80
Negative Autocorrelation Detection:
The results show that it can be concluded for the regression analysis that there is no positive autocorrelation and there are no negative autocorrelation, and
it can be concluded that there is absolutely no autocorrelation.
4.2.3 Multiple Regression Analysis
Multiple regression analysis used to test the effect of two or more independent variables toward the dependent variable. In this research,
Independent variables is Good Corporate Governance components which elaborate into size of Board of Commissioners BOC, size of Independent
Commissioner IC and size of Audit Committee AC, and Dependent Quality Sustainable Report Disclosure which correlate with GRI G3index
Coefficients
a
Model Unstandardized
Coefficients Standardized
Coefficients t
Sig. Collinearity
Statistics B
Std. Error
Beta Tolerance VIF
1 Constant
1.163 .119
9.792 .000 BOC
-.016 .008
-.335 -2.145 .042 .940 1.064
SIC -.484
.180 -.414 -2.685 .012
.964 1.037 AC
.015 .013
.189 1.197 .242 .916 1.092
a. Dependent Variable: SR Source: Processed from secondary data SPSS ver 21.0
The result of multiple regression analysis has been explained in table. The result of multiple regression analysis with using significance 5 obtained the
following equation: 2.080 1.214there is negative autocorrelation incorrect
2.080 1.650there is no negative autocorrelation correct 1.214 2.080 1.650the test does not convince or inconclusive
incorrect
81
Y = 1.
163
-0.016X
1
-0.484X
2
+0.015X
3
+ε
From the multiple linear regression equation above, it can be explained for each variable as follows:
1. Constant at
1.
163 units stated that if there is no influence or change into size
of Board of Commissioners BOC, size of Independent Commissioner IC and size of Audit Committee AC, then the value of firm value will be
1.
163. 2.
Regression coefficient of Board of Commissioners BOC marked negative at -0.016. It shows that the influence of Board of Commissioners BOC on the
quality of Sustainability Report Disclosure is negative, which means that if the value or number of Board of Commissioners BOC is increased by one point,
then GRI index will decrease by -0.016 or on the contrary, with assumption variables X2 and X3, remain or unchanged.
3. Regression coefficient of size of Independent Commissioner IC marked
negative at -0.484. It shows that the influence of size of Independent Commissioner IC on the quality of Sustainability Report Disclosure is
negative, which means that if the value or number of Independent Commissioner IC is increased by one point, then GRI index will increase by
-0.484 or on the contrary, with assumption variables X1 and X3, remain or
unchanged. 4.
Regression coefficient of size of Audit Committee AC marked positive at
0.015
. It shows that the influence of size of Audit Committee AC on the quality of Sustainability Report Disclosure is positive, which means that if the
value or number of Audit Committee AC is increased by one point, then GRI index will increase by
0.015
or on the contrary, with assumption variables X1 and X2, remain or unchanged.
