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All Journal Jurnal Manajemen dan Kewirausahaan
Chairuddin Chairuddin
Sekolah Tinggi Manajemen Informatika dan Komputer Indonesia Mandiri
Economics, Econometrics & Finance

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THE ROLE OF ARTIFICIAL INTELLIGENCE COMPETENCIES, ORGANIZATIONAL SUPPORT, AND EMPLOYEE SELF-EFFICACY IN PREDICTING GOVERNMENT EMPLOYEE PERFORMANCE: A MEDIATION ANALYSIS WITH WORK ENGAGEMENT Afzil Ramadian; Chairuddin Chairuddin; Loso Judijanto; Rachmawati Rachmawati; Encep Sopandi
Jurnal Manajemen dan Kewirausahaan Vol. 27 No. 1 (2025): MARCH 2025
Publisher : Management Study Program, Faculty of Business and Economics, Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jmk.27.1.22-32

Abstract

The purpose of this research is to determine the role of Artificial Intelligence Competencies, organizational support, and employee self-efficacy in predicting the performance of government employees. This research uses quantitative methods with a type of correlation research. The structural Equation Model (SEM) approach is assisted by the smart PLS application. This approach was chosen because it aims to determine the correlation between the Artifical Intelligence Competencies, Organizational Support, and Employee Self-Efficacy variables: Employee Self-Efficacy. Data analysis in this research used descriptive analysis and statistical analysis. Descriptive analysis is done by describing the results of the sampling percentage. Based on the results of the research, we show that Artificial Intelligence (AI) competencies, employee self-efficacy, work engagement, and organizational support proved to have an important contribution to improving the performance of government employees. Implications of this study indicates the need of holistic approach in human resource management in government sector. Organizations should also develop technical competencies like artificial intelligence and support psychological competencies like self-efficacy and work engagement through just policies and sufficient facilities.
Co-Authors Afzil Ramadian Encep Sopandi, Encep Loso Judijanto Rachmawati Rachmawati