Open AccessDETERMINATION OF COMPETENCE, EDUCATION AND SELF EFFICACY WITH WORK SPIRIT AS A MEDIATOR VARIABLE ON EMPLOYEE PERFORMANCE TAX MANAGEMENT AGENCY AND RETREBUTION FOR THE CITY OF BATAM
Author(s) -
Ayu Rahmasari,
Indrayani Indrayani,
Reny Nozariyanti,
Rajesh Rila,
Muammar Khaddafi
Publication year - 2022
Publication title -
international journal of social science, educational, economics, agriculture research, and technology
Language(s) - English
Resource type - Journals
ISSN - 2827-766X
DOI - 10.54443/ijset.v1i3.19
Subject(s) - path analysis (statistics) , path coefficient , variables , competence (human resources) , structural equation modeling , psychology , statistics , mathematics , normality , regression analysis , econometrics , social psychology
In this study, researchers used data respondents, such as gender, age and long working respondents to provide information on the characteristics of respondents. The questionnaire was spread over 42. The discussion in this chapter is the result of field studies to obtain data on the questionnaire responses that measure five key variables in the study, namely competence, education, self efficacy, work spirit and employee performance. Analysis of data with parametric and non parametrics statistics using SEM-PLS (structural Equation Modelling-Partial Least Square) on the research variables, instrument test, normality test, hypothesis test, as well as discussion of the hypothesis test results and path analysis Path. This research uses path analysis to test relationship patterns that reveal the influence of variables or a set of variables against other variables, both direct influences and indirect influences. Calculation of line coefficient in this study assisted with Smart PLS Ver 3.0. To find out the direct and indirect influences between variables then be seen from the calculation result of the line coefficient and to know the significance.The influence of the variable X3 on X4 has a P-Values value of 0.008 <0.05, so it can be stated that the influence between X3 on X4 is significant. The influence of the variable X3 on X4 has a P-Values value of 0,000 <0.05, so it can be stated that the influence between X3 on X4 is significant. The influence of the variable X4 on Y has a P-Values value of 0.008 <0.05, so it can be stated that the influence between X4 on Y is significant. The influence of the variable X1 to X4 has a P-Values value of 0.010 <0.05, so it can be stated that the influence between X1 to X4 is significant. The effect of the variable X1 on Y has a P-Values value of 0.047 <0.05, so it can be stated that the effect between X1 on Y is significant. The influence of the variable X2 on X4 has a P-Values value of 0,000 <0.05, so it can be stated that the influence of X2 on X4 is significant. The effect of the variable X2 on Y has a P-Values value of 0.007 <0.05, so it can be stated that the influence between X2 on Y is significant.