Analysis and Discussion 1. Validity Test

56 Reliability tests can only be done after the instrument has confirmed its validity ˜ Reliability testing in this study to indicate the level of internal consistency reliability of the techniques used is to measure the coefficient of Cronbach ™ s Alpha with SPSS š›˜ Alpha values range from › œ ž questions can be considered reliable if the alpha value is greater than ›˜ Ÿ›˜ Table 4.7 Reliability Test for Auditor experience Source: Processed primary data by spss 20.0 Reliability test for audit experience variable is shown on table ˜ Ÿ˜ ¡¢ seen as in the table ž £ he Cronbach ¤ s alpha › ž¥ šš means the data are reliable ˜ Table 4.8 Reliability Test for Professional Judgment of Auditor Source: Processed primary data by spss 20.0 Reliability test for Professional ¦ udgment of Auditor variable is shown on table ˜ § ˜ ¡¢ seen as in the table ž £ he Cronbach ¤ s alpha › ž ¥ § means the data are reliable ˜ Reliability Statistics Cronbachs Alpha N of Items .822 2 Reliability Statistics Cronbachs Alpha N of Items .847 9 57 Table 4.9 Reliability Test for Quality of Audit Evidence Collected Source: Processed primary data by spss 20.0 Reliability test for Quality of Audit Evidence Collected variable is shown on table ¨© ª © As seen as in the table « ¬ he Cronbach ­ s alpha ®« ª¯° means the data are reliable ©

3. Classic Assumption Test

a © ± ² ³ mality Test The purpose of the normality testis to determine whether the regression normally distributed or not © A good regression model is to have normal or nearly normal distribution © ´ n this research « to detect whether normally distributed data or not « it can be done with using graph analysis namely histogram graph Normal Probability Plot P-P Plot and statistical analysis namely µ ² ¶ mogorov · Smirnov test © Figure 4.1 Reliability Statistics Cronbachs Alpha N of Items .856 10 58 Normal P-Plot Graph Source: Processed primary data by spss 20.0 Based on figure ¸ ¹º this research has done normality data distribution test ¹ The result acquired from SPSS »¼ statistic software ¹ From the P ½ P Plots diagram above ¾ it can be seen that the plots are distributed along the diagonal line ¹ Thus ¾ it can be concluded that the data used in this research has a normal distribution ¹ ¿ÀÁ  ver ¾ graph analysis can emerge different interpretation among reader ¾ so that statistical analysis test is needed to ensure the interpretation mistake for reading the graph ¹ Table ¸ ¹Ã below will show the result of statistical analysis namely ÄÀÅ mogorov ½ Smirnov test Æ 59 Table 4.10 Kolmogorov-Smirnov Test Source: Processed primary data by spss 20.0 The result of Kolmogorov-Smirnov test on table ÇÈ É Ê lso shows that the value of Kolmogorov-Smirnov Ë ÈÇÉÌ with the level of significant probability Ë ÈÍ Ì Î Ï the value of p Ë È Ë ÐÈ So the residual data is distributed normally È Therefore Ï regression model used in this research has met the normality test assumption È b È Ñ ulticollinearity Test The aim from Ñ ulticolinearity Test is to test whether the regression model found a correlation among the independent variables È A good regression model should there is no correlation among independent variables È Ò n this research Ï to detect the presence or absence of Ñ ulticolinearity can be One-Sample Kolmogorov-Smirnov Test Unstandardize d Residual N 50 Mean 0E-7 Normal Parameters a,b Std. Deviation 4.18400133 Absolute .069 Positive .063 Most Extreme Differences Negative -.069 Kolmogorov-Smirnov Z .487 Asymp. Sig. 2-tailed .972 a. Test distribution is Normal. b. Calculated from data.