THE ROLE OF ARTIFICIAL INTELLIGENCE COMPETENCIES, ORGANIZATIONAL SUPPORT, AND EMPLOYEE SELF-EFFICACY IN PREDICTING GOVERNMENT EMPLOYEE PERFORMANCE: A MEDIATION ANALYSIS WITH WORK ENGAGEMENT

Authors

DOI:

https://doi.org/10.9744/jmk.27.1.22-32

Keywords:

Artificial Intelligence Competencies, Organizational Support, Employee Self-Efficacy, Government Employee Performance

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.

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2025-03-28

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Ramadian, A., Chairuddin, C., Judijanto, L., Rachmawati, R., & Sopandi, E. (2025). THE ROLE OF ARTIFICIAL INTELLIGENCE COMPETENCIES, ORGANIZATIONAL SUPPORT, AND EMPLOYEE SELF-EFFICACY IN PREDICTING GOVERNMENT EMPLOYEE PERFORMANCE: A MEDIATION ANALYSIS WITH WORK ENGAGEMENT. Jurnal Manajemen Dan Kewirausahaan, 27(1), 22–32. https://doi.org/10.9744/jmk.27.1.22-32

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Vol. 27 No. 1 (2025): MARCH 2025

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