<![CDATA[In this study, researchers used respondent data, such as gender, age, and length of work of respondents in order to provide information about the characteristics of respondents. Wherefrom the questionnaire distributed were 103 respondents. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, test instruments, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Paths. This research uses the analysis path (path analysis) to test the pattern of relationships that reveal the influence of variables or a set of variables on other variables, both direct and indirect effects. The results of the study are as follows: The influence of variables X3 on X4 has a P-Values value of 0.022 <0.05, so it can be stated that the effect between X3 on X4 is significant. The effect of the variable X3 on Y has a P-Values value of 0,000> 0.05, so it can be stated that the influence between X3 on Y is significant. The effect of the X4 variable on Y has a P-value Values of 0.008> 0.05, so it can be stated that the influence is inter an X4 to Y is significant. The effect of variable X1 to X4 has a P-Values value of 0.006 <0.05, so it can be stated that the influence between X1 to X4 is significant. The effect of the X1 variable on Y has a P-Values value of 0.028> 0,05, so it can be stated that the influence between X1 to Y is significant. The effect of variable X2 on X4 has a P-Values value of 0,000 <0.05, so it can be stated that the influence between X2 on X4 is significant. The effect of variable X2 on Y has P-Values value of 0.013 <0.05, so it can be stated that the influence between X2 on Y is significant. ]]>
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