Pengaruh Literasi Digital terhadap Etika Penggunaan Artificial Intelligence pada Mahasiswa Perguruan Tinggi
DOI:
https://doi.org/10.35870/jtik.v11i1.7479Keywords:
Digital Literacy, AI Ethics, Artificial Intelligence, Students, Higher EducationAbstract
The development of Artificial Intelligence (AI) in higher education has transformed the way students seek information, complete assignments, and understand academic materials. However, AI use also raises ethical issues, including plagiarism, overreliance on instant answers, and a lack of transparency in acknowledging AI assistance. This study aims to analyze the effect of digital literacy on the ethical use of AI among university students. A quantitative survey method was employed. Data were collected using a 1–5 Likert-scale questionnaire from 125 respondents, with 119 complete responses analyzed. Digital literacy was measured using 12 items, while ethical AI use was measured using 12 items. Data were analyzed using descriptive statistics, validity testing, reliability testing, correlation, and simple linear regression. The results show that digital literacy has a positive and significant effect on ethical AI use. The correlation coefficient of 0.638 indicates a strong relationship, while the coefficient of determination of 0.406 indicates that digital literacy explains 40.6% of the variation in ethical AI use. The regression equation is Y = 1.196 + 0.706X. These findings indicate that students with higher digital literacy tend to use AI more ethically, responsibly, and transparently. This study recommends strengthening digital literacy programs with an emphasis on AI ethics in higher education.
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References
Aswan, D. (2025). Hubungan antara literasi digital dan persepsi mahasiswa tentang etika penggunaan AI di kalangan akademik. Jurnal Ilmiah Wahana Pendidikan, 11(6.D), 283–294.
Bittle, K., & El-Gayar, O. (2025). Generative AI and academic integrity in higher education: A systematic review and research agenda. Information, 16(4), 296.
Chen, K., Tallant, A. C., & Selig, I. (2025). Exploring generative AI literacy in higher education: Student adoption, interaction, evaluation, and ethical perceptions. Information and Learning Sciences, 126(1–2), 132–148.
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating? Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239.
Gu, X., & Ericson, B. J. (2025). AI literacy in K-12 and higher education in the wake of generative AI: An integrative review.
Hazari, S., & Vaidya, S. (2024). Artificial intelligence literacy for higher education. Journal of Educational Research and Practice, 14(1).
Huang, Y. (2015). Research of big data based on the views of technology and application. The Open Automation and Control System, (April), 1312–1317. https://doi.org/10.4236/ajibm.2015.54021.
Kementerian Komunikasi dan Informatika, Japelidi, & Siberkreasi. (2023). Empat Pilar Literasi Digital: Cakap, Aman, Budaya, dan Etika Digital. Jakarta.
Lund, B., & Wang, T. (2025). Student perceptions of AI-assisted writing and academic integrity. AI, 1(1), 15–28.
Marin, Y. R., et al. (2025). Ethical challenges associated with the use of artificial intelligence in universities. Journal of Academic Ethics, 23(2), 201–219.
McDonald, N., Johri, A., Ali, A., & Hingle, A. (2024). Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines. ArXiv.
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI Literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041.
Ng, W. (2012). Can we teach digital natives digital literacy? Computers & Education, 59(3), 1065–1078.
UNESCO. (2023). Guidance for Generative AI in Education and Research. UNESCO Publishing.
Zalisman. (2025). Students’ academic integrity index in using generative artificial intelligence among Islamic education major students in Islamic higher education. POTENSIA: Jurnal Kependidikan Islam, 9(2). https://doi.org/10.24014/potensia.v9i2.37740.
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Copyright (c) 2027 Yusuf Unggul Budiman, Ahmad Jurnaidi Wahidin, Daz Vholasky Anggraini

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