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The Influence of Artificial Intelligence Knowledge and Job Market Awareness on Fresh Graduates’ Quality : The Mediating Role of Employability Skill Handayani, Feliana; Nurmalasari, Made Ratih
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.5671

Abstract

In Indonesia, rapid AI adoption and digital transformation in various sectors have created new demands for graduates to possess both technological literacy and employability skills. Many fresh graduates face a skills mismatch, as traditional curricula lag behind industry needs, requiring not only technical knowledge but also critical thinking, problem-solving, and adaptability. This study aims to analyze the effects of AI Knowledge and Job Market Awareness on Fresh Graduates’ Quality with Employability Skills as a mediating variable. This research adopts a quantitative approach using a survey method. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to examine the relationships among the research variables. This study finds that AI Knowledge and Job Market Awareness positively and significantly influence Employability Skills and Fresh Graduates’ Quality. Employability Skills have a direct effect on graduate quality and also mediate the effects of AI Knowledge and Job Market Awareness, indicating that skill development is the main pathway through which technological understanding and labor market awareness enhance graduates’ work readiness and overall quality. Based on the findings, students are encouraged to strengthen their critical evaluation skills when using AI tools, develop a more realistic understanding of job market conditions, enhance their ability to assess the accuracy and relevance of digital information, and consistently demonstrate ethical and responsible behavior in academic and professional activities. Future research is recommended to involve broader samples and additional variables to improve generalizability and to further examine factors influencing fresh graduates’ quality in AI-driven labor markets.