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Multiple Regression Analysis Simultaneous Hypothesis Testing F Test

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3. Hypothesis Testing

a. Multiple Regression Analysis

The statistical tool used to test the hypothesis of this study is multiple regression test by pooling the data because in the regression analysis, besides measuring the strength of the relationship between two or more variable, also shows the direction of the relationship between the dependent variable and independent variable Ghozali, 2006. The influence of independent variable on the dependent variable was tested at a significance level of 5 and a confidence level of 95. Multiple regression model used in this study: PBV = A0 + A1 DER + A2 DAR + A3 TGB +A4ICR + A5FLM + e Where: DER : Debt to Equity Ratio DAR : Debt to Assets Ratio TGB : Tangibility ICR : Interest Coverage Ratio FLM : Financial Leverage Multiplier L 0-L5 : Estimated Coefficients e : error

b. Simultaneous Hypothesis Testing F Test

Simultaneous Hypothesis Testing or F test was used to assess the goodness of fit regression models tested in this study. A good regression model showed that the independent variables are able to explain or predict the dependent variable when tested simultaneously. The criteria used in the decision making according to Ghozali 2011 are: 1 If F Value F Table, then H : Capital Structure variable DER, DAR, TGB, ICR, FLM has no influence on Firm Value PBV, is rejected 2 If sig 0.05, then H : Capital Structure DER, DAR, TGB, ICR, FLM has no influence on Firm Value PBV, is rejected In the testing the effect of capital structure variable on Firm Value, it is conducted by multiple linear regression analysis partially. Whereas, the independent variables on this research are DER, DAR, TGB, ICR, and FLM and the dependent variable is PBV.The F test result it can be seen from the table above, it can be known that the 7 level of significance in this model is 0.000 0.05 which means there is significant influence simultaneously on the independent variable in the form DER, DAR, TGB, ICR, FLM on the dependent variable is PBV.

c. Coefficient of Determination Adjusted R

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