DETERMINATION OF LEADERSHIP, COMPETENCY AND WORK DISCIPLINE WITH WORK MOTIVATION AS A MEDIATOR VARIABLES TO ORGANIZATIONAL COMMITMENT USING SEM-PLS (EMPLOYEE RESEARCH STUDY IN DEPARTMENT OF HEALTH BINTAN DISTRICT)

Abstrak

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 75. The discussion in this chapter is the result of field studies to obtain data on the answers to the questionnaire which measures the five main variables in this study, namely leadership, competence, work discipline, work motivation and organizational commitment. 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 0.003<0.05, so it can be stated that the effect of X3 on Y is significant. The influence of the X4 variable on Y has a P-Values value of 0.014 <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 0.020<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 0.001 <0.05, so it can be stated that The influence between X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.000 <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 0.000 <0.05, so it can be stated that the effect of X2 on Y is significant.