Aisah 1 Mut’mainna 2 , Syafira Larasati Yasram 3
4. Autocorrelation Test
The autocorrelation test aims to test whether in the linear regression model there is a correlation between the confounding errors in period t and the confounding errors in the t-1 (previous) period. A good regression model is one that is free from autocorrelation. In this study using the Durbin-Watson method.
The absence of autocorrelation in the DW test value must meet the requirements du < dw < 4 – du. The test results using durbin watson can be seen in the table below.
Autocorrelation Test Results Summary
modelb
Model R
R Square
Adjusted R Square
std. Error of the Estimate
Durbin- Watson
1 .882a .778 .770 5168062 2014
a. Predictors: (Constant), DER, CR, SIZE b. Dependent Variable: PBV
(source: secondary data processed with SPSS v25, 2023)
From the test results in the table above, the Durbin Watson number is 2.014. Based on the Durbin Watson table, it is known that the upper limit value (du) is 1.7751 and the 4-du value is 2.2249 which fulfills the requirements du <
dw < 4 – du or 1.7751 < 2.014 < 2.2249 so that it can be concluded that the regression model in this study there was no autocorrelation.
HYPOTHESIS TESTING
a. Determination Coefficient Test (R2 Test)
The coefficient of determination test (R2) is used to measure how strong the independent variables explain the dependent variable. The coefficient of determination is between 0 and 1. The value of determination is determined by the Adjusted R-Square value. The Adjusted R-Square values obtained are presented in the following table:
Test Results for the Coefficient of Determination (R2) Summary models
Model R
R Square
Adjusted R Square
std. Error of the Estimate
1 .21
4a
04 6
02 2
10660.80 476 a. Predictors: (Constant), DER, CR
(source: secondary data processed with SPSS v25, 2023)
Based on the table above, it can be seen that the value of R square is 0.046. This means that 4.6% of the independent variables which include the current ratio, debt to equity ratio, are able to explain the dependent variable PBV, while the remaining 95.4% (100% -4.6%) are influenced by factors – other factors outside this research model.
Test Results for the Coefficient of Determination (R2) Moderation Summary models
Model R
R Square
Adjusted R Square
std. Error of the Estimate
1 .877a .769 .758 5306096
a. Predictors: (Constant),CR, CR*SIZE, DER, DER*PBV (source: secondary data processed with SPSS v25, 2023)
Based on the table above it can be seen that the value of the adjusted R square is 0.758. This means that 75.8% of the firm value variable can be explained by the variable current ratio, debt to equity ratio, as well as the interaction between the current ratio and size, the interaction between the debt to equity ratio and size, while the remaining 24.2% (100%-75 .8%) is influenced by other factors outside this research model.
It can be seen from the two tables above that there is an increase in the value of the adjusted R square from the previous 4.6% to 75.8%. This shows that the size variable can moderate the effect of CR, DER on PBV.
b. Simultaneous Significance Test (F Test)
The simultaneous significance test (F test) aims to test whether all the independent variables simultaneously have an influence on the dependent variable. If the significance value is > 0.05 then all independent variables simultaneously do not affect the dependent variable, but if the significance value is <0.05 then all independent variables simultaneously affect the dependent variable. The following are the results of the simultaneous significance test (F test):
Simultaneous Significance Test Results (Test F) ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 111819987 88.667
6 1863666464.7 78
66,19 4
.000b residual 335040427
0.190
119 28154657733
Total 145324030
58.857 125 a. Dependent Variable: PBV
b. Predictors: (Constant), CR, CR*SIZE, DER, DER*SIZE (source: secondary data processed with SPSS v25, 2023)
Based on the table above, it can be seen that the significance value is 0.000 which means it is less than 0.05 so it can be concluded that the model is feasible to use.
Individual Parameter Significant Test (t test)
The t statistical test shows how far the influence of one independent variable individually explains the dependent variable. The test was carried out with a significance level of 0.05 (α=5%). If the significance value of t <0.05 then Ho is rejected and Ha is accepted, which means that the independent variable has a significant effect on the dependent variable and vice versa. The results of the t test can be seen in the table below.
Individual Parameter Significant Test Results (t test)
(source: secondary data processed with SPSS v25, 2023)
Based on the results of the individual parameter significance test (t test) in the table, the multiple linear regression equation is obtained as follows: PBV
= 3,106.577 – 554,607CR – 1,162.845DER +4.715CR*SIZE + 6.736DER*SIZE Based on the regression results in the table above, the following conclusions can be drawn:
1. The constant value α of 3,106.577 indicates that if all the independent variables, namely the current ratio, debt to equity ratio and moderation, have a value of 0, then PBV has a value of 3,016.577.
2. The variable X1, the current ratio (CR) has a coefficient value of -554,607 Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
T Sig.
B std.
Error
Betas
1 (Constant) 3106577 1389.154 2,236 .027
CR -554,607 230,021 -.128 -2,411 .017
DER -1162.845 981,685 -.070 -1,185 .239
CR*SIZE 4,715 .430 .715 10,957 .000
DER*SIZE 6,736 1,492 .394 4,515 .000
a. Dependent Variable:PBV
which means that for every one unit increase in the current ratio, and other variables have a constant value, PBV will decrease by 554,607. The coefficient is negative indicating that there is an opposite relationship between the independent variable and the dependent variable, meaning that the higher the CR value, the PBV will decrease and vice versa. The significance value of the current ratio is 0.017, this shows a significance value of less than 0.05. So in this case the current ratio variable has a significant negative effect on PBV, so it can be concluded that H1 is accepted.
3. Variable X2, the debt to equity ratio (DER) has a coefficient value of - 1,162.845 means that for every one unit increase in debt to equity ratio, and other variables have constant values, so PBV will decrease by 1,162.845. The coefficient is negative indicating that there is an opposite relationship between the independent variable and the dependent variable, meaning that the higher the DER value, the PBV will decrease and vice versa. The significance value of the debt to equity ratio is 0.239, this indicates a significance value greater than 0.05. So in this case the debt to equity ratio variable has no effect on PBV, so it can be concluded that H2 is rejected.
4. The interaction variable X1*Z, the current ratio with size has a regression coefficient value of 4.715, which means that for every one-unit increase in the interaction of the current ratio with size and other variables that have a constant value, PBV will increase by 4.715. The coefficient is positive indicating that there is a direct relationship between the independent variable and the dependent variable, meaning that the higher the CR*SIZE value, the PBV will increase and vice versa. The significant value of the current ratio interaction with size is 0.000, this shows a significance value of less than 0.05. So in this case the size variable moderates the effect of the current ratio on PBV, so that H3 is accepted.
5. The interaction variable X2*Z, the debt to equity ratio with size has a coefficient value of 6.736, which means that for every one-unit increase in the interaction of the debt to equity ratio with size, and other variables have a constant value, PBV will increase by 6.736. The coefficient is positive indicating that there is a direct relationship between the independent variable and the dependent variable, meaning that the higher the DER*SIZE value, the PBV will increase and vice versa. The significance value of the interaction of the debt to equity ratio with a size of 0.000 indicates a significance value of less than 0.05. So in this case the size variable moderates the effect of the debt to equity ratio on PBV, so that H4 is accepted.
DISCUSSION