnov Test Wt_ATO N 80 Normal Parameters a,,b Mean Std. Deviation Most Extreme Differences Absolute.060 Positive.060 Negative Kolmogorov-Smirnov Z.538 Asymp. Sig. (2-tailed).934 a. Test distribution is Normal. b. Calculated from data.
20 UJI GLEJSER SETELAH WEIGHTING (PEMBOBOTAN)
21 Coefficients a,b Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 Wt_SQROOT Wt_VAIC Wt_UKURAN Wt_LEVERAGE a. Dependent Variable: ABS_RES b. Linear Regression through the Origin
22 LAMPIRAN 6 HASIL PENGOLAHAN DATA MBR HASIL MBR SEBELUM LN Model Summary b Adjusted R Std. Error of Model R R Square Square the Estimate Durbin-Watson a a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: MBR ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual 5.118E Total 5.282E7 79 a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: MBR Coefficients a Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: MBR One-Sample Kolmogorov-Smirnov Test MBR
23 N 80 Normal Parameters a,,b Mean Std. Deviation Most Extreme Differences Absolute.290 Positive.266 Negative Kolmogorov-Smirnov Z Asymp. Sig. (2-tailed).000 a. Test distribution is Normal. b. Calculated from data.
24 UJI GLEJSER SEBELUM LN Coefficients a Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: ABS_RES HASIL MBR SETELAH LN Model Summary b Adjusted R Std. Error of Model R R Square Square the Estimate Durbin-Watson a a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: Ln_MBR ANOVA b Sum of Model Squares df Mean Square F Sig. 1 Regression a Residual
25 Total a. Predictors: (Constant), LEVERAGE, VAIC, UKURAN b. Dependent Variable: Ln_MBR Coefficients a Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAGE a. Dependent Variable: Ln_MBR One-Sample Kolmogorov-Smirnov Test Ln_MBR N 76 Normal Parameters a,,b Mean Std. Deviation Most Extreme Differences Absolute.053 Positive.045 Negative Kolmogorov-Smirnov Z.462 Asymp. Sig. (2-tailed).983 a. Test distribution is Normal. b. Calculated from data.
26
27 UJI GLEJSER SETELAH LN Coefficients a Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) VAIC UKURAN LEVERAG E a. Dependent Variable: ABS_RES
28 HASIL LN MBR SETELAH WEIGHTING (PEMBOBOTAN) Model Summary c,d Std. Error of the Model R R Square b Adjusted R Square Estimate Durbin-Watson a a. Predictors: Wt_LEVERAGE, Wt_SQROOT, Wt_UKURAN, Wt_VAIC b. For regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept. c. Dependent Variable: Wt_Ln_MBR d. Linear Regression through the Origin ANOVA c,d Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total b 72 a. Predictors: Wt_LEVERAGE, Wt_SQROOT, Wt_UKURAN, Wt_VAIC b. This total sum of squares is not corrected for the constant because the constant is zero for regression through the origin. c. Dependent Variable: Wt_Ln_MBR d. Linear Regression through the Origin Coefficients a,b Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 Wt_SQROOT Wt_VAIC Wt_UKURAN Wt_LEVERAGE a. Dependent Variable: Wt_Ln_MBR b. Linear Regression through the Origin
29 One-Sample Kolmogorov-Smirnov Test Wt_Ln_MBR N 72 Normal Parameters a,,b Mean Std. Deviation Most Extreme Differences Absolute.062 Positive.062 Negative Kolmogorov-Smirnov Z.524 Asymp. Sig. (2-tailed).947 a. Test distribution is Normal. b. Calculated from data.
30 UJI GLEJSER SETELEH LN MBR DI WEIGHTING Coefficients a,b Standardized Unstandardized Coefficients Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 Wt_SQROOT Wt_VAIC Wt_UKURAN Wt_LEVERAGE a. Dependent Variable: ABS_RES b. Linear Regression through the Origin
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