Pengaruh Penggunaan Artificial Intelligence (AI) dan Literasi Digital terhadap Kemampuan Akademik Mahasiswa Jurusan Ekonomi Stambuk 2023 Fakultas Ekonomi dan Bisnis Universitas Negeri Medan
Abstract
The rapid integration of artificial intelligence (AI) into higher education has expanded students' access to academic support, yet its educational value may depend on students' capacity to navigate and evaluate digital information critically. This study examined the effects of AI use and digital literacy on the academic ability of Economics Department students from the 2023 cohort at the Faculty of Economics and Business, Universitas Negeri Medan. Using a quantitative ex post facto design, data were collected from 158 students selected from a population of 261 through questionnaire-based measures and analyzed using instrument testing, classical assumption tests, multiple linear regression, partial t-tests, an F-test, and the coefficient of determination. AI use had a positive and statistically significant effect on academic ability (t = 2.798, p = .006), while digital literacy showed a stronger positive and significant effect (t = 5.840, p < .001). Jointly, both predictors significantly explained academic ability (F = 47.630, p < .001), with R² = .381, indicating that 38.1% of the variance was accounted for by the model. These findings demonstrate that AI is most educationally meaningful when accompanied by students' capacity to access, evaluate, verify, and use digital information responsibly. The study implies that universities should integrate AI-use guidance with systematic digital-literacy development so that AI functions as a cognitive support tool rather than a substitute for independent academic reasoning.
References
1
UNESCO, AI and Education: Guidance for Policy-Makers. Paris, France: UNESCO, 2021.
2
O. Zawacki-Richter, V. I. Marin, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education where are the educators?,” International Journal of Educational Technology in Higher Education, vol. 16, Art. no. 39, 2019. https://doi.org/10.1186/s41239-019-0171-0
3
Y. K. Dwivedi, L. Hughes, E. Ismagilova, G. Aarts, C. Coombs, T. Crick, Y. Duan, R. Dwivedi, J. Edwards, and A. Eirug, “Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy,” International Journal of Information Management, vol. 57, Art. no. 101994, 2021. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
4
F. J. Hamu, D. Wea, and N. Setiyaningtiyas, “Faktor-faktor yang mempengaruhi kinerja akademik mahasiswa: Analisis structural equation model,” Jurnal Paedagogi, vol. 10, no. 1, pp. 175–186, 2023. https://doi.org/10.33394/jp.v10i1.6473
5
A. Fitriana and N. Kurniasih, “Prestasi belajar mahasiswa (studi mahasiswa PAI yang aktif berorganisasi di IAIIG Cilacap),” Jurnal Tawadhu, vol. 5, no. 1, pp. 44–58, 2021. https://doi.org/10.52802/twd.v5i1.140
6
D. Ifenthaler, R. Majumdar, P. Gorissen, M. Judge, S. Mishra, J. Raffaghelli, and A. Shimada, “Artificial intelligence in education: Implications for policymakers, researchers, and practitioners,” Technology, Knowledge and Learning, vol. 29, no. 4, pp. 1693–1710, 2024. https://doi.org/10.1007/s10758-024-09747-0
7
F. Li, L. Cheng, X. Wang, L. Shen, Y. Ma, and A. Y. M. Atiquil Islam, “The causal relationship between digital literacy and students’ academic achievement: A meta-analysis,” Humanities and Social Sciences Communications, vol. 12, Art. no. 108, 2025. https://doi.org/10.1057/s41599-025-04399-6
8
A. Caton, Kinshuk, and W. Savenye, “Dependencies of digital literacy domains for improved college readiness in higher education: A systematic literature review,” Technology, Knowledge and Learning, 2025. https://doi.org/10.1007/s10758-025-09872-4
9
Y. K. Dwivedi, N. Kshetri, L. Hughes, E. L. Slade, A. Jeyaraj, A. K. Kar, A. M. Baabdullah, A. Koohang, V. Raghavan, M. Ahuja, et al., “So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy,” International Journal of Information Management, vol. 71, Art. no. 102642, 2023. https://doi.org/10.1016/j.ijinfomgt.2023.102642
10
E. Kasneci, K. Sessler, S. Kuchemann, M. Bannert, D. Dementieva, F. Fischer, U. Gasser, G. Groh, S. Gunnemann, E. Hullermeier, et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learning and Individual Differences, vol. 103, Art. no. 102274, 2023. https://doi.org/10.1016/j.lindif.2023.102274
11
S. AlBlooshi, “Artificial intelligence in higher education, opportunities, and challenges: A review,” Frontiers in Education, vol. 10, Art. no. 1683968, 2026. https://doi.org/10.3389/feduc.2025.1683968
12
D. Y. Long, S. Wang, S. Md Rashid, and X. T. Lu, “Artificial intelligence in higher education: A systematic review of its impact on student engagement and the mediating role of teaching methods,” Frontiers in Education, vol. 10, Art. no. 1648661, 2026. https://doi.org/10.3389/feduc.2025.1648661
13
L. Dong, X. Tang, and X. Wang, “Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis,” Computers and Education: Artificial Intelligence, vol. 8, Art. no. 100400, 2025. https://doi.org/10.1016/j.caeai.2025.100400
14
C. Fan, L. Ke, Z. Chen, and P. Lv, “Exploring the effect of GenAI on learning outcomes in higher education: A three-level meta-analysis,” Frontiers in Psychology, vol. 17, Art. no. 1758670, 2026. https://doi.org/10.3389/fpsyg.2026.1758670
15
C. Liu, L. Xie, and G. Xu, “Generative AI in higher education: A meta-analysis of intellectual and social-emotional outcomes,” Frontiers in Psychology, vol. 17, Art. no. 1848745, 2026. https://doi.org/10.3389/fpsyg.2026.1848745
16
Y. Kokver, H. M. Pektas, and H. Celik, “Artificial intelligence applications in education: Natural language processing in detecting misconceptions,” Education and Information Technologies, vol. 30, pp. 3035–3066, 2025. https://doi.org/10.1007/s10639-024-12919-1
17
R. Ilfi and S. Manaf, “Kecerdasan buatan dan kaitannya dalam membentuk nilai dan karakter dalam pendidikan,” ISTIGHNA: Jurnal Pendidikan dan Pemikiran Islam, vol. 7, no. 1, pp. 40–50, 2024.
