Computer Science Students’ Intention to Use AI Assistants: Extended UTAUT2

Lutfi Firmansyah Putra Mamangkei, Kurnia Ramadhan Putra, Ahmad Fahri

Abstract


Perkembangan pesat Artificial Intelligence (AI) Assistant telah mengubah lanskap pembelajaran di perguruan tinggi, khususnya di kalangan mahasiswa Rumpun Ilmu Komputer. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi niat perilaku (behavioral intention) mahasiswa dalam menggunakan AI Assistant dengan mengembangkan model Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) melalui penambahan variabel AI Literacy dan Trust. Penelitian ini menggunakan pendekatan kuantitatif eksplanatori dengan metode survei terhadap 90 mahasiswa bidang teknologi. Analisis data dilakukan menggunakan Partial Least Squares Structural Equation Modeling (PLS-SEM) dengan bantuan perangkat lunak SmartPLS 4. Hasil penelitian menunjukkan bahwa model memiliki kemampuan prediksi yang kuat dengan nilai R-square sebesar 0,755. Temuan empiris menunjukkan bahwa Habit, Trust, dan Social Influence berpengaruh signifikan terhadap niat penggunaan AI Assistant. Sebaliknya, AI Literacy dan Effort Expectancy tidak menunjukkan pengaruh yang signifikan, yang mengindikasikan bahwa pada mahasiswa dengan latar belakang teknis, kebiasaan penggunaan dan tingkat kepercayaan terhadap keandalan sistem lebih menentukan niat penggunaan dibandingkan aspek kemudahan penggunaan.


Keywords


Asisten AI; Literasi AI; Mahasiswa Ilmu Komputer; Kepercayaan; UTAUT2

References


Y. K. Dwivedi et al., "“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy," Int. J. Inf. Manage., vol. 71, p. 102642, Aug. 2023, doi: 10.1016/j.ijinfomgt.2023.102642.

A. Yani, "Peran artificial intelligence sebagai salah satu faktor dalam menentukan kualitas mahasiswa di era society 5.0," J. Educ. Res., vol. 5, no. 3, pp. 1089–1096, 2024.

D. Baidoo-Anu and L. O. Ansah, "Education in the era of generative AI: Understanding the potential benefits of ChatGPT in promoting teaching and learning," J. AI, vol. 7, no. 1, pp. 33–51, 2023.

B. G. Acosta-Enriquez et al., "Acceptance of artificial intelligence in university contexts: A conceptual analysis based on UTAUT2 theory," Heliyon, vol. 10, no. 20, p. e38315, 2024.

V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, "User acceptance of information technology: toward a unified view," MIS Quart., vol. 27, no. 3, pp. 425–478, Sep. 2003.

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 Quart., vol. 36, no. 1, pp. 157–178, Mar. 2012.

A. Strzelecki, "To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology," Interact. Learn. Environ., pp. 1–14, 2023, doi: 10.1080/10494820.2023.2209881.

F. N. A'ini, I. S. E. Maghfiroh, and Y. T. Mursityo, "Analisis faktor yang memengaruhi niat dan perilaku penggunaan ChatGPT pada mahasiswa menggunakan model UTAUT2 termodifikasi," J. Sist. Informasi, Teknol. Informasi, dan Edukasi Sist. Informasi (JUST-SI), vol. 5, no. 1, pp. 1–12, 2024.

L. A. Galantry and A. R. Tanaamah, "Analisis adopsi ChatGPT menggunakan model UTAUT," Sistemasi: J. Sist. Informasi, vol. 13, no. 3, pp. 1216–1225, 2024.

F. A. Nugroho, A. D. Herlambang, A. Rachmadi, and E. E. Sasmita, "Analisis persepsi mahasiswa rumpun ilmu komputer terhadap pemanfaatan artificial intelligence dalam penulisan tugas akhir," J. Teknol. Inf. dan Ilmu Komputer (JTIIK), vol. 12, no. 4, pp. 829–842, 2025.

A. N. Umami, A. Mukminin, and R. Hartono, "Students' perception of the use of AI chatbot in English writing class," Techno-Educ., vol. 3, no. 2, 2025.

D. T. K. Ng, J. K. L. Leung, S. K. W. Chu, and M. S. Qiao, "Conceptualizing AI literacy: An exploratory review and framework," Comput. Educ. Artif. Intell., vol. 2, p. 100031, 2021, doi: 10.1016/j.caeai.2021.100031.

D. Long and B. Magerko, "What is AI literacy? Competencies and design considerations," in Proc. 2020 CHI Conf. Human Factors Comput. Syst., Honolulu, HI, USA, 2020, pp. 1–16.

T. Robinson, "Generative artificial intelligence in higher education: Understanding faculty adoption through the technology acceptance model," Int. Educ. Cult. Stud., vol. 5, no. 2, 2025.

D. Gefen, E. Karahanna, and D. W. Straub, "Trust and TAM in online shopping: An integrated model," MIS Quart., vol. 27, no. 1, pp. 51–90, Mar. 2003.

J. F. Hair Jr, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd ed. Thousand Oaks, CA, USA: Sage, 2021.

W. W. Chin, "The partial least squares approach to structural equation modeling," in Modern Methods for Business Research, G. A. Marcoulides, Ed. Mahwah, NJ: Lawrence Erlbaum Associates, 1998, pp. 295–336.

J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, "When to use and how to report the results of PLS-SEM," Eur. Bus. Rev., vol. 31, no. 1, pp. 2–24, 2019.

C. Fornell and D. F. Larcker, "Evaluating structural equation models with unobservable variables and measurement error," J. Mark. Res., vol. 18, no. 1, pp. 39–50, 1981.

J. Henseler, C. M. Ringle, and M. Sarstedt, "A new criterion for assessing discriminant validity in variance-based structural equation modeling," J. Acad. Mark. Sci., vol. 43, no. 1, pp. 115–135, 2015.


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