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3.4.3 Multiple Regression Analysis
Multiple regression analysis used to test the effect of two or more independent variables toward the dependent variable Ghozali, 2011. Regression
analysis divided into two kinds, simple regression analysis if there is only one independent variable and multiple regression analysis if there is more than one
independent variable. Multiple regression analysis can be measured partially indicated by coefficient of partial regression jointly indicated by coefficient of
multiple determination or R
2
. Independent variable in this research is Good Corporate Governance
components which elaborate into size of board of commissioners, proportion of independent commissioners and size of audit committee. Besides, dependent
variable is sustainability report which appropriates with GRI G3 Indicators.
Structural equation model that proposed as an empirical model is as
follows:
Y
1
= β + β
1
X
1
+ β
2
X
2
+ β
3
X
3
+ ε
Where
Y1 Sustainability Report
X1
Size of Board of Commissioners
X2 Proportion of Independent Commissioners
X3
Size of Audit Committee
β1
Regression Variable Size of Board of Commissioners
β2
Regression Variable Proportion of Independent Commissioners
β3
Regression Variable Size of Audit Committee
ε
Error
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a. Simultaneous Regression Analysis Test - F
Essentially, F- test has purpose to know whether among independent variables simultaneously have significant influence toward dependent
variable. Independent variables in this research are good corporate governance components structure whereas dependent variable is sustainability report
disclosure. So, F- test has a function to know the influence among good corporate governance components towards the quality of sustainability report
disclosure . α that is used for this research is 0.05 5 with assumption:
1 α 5, Ho is accepted.
2 α 5, Ho is rejected.
b. Partial Regression Testing T-test
The T-Test has the purpose to examine the influences of the independent variables GCG Components to the dependent variables, which
GRI G3 Indicators. The value significant T is compared with the degree of believes.
The level of significance used in this test is 5 or α 0.05 Thus, if the significant T is more than 0,05 so H1, H2 or H3 is rejected. Whereas, if
significant T is less than 0,05 so H1, H2 or H3 is accepted. If H1, H2 and H3 are accepted, this means that there is a significant relationship between
independent variable and dependent variables.
3.4.4 Coefficient Determination Test R
2
Coefficient determination R² can measure how far ability of independent variable GCG Components elaborate dependent variables GRI G3 Indicators.
