DETERMINATION OF COMPENSATION, WORK FACILITIES, WORK DISCIPLINE ON WORK MOTIVATION AS A VARIABLES OF WORKING SATISFACTION MEDIATOR USING SEM-PLS IN (EMPLOYEE RESEARCH STUDY OF BP BATAM)

Authors

  • Tommy Arby Rumengan Universitas Batam
  • M. Zainur Universitas Batam
  • Jemmy Rumengan Universitas Batam
  • Khadafi Universitas Batam

Abstract

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. Where from the questionnaires distributed as many as 40. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures five main variables in this study, namely compensation, work facilities, work discipline, work motivation and job satisfaction. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument testing, normality test, hypothesis testing, and discussion of hypothesis test results and Path Analysis Path. This study uses path analysis to examine relationship patterns that reveal the effect of a variable or set of variables on other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To determine the direct and indirect effect between variables, it is seen from the calculation of the path coefficient and to determine the significance.  The influence of the variable X3 on X4 has a P-Values ​​value of 0.007 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values ​​value of 0.011 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of the variable X4 on Y has a P-Values ​​value of 0.002 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values ​​value of 0.007 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of the variable X1 on Y has a P-Values ​​value of 0.009 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values ​​value of 0.021 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values ​​value of 0.012 <0.05, so it can be stated that the effect of X2 on Y is significant.  

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Published

2023-03-03

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