Vol. 25 No. 11 (2026): Musytari: Neraca Manajemen, Akuntansi, dan Ekonomi, ISSN 3025-9495
Articles

Pengaruh Penggunaan Generative AI terhadap Efektivitas Kegiatan Mahasiswa Universitas Airlangga

Agustin Alfin Setyani
Program Studi D4 Manajemen Perkantoran Digital, Fakultas Vokasi, Universitas Airlangga, Surabaya, Indonesia
Rivanda Milani Putri
Program Studi D4 Manajemen Perkantoran Digital, Fakultas Vokasi, Universitas Airlangga, Surabaya, Indonesia
Amaliyah
Program Studi D4 Manajemen Perkantoran Digital, Fakultas Vokasi, Universitas Airlangga, Surabaya, Indonesia
Erindah Dimisyqiyani
Program Studi D4 Manajemen Perkantoran Digital, Fakultas Vokasi, Universitas Airlangga, Surabaya, Indonesia

Published 2026-10-07

Keywords

  • Generative AI,
  • Efektivitas kegiatan mahasiswa,
  • Universitas Airlangga

How to Cite

Pengaruh Penggunaan Generative AI terhadap Efektivitas Kegiatan Mahasiswa Universitas Airlangga. (2026). Musytari : Jurnal Manajemen, Akuntansi, Dan Ekonomi, 25(11). https://journal.cib.institute/index.php/musytari/article/view/4949

Abstract

Penggunaan Generative AI oleh mahasiswa tidak hanya berkaitan dengan capaian pembelajaran, tetapi juga mencakup pemanfaatannya dalam berbagai tahapan penyelesaian kegiatan. Namun, penelitian terdahulu lebih banyak mengkaji academic performance, learning outcomes, dan kemampuan pemecahan masalah, sehingga efektivitas kegiatan mahasiswa masih perlu dikaji secara lebih spesifik. Penelitian ini bertujuan untuk menganalisis pengaruh penggunaan Generative AI terhadap efektivitas kegiatan mahasiswa Universitas Airlangga. Penelitian ini menggunakan pendekatan kuantitatif dengan desain survei cross-sectional. Data diperoleh melalui kuesioner dari 65 mahasiswa aktif Universitas Airlangga yang pernah menggunakan Generative AI dalam kegiatan sebagai mahasiswa dan dipilih menggunakan purposive sampling. Data dianalisis menggunakan regresi linear sederhana. Hasil penelitian menunjukkan bahwa penggunaan Generative AI berpengaruh positif dan signifikan terhadap efektivitas kegiatan mahasiswa, dengan koefisien regresi sebesar 0,467, nilai t sebesar 4,338, dan signifikansi sebesar 0,000. Nilai R Square sebesar 0,230 menunjukkan bahwa penggunaan Generative AI menjelaskan 23,0% variasi efektivitas kegiatan mahasiswa dalam model penelitian. Temuan ini menunjukkan bahwa penggunaan Generative AI berpengaruh positif dan signifikan terhadap efektivitas kegiatan mahasiswa dalam model penelitian, yang mencakup pencapaian tujuan, kualitas hasil, efisiensi pelaksanaan, dan ketepatan waktu penyelesaian.

References

  1. Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of Generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21, 10. https://doi.org/10.1186/s41239-024-00444-7
  2. Barcelona, A., & Dela Cruz, S. R. (2025). Development and validation of a scale measuring students’ use of generative artificial intelligence tools. International Journal of Evaluation and Research in Education, 14(5), 3612–3621. https://doi.org/10.11591/ijere.v14i5.34809
  3. Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, 149. https://doi.org/10.3389/fpubh.2018.00149
  4. Chen, S., & Cheung, A. C. K. (2025). Effect of generative artificial intelligence on university students' learning outcomes: A systematic review and meta-analysis. Educational Research Review, 49, 100737. https://doi.org/10.1016/j.edurev.2025.100737
  5. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
  6. Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 227, 105224. https://doi.org/10.1016/j.compedu.2024.105224
  7. Gander, F., Gaitzsch, I., & Ruch, W. (2020). The relationships of team role- and character strengths-balance with individual and team-level satisfaction and performance. Frontiers in Psychology, 11, 566222. https://doi.org/10.3389/fpsyg.2020.566222
  8. Garalde, A., Solabarrieta, J., Urquijo, I., & Ortiz de Anda-Martín, I. (2024). Assessing peer teamwork competence: Adapting and validating the comprehensive assessment of team member effectiveness–short in university students. Frontiers in Education, 9, 1429485. https://doi.org/10.3389/feduc.2024.1429485
  9. Gasaymeh, A. M., Abu Qbeita, A., AlMohtadi, R., & Beirat, M. (2025). Exploring education students’ use of ChatGPT for academic and personal purposes: Insights from a developing country context. Frontiers in Education, 10, 1580310. https://doi.org/10.3389/feduc.2025.1580310
  10. Gibson, C. B., Zellmer-Bruhn, M. E., & Schwab, D. P. (2003). Team effectiveness in multinational organizations: Evaluation across contexts. Group & Organization Management, 28(4), 444–474. https://doi.org/10.1177/1059601103251685
  11. Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60–63. https://doi.org/10.4103/IJAM.IJAM_7_18
  12. Klasmeier, K. N., & Rowold, J. (2022). A diary study on shared leadership, teamwork engagement, and goal attainment. Journal of Occupational and Organizational Psychology, 95(1), 36–59. https://doi.org/10.1111/joop.12371
  13. Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., van Buuren, S., van der Beek, A. J., & de Vet, H. C. W. (2013). Development of an individual work performance questionnaire. International Journal of Productivity and Performance Management, 62(1), 6–28. https://doi.org/10.1108/17410401311285273
  14. López-López, E. M., Bru-Cordero, O. E., & Correa-Álvarez, C. D. (2026). Discipline-sensitive Generative AI in higher education. Encyclopedia, 6(6), 119. https://doi.org/10.3390/encyclopedia6060119
  15. Maier, C., Thatcher, J. B., Grover, V., & Dwivedi, Y. K. (2023). Cross-sectional research: A critical perspective, use cases, and recommendations for IS research. International Journal of Information Management, 70, 102625. https://doi.org/10.1016/j.ijinfomgt.2023.102625
  16. Memon, M. A., Tunca, B., Ting, H., Cheah, J.-H., Thurasamy, R., & Chuah, F. (2024). Purposive sampling: A review and guidelines for quantitative research. Journal of Applied Structural Equation Modeling, 9(1), 1–23. https://doi.org/10.47263/JASEM.9(1)01
  17. Nemt-allah, M., Khalifa, W., Badawy, M., Elbably, Y., & Ibrahim, A. (2024). Validating the ChatGPT usage scale: Psychometric properties and factor structures among postgraduate students. BMC Psychology, 12, 497. https://doi.org/10.1186/s40359-024-01983-4
  18. Roustaei, N. (2024). Application and interpretation of linear regression analysis. Medical Hypothesis, Discovery & Innovation in Ophthalmology, 13(3), 151–159. https://doi.org/10.51329/mehdiophthal1506
  19. Urban, M., Děchtěrenko, F., Lukavský, J., Hrabalová, V., Svacha, F., Brom, C., & Urban, K. (2024). ChatGPT improves creative problem-solving performance in university students: An experimental study. Computers & Education, 215, 105031. https://doi.org/10.1016/j.compedu.2024.105031
  20. van Woerkom, M., & Croon, M. A. (2009). The relationships between team learning activities and team performance. Personnel Review, 38(5), 560–577. https://doi.org/10.1108/00483480910978054