18
N. Isnain, “Implementasi artificial intelligence dalam sektor pendidikan,” Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research, vol. 2, no. 2, pp. 3175–3182, 2025. https://doi.org/10.32672/mister.v2i2.3104
19
P. Enriquez, H.-Y. Lin, and C. Baciu, “Artificial intelligence in higher education: Student use, perceived benefits, and emerging risks,” Frontiers in Education, vol. 11, Art. no. 1812390, 2026. https://doi.org/10.3389/feduc.2026.1812390
20
A. M. Vieriu and G. Petrea, “The impact of artificial intelligence (AI) on students’ academic development,” Education Sciences, vol. 15, no. 3, Art. no. 343, 2025. https://doi.org/10.3390/educsci15030343
21
E. Ferrara, “GenAI against humanity: Nefarious applications of generative artificial intelligence and large language models,” Journal of Computational Social Science, vol. 7, no. 1, pp. 549–569, 2024. https://doi.org/10.1007/s42001-024-00250-1
22
Y.-L. Lin, W.-T. Wang, and C. Chen, “AI-enhanced education: Exploring the impact of students’ GenAI literacy on their psychological factors and learning performance,” The International Journal of Management Education, vol. 24, no. 2, Art. no. 101411, 2026. https://doi.org/10.1016/j.ijme.2026.101411
23
S.-C. Kong, W. M.-Y. Cheung, and G. Zhang, “Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds,” Computers and Education: Artificial Intelligence, vol. 2, Art. no. 100026, 2021. https://doi.org/10.1016/j.caeai.2021.100026
24
M. D. Adewale, A. Azeta, A. Abayomi-Alli, and A. Sambo-Magaji, “Impact of artificial intelligence adoption on students’ academic performance in open and distance learning: A systematic literature review,” Heliyon, vol. 10, no. 22, Art. no. e40025, 2024. https://doi.org/10.1016/j.heliyon.2024.e40025
25
Sugiyono, Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung, Indonesia: Alfabeta, 2019.
26
S. Arikunto, Prosedur Penelitian: Suatu Pendekatan Praktik, rev. ed. Jakarta, Indonesia: Rineka Cipta, 2010.
27
I. Maesaroh, U. A. Miladia, M. Fithriyan, and L. Nulhakim, “Teknik pengumpulan data dalam penelitian,” Pendas: Jurnal Ilmiah Pendidikan Dasar, vol. 10, no. 2, 2025. https://doi.org/10.23969/jp.v10i02.27110
28
A. A. Zayrin, H. Nupus, K. K. Maizia, S. Marsela, R. Hidayatullah, and H. Harmonedi, “Analisis instrumen penelitian pendidikan (uji validitas dan reliabilitas instrumen penelitian),” Jurnal QOSIM: Jurnal Pendidikan Sosial & Humaniora, vol. 3, no. 2, pp. 780–789, 2025. https://doi.org/10.61104/jq.v3i2.1070
29
W. Agustinaningsih and A. Nurjanah, “Pengembangan dan uji validitas serta reliabilitas instrumen angket kemampuan sosiosaintifik pada evaluasi pembelajaran fisika,” KUANTUM: Jurnal Pembelajaran dan Sains Fisika, vol. 6, no. 2, pp. 308–317, 2025. https://doi.org/10.63976/kuantum.v6i2.1186
30
E. and Sarwani, “Uji asumsi klasik dalam regresi linier berganda,” KEIZAI: Jurnal Kajian Ekonomi, Manajemen, & Akuntansi, vol. 6, no. 1, pp. 120–134, 2025. https://doi.org/10.56589/keizai.v6i1.523
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2026-08-18
