DETERMINATION OF WORK CHARATERISTICS, LOCUS OF CONTROL, REWARD WITH WORK ACHIEVEMENT AS INTERVENING VARIABLES ON PERFORMANCE WITHUSING SEM-PLS (STUDY EMPLOYEE RESEARCH IN BINTAN DISTRICT HEALTH OFFICE
DOI:
https://doi.org/10.37776/jzm.v11i1.775Kata Kunci:
job characteristics, locus of control, reward, work achievement, performanceAbstrak
      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 41. 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 job characteristics, locus of control, reward, work performance and performance. 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 the results of hypothesis testing and Path Analysis Path. This study uses path analysis to examine patterns of relationships 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 effect of the variable X3 on X4 has a P-Values value of 0.000 <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 0.012 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of variable X4 on Y has a P-Values value of 0.033 <0.05, so it can be stated that the effect between X4 and Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.043 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y has a P-Values value of 0.014 <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 0.021 <0.05, so it can be stated that the effect of X2 on Y is significantReferensi
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