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the maximum value is 0.9618 which the name of the company is Petronas Gas BHD, whereas the standard deviation value is 0.1851924.
2. Classical Assumption Test
a. The Result of Normality Test
The statistical test that can be used to test whether the residuals are normally distributed non-parametric test statistic Kolmogorov-Smirnov KS
by making hypotheses: H0: the data were normally distributed residuals
Ha: the data not normally distributed residuals. The result is shown in.
Figure 4.3
Source: Secondary Data Output From SPSS 18
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Based on Figure 4.1 it can be seen that the points spread around the diagonal line follow the direction of a diagonal spread. Thus, it can be
stated that the distribution of the data close to normal or have met the assumptions of normality.
If the significance value greater than 0.05 then H0 is accepted and Ha rejected, otherwise if the significance value is less than 0.05 then H0 rejected
and Ha accepted.
Table 4.4 Normality Test by One-Sample Kolmogorov-Smirnov Test
Source: Secondary Data Output From SPSS 18 Based on the results of statistical tests with models such as the
Kolmogorov-Smirnov contained in table can be concluded that the data were normally distributed. It can be seen from the significance value of 0.125 is
greater than 0.05. N
Kolmogorov-Smirnov Z Asymp. Sig. 2-tailed
Unstandardi zed Residual
285 1.177
.125
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b. The Result of Multicollinearity Test
Detection of multicollinearity can be seen, that if the value of Variance Inflation Factor VIF of not more than 10 and the value of tolerance is no less
than 0.1, it can be said to be free of multicollinearity. VIF values and tolerance of other research variables can be seen from the following table.
Table 4.5 Results Multicollinearity Test
Model Collinearity Statistics
Tolerance VIF
1 Constant
BOD .766
1.306 BOI
.752 1.329
MO .871
1.148 IO
.819 1.221
a. Dependent Variable: ROA
Source: Secondary Data Output From SPSS 18 Based on table 4.4 above, it can be concluded this research free of
multicollinearity. All independent variables have VIF values less than 10. In addition, each independent variable have a tolerance value is greater than 0.1.
Thus there is no multicollinearity in this regression model.
c. The Result of Autocorrelation Test
