DETERMINATION OF COMPETENCY , SCHOOL CLIMATE, WORK DISCIPLINE WITH WORK MOTIVATION AS INTERVENING VARIABLES ON TEACHER PERFORMANCE BY USING SEM-PLS (TEACHER RESEARCH STUDY AT VOCATIONAL SCHOOL OF PERTIWI BATAM)

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 30. 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 competence, school climate, work discipline, work motivation and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significance. The influence of the X3 variable on X4 has a P-Values value of 0.029 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence variable X3 on Y with a P-Values value of 0.002 <0.05, so it can be stated that the influence between X3 on Y is significant. The effect of the variable X4 on Y with 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 with a P-Values value of 0.027 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y with a P-Values value of 0.012 <0.05, so it can be stated that the effect of X1 on Y is significant. The influence variable X2 on X4 has a P-Values value of 0.009 <0.05, so it can be stated that the effect between X2 and X4 is significant. The effect of the X2 variable on Y with a P-Values value of 0.017 <0.05, so it can be stated that the effect of X2 on Y is significant