Penerimaan ChatGPT di Perguruan Tinggi: PRISMA Systematic Literature Review Berbasis Model TAM dan UTAUT
Keywords:
Artificial IntelligenceAbstract
Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi penerimaan dan adopsi ChatGPT sebagai teknologi kecerdasan buatan (Artificial Intelligence/AI) di lingkungan pendidikan tinggi melalui pendekatan PRISMA Systematic Literature Review (SLR). Kajian ini mengintegrasikan dua model teoritis utama dalam penelitian penerimaan teknologi, yaitu Technology Acceptance Model (TAM) dan Unified Theory of Acceptance and Use of Technology (UTAUT). Sebanyak 40 artikel ilmiah yang terbit pada periode 2022–2025 dianalisis secara sistematis berdasarkan kriteria inklusi dan eksklusi yang relevan. Hasil analisis menunjukkan bahwa faktor Habit, Performance Expectancy, Social Influence, dan Hedonic Motivation merupakan determinan dominan yang memengaruhi niat perilaku (Behavioral Intention) dalam penggunaan ChatGPT di perguruan tinggi. Selain itu, penelitian ini juga mengidentifikasi adanya celah konseptual terkait variabel moderator seperti jenis kelamin, usia, dan literasi AI, yang belum banyak diteliti secara mendalam pada konteks pendidikan tinggi di Indonesia. Temuan ini diharapkan dapat memberikan kontribusi akademik dalam pengembangan model penerimaan teknologi berbasis AI serta menjadi acuan praktis bagi pengambil kebijakan dan pengembang aplikasi pendidikan digital untuk meningkatkan adopsi teknologi secara efektif di era pembelajaran berbasis kecerdasan buatan.
References
“ChatGPT: Optimizing language models for dialogue.,” Open AI. [Online]. Available: https://openai.com/blog/chatgpt
S. Alghamdi and Y. Alhasawi, “Exploring The Factors Influencing the Adoption of ChatGPT in Educational Institutions: Insights from Innovation Resistance Theory,” J. Appl. Data Sci., vol. 5, no. 2, pp. 474–490, 2024, doi: 10.47738/jads.v5i2.198.
H. Moradi, “Integrating AI in higher education: factors influencing ChatGPT acceptance among Chinese university EFL students,” Int. J. Educ. Technol. High. Educ., vol. 22, no. 1, 2025, doi: 10.1186/s41239-025-00530-4.
F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Q. Manag. Inf. Syst., vol. 13, no. 3, pp. 319–339, 1989, doi: 10.2307/249008.
V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Q. Manag. Inf. Syst., vol. 27, no. 3, pp. 425–478, 2003, doi: 10.2307/30036540.
A. Strzelecki, “Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology,” Innov. High. Educ., vol. 49, no. 2, pp. 223–245, 2024, doi: 10.1007/s10755-023-09686-1.
N. I. Mohd Rahim, N. A. Iahad, A. F. Yusof, and M. A. Al-Sharafi, “AI-Based Chatbots Adoption Model for Higher-Education Institutions: A Hybrid PLS-SEM-Neural Network Modelling Approach,” Sustain., vol. 14, no. 19, 2022, doi: 10.3390/su141912726.
A. Pratita, T. L. M. Suryanto, A. Pratama, and A. Wibowo, “ChatGPT in Education: Investigating Students Online Learning Behaviors,” Int. J. Inf. Educ. Technol., vol. 15, no. 3, pp. 510–524, 2025, doi: 10.18178/ijiet.2025.15.3.2262.
S. Taylor and P. A. Todd, “Understanding information technology usage.pdf.crdownload.pdf,” 1995. [Online]. Available: https://www.jstor.org/stable/23011007
V. Venkatesh and F. D. Davis, “Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies,” Manage. Sci., vol. 46, no. 2, pp. 186–204, 2000, doi: 10.1287/mnsc.46.2.186.11926.
S. Dube et al., Students’ Perceptions of ChatGPT in Education: A Rapid Systematic Literature Review, vol. 1019 LNNS, no. June 2025. Springer Nature Switzerland, 2024. doi: 10.1007/978-3-031-62273-1_18.
A. Anwar, N. Thongpapanl, and A. R. Ashraf, “Strategic imperatives of mobile commerce in developing countries: the influence of consumer innovativeness, ubiquity, perceived value, risk, and cost on usage,” J. Strateg. Mark., vol. 29, no. 8, pp. 722–742, 2021, doi: 10.1080/0965254X.2020.1786847.
V. Venkatesh, J. Y. L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology,” MIS Q. Manag. Inf. Syst., vol. 36, no. 1, pp. 157–178, 2012, doi: 10.2307/41410412.
S. Kitchenham, B., & Charters, “Guidelines for performing systematic literature reviews in software engineering,” Tech. report, Ver. 2.3 EBSE Tech. Report. EBSE, no. January 2007, pp. 1–57, 2007.
S. W. Romi, “A Systematic Literature Review of Software Defect Prediction: Research Trends, Datasets, Methods and Frameworks,” J. Softw. Eng., vol. 1, no. 1, pp. 1–16, 2015.
M. J. Page et al., “The PRISMA 2020 statement: An updated guideline for reporting systematic reviews,” Bmj, vol. 372, 2021, doi: 10.1136/bmj.n71.
