Analisis Dampak Penggunaan Artificial Intelligence Terhadap Lapangan Kerja Pada Mahasiswa Universitas Pahlawan - Amra Az Zahra; R. Joko Musridho; Rofdan Azzaky Fauzi; Bayu Gunawan; Amita Apriyani; Ari Hendrawan; Khairun Fadli; Isfi Alyuda; Widia Ningsih; Salsabillah Rahmadhani; Ardiansyah Mulia; Arlian Dinata (Global Sustainability Research Institute, 2026)
Introduction: The rapid development of Artificial Intelligence (AI) has significantly transformed various sectors, particularly the labor market. While AI offers opportunities to improve efficiency and productivity, it also raises concerns regarding the potential reduction of human labor demand in certain occupations. This study aims to analyze the perceptions of Universitas Pahlawan students regarding the impact of AI on employment and to determine whether AI is predominantly perceived as an opportunity or a threat. Methods:This study employed a quantitative research approach using the Naive Bayes algorithm as the primary classification method. Data were collected through an online questionnaire distributed to 100 Universitas Pahlawan students who had prior experience using AI technologies. The collected data were analyzed to classify respondents' perceptions into opportunity, threat, and neutral categories. Results: The findings revealed that 38% of respondents perceived AI as an opportunity, 37% viewed it as a threat, and 25% expressed a neutral perception. Furthermore, the Naive Bayes classification results indicated that the opportunity category had the highest probability, suggesting that most respondents tend to hold positive perceptions of AI in the context of future employment. Conclusion and Suggestion: The study concludes that Universitas Pahlawan students generally perceive AI as an opportunity rather than a threat in the workplace. Nevertheless, continuous efforts to enhance digital literacy, technological competencies, and adaptability are essential to enable students to respond effectively to the evolving demands of the AI-driven labor market. Future research is recommended to involve a larger and more diverse sample across different universities and demographic backgrounds to improve the generalizability of the findings.