THE EFFECT OF ACADEMIC SELF-EFFICACY ON ACADEMIC BURNOUT ON ENGINEERING STUDENTS WHO WORK

Abstract

Students who work are required to be able to carry out their duties and responsibilities well, starting from time management between the time spent in college and work, discipline, both in lectures and in work, and paying attention to physical health conditions because students have to divide roles between become a student and employee. Going to college while working is not easy. So that when students are not able to carry out these dual roles, it will lead to academic burnout. This study aims to prove empirically the Effect of Academic Self-Efficacy on Academic Burnout. This study uses quantitative methods with a population of 131 students. In this case, the researcher used a non-probability sampling technique with incidental sampling technique, which resulted in a total of 69 students working. The data collection method is in the form of a questionnaire collected online using google form. The scale used is the Likert scale with 4 (four) alternative answers. Test the validity of the scale using content validity. The scale reliability test uses the Cronbach alpha technique. The data analysis technique uses simple linear regression. The results of the study indicate that there is a significant negative effect between the academic self-efficacy variable and academic burnout, which means that the higher the academic self-efficacy, the lower the academic burnout. This research is expected to enrich the reader's knowledge about the topic of Burnout, especially the Effect of Academic Self-Efficacy on Academic Burnout on Students of the Faculty of Engineering, University of X who are working. In addition, the results of the existing research are expected to be a reference for further research. This study uses incidental sampling technique so that it cannot be ascertained that the subjects are representative of all study programs. It is hoped that future researchers will use subjects from all study programs so that research results can be generalized.