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heteroscedasticity. Conversely, if there is no clear pattern as well as points that spread then there is no heteroscedasticity.
3. Hypotesis Testing
a. Test Coefficient of Determination R
2
The coefficient of determination R
2
was essentially measure how far the models ability to explain variation in the dependent variable.
Determination coefficient is between zero and one. Small value of R
2
is the ability of independent variables in explaining the dependent variable is very limited. Value close to one means that the independent
variable gives almost all the information needed to predict the variation in the dependent variable Ghozali, 2013: 97.
Coefficient determination is a statistical measurement of how well the regression line approximates the real data point. By knowing the
value of R
2
, It can determine the magnitude contribution of independent variables toward the dependent variable. R
2
expresses a value between zero and one. If R
2
is near to 0, most of data variations cannot be explained by the regression model. In this case, the
regression model fits the data poorly. On the other hand, if R
2
is near to 1, most of the variation in the dependent variable can be explained
by the regression model. In other words, the regression model fits the data well Sekaran, 2010.
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The closer adjusted R
2
score to 1, the better independent variables explaining dependent variable The hypothesis in this study is
influenced by the value of the corresponding variable coefficient significance after testing. Conclusion the hypothesis made by t-test.
b. Multiple Regression Analysis
Multiple regression analysis is used to test the effect of two or more independent variables toward the dependent variable Ghozali, 2013 :
96 . 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 variables. Multiple regression analysis can be measured partially indicated by
coefficient of partial regression jointly indicated by coefficient of multiple determination or R
2
Indriantoro and Supomo, 2002.
c. Simultaneous Significance Testing F-Test
Essentially, F-test has purpose to know whether among independent variables simultaneously have significant influence
toward dependent variable Ghozali, 2013: 98. Independent variables in this research are good corporate governance indicator and ownership
structure whereas dependent variable is company performance. So, F- test has a function to know the effect of good corporate governance on
company performance. α used for this research is 0.05 5 with assumption:
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1 If sig ≥ 5, ho is accepted.
2 If sig 5, ho is rejected.
d. Partial Significance Test t-Test
Partial Significance Test or t-test basically has purpose to know how far and how much the influence independent variables on
dependent variables Ghozali, 2013:98. In this research, t-test is done to know the effect of good corporate governance as independent
variables on company performance as dependent variable. Assumption used for this test are if the significance value of t more
than α significance value α, then hypothesis is rejected but if on contrary the significance value of t
less than α significance value α, so hypothesis is accepted. Level of significance α use in this research
is 0.05 5.
e. Moderated Regression Analysis MRA
The purpose of this analysis to determine whether the moderating variables will strengthen or weaken the relationship between
independent variables and the dependent variable. Moderated Regression Analysis MRA is a specific application of multiple linear
regression where the regression equation contains elements of interaction multiplication of two or more independent variables.
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E. Definition of Operational Research
Operational variable is a way to set up a concept and how the concept should be measured so that there are variables that can lead to other problems
of a variable depends on the situation and condition of other variables. Operational variables based on the nature of the attributes of the object
observed in the study, can form both qualitative and quantitative researchers made merely for the purpose of research, after understanding the attributes
based on the support of various runway.
1. Independent Variables
The independent variable is the type of variables that explain or influence another variable or variables suspected as the caue of the
dependent variable Indriantoro and Supomo, 2009: 64. The independent variables in this research is earnings management thet proxy by
discretionary accrual using Jones model that modified Dechow et.al Dechow et.al in Herawaty, 2008 with the following step :
a Total Accrual TAC = NIit
– CFOit
Description : NIit = Net income company i on periode t
CFOit = cash flow of operation company i on periode t
