Faktor-Faktor yang Mempengaruhi Niat Mahasiswa Pendidikan Ekonomi untuk Menggunakan ChatGPT dalam Pembelajaran: Penerapan Model UTAUT
Keywords:
ChatGPT ; UTAUT Model; Intention to UseAbstract
Technological developments in the world of education are increasingly
developing, one of which is the emergence of generative AI such as ChatGPT,
which has been widely used to assist in academic activities. However, the
accuracy of the information generated by ChatGPT is sometimes misleading,
which can affect students' intentions to use ChatGPT. This study aims to
analyze the factors that influence the intention to use ChatGPT by economics
education students in East Java using the UTAUT model. A quantitative
approach with a survey method in the form of a questionnaire was used in this
study. The population used in this study included all undergraduate economics
education students in East Java who have used ChatGPT in learning. The
sampling technique in this study used simple random sampling and the number
of samples used in this study was 170 respondents. Online questionnaires were
distributed via Google Forms to collect data in this study, and PLS-SEM with
the help of SmartPLS 4 software was used for research data analysis techniques.
This study found that all variables in the UTAUT model, including effort
expectancy, facilitating condition, performance expectancy, and social
influence, have a positive effect on students' intentions to use ChatGPT. This
shows that the intention to use ChatGPT among economics students is
influenced by perceptions regarding ease of use, availability of supporting
facilities, performance benefits, and social support.
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Abdalla, Suliman Zakaria Suliman. 2025. “Understanding ChatGPT Adoption for Data Analytics Learning: A UTAUT Perspective among Social Science Students in Oman.” Social Sciences and Humanities Open 101310. doi: https://doi.org/10.1016/j.ssaho.2025.101310.
Al-mamary, Yaser Hasan Salem. 2022. “International Journal of Information Management Data Insights Understanding the Use of Learning Management Systems by Undergraduate University Students Using the UTAUT Model : Credible Evidence from Saudi Arabia.” Internasional Journal of Information Management Data Insightd 2 2:100092. doi: 10.1016/j.jjimei.2022.100092.
Al-nuaimi, Maryam Nasser, Omar Said Al Sawafi, Sohail Iqbal Malik, and Rana Saeed Al-Maroof. 2022. “Extending the Unified Theory of Acceptance and Use of Technology to Investigate Determinants of Acceptance and Adoption of Learning Management Systems in the Post-Pandemic Era : A Structural Equation Modeling Approach.” Interactive Learning Environments 1–27. doi: 10.1080/10494820.2022.2127777.
Arthur, F., I. Salifu, and S. Abam Nortey. 2025. “Predictors of Higher Education Students’ Behavioural Intention and Usage of ChatGPT: The Moderating Roles of Age, Gender and Experience.” Interactive Learning Environments 33(2):993–1019. doi: 10.1080/10494820.2024.2362805.
Bahadur, S. G. C., P. Bhandari, S. K. Gurung, E. Srivastava, D. Ojha, and B. R. Dhungana. 2024. “Examining the Role of Social Influence, Learning Value and Habit on Students’ Intention to Use ChatGPT: The Moderating Effect of Information Accuracy in the UTAUT2 Model.” Cogent Education 11(1). doi: 10.1080/2331186X.2024.2403287.
Bayaga, Anass. 2025. “AI-Powered Platforms in STEM Education, Insights from UTAUT Model : PLS-SEM and Artificial Neural Networks Hybrid Analysis.” Telematics and Informatics Reports 20:100266.
Bhattacharya, K., A. S. Bhattacharya, N. Bhattacharya, V. D. Yagnik, P. Garg, and S. Kumar. 2023. “ChatGPT in Surgical Practice—a New Kid on the Block.” Indian Journal of Surgery 85(6):1346–49. doi: 10.1007/s12262-023-03727-x.
Budhathoki, Tribikram, Araz Zirar, Eric Tchouamou Njoya, and Achyut Timsina. 2024. “ChatGPT Adoption and Anxiety: A Cross-Country Analysis Utilising the Unified Theory of Acceptance and Use of Technology (UTAUT).” Studies in Higher Education 49(5):831–46. doi: 10.1080/03075079.2024.2333937.
Damtew, Agmasie, Adamu Takele, Binyam Tilahun, Masresha Derese, and Kassahun Dessie. 2023. “Informatics in Medicine Unlocked Intention to Use Wearable Health Devices and Its Predictors among Diabetes Mellitus Patients in Amhara Region Referral Hospitals , Ethiopia : Using Modified UTAUT-2 Model.” Informatics in Medicine Unlocked 36(December 2022):101157. doi: 10.1016/j.imu.2022.101157.
Foroughi, Behzad, Madugoda Gunaratnege Senali, Mohammad Iranmanesh, Ahmad Khanfar, Morteza Ghobakhloo, Nagaletchimee Annamalai, and Bita Naghmeh-Abbaspour. 2023. “Determinants of Intention to Use ChatGPT for Educational Purposes: Findings from PLS-SEM and FsQCA.” International Journal of Human-Computer Interaction 40(17):4501–20. doi: 10.1080/10447318.2023.2226495.
Giray, L., and R. Aquino. 2024. “Use and Impact of ChatGPT on Undergraduate Engineering Students: A Case from the Philippines.” Internet Reference Services Quarterly 28(4):453–62. doi: 10.1080/10875301.2024.2384028.
Ha, Taemin, Hyeonho Yu, Boram Lim, Hoyoon Jung, Collin Brooks, Jennifer Krause, and Brian Dauenhauer. 2024. “Using ChatGPT in the Field of Kinesiology: Opportunities and Considerations.” Journal of Physical Education and Sport 24(1):3–12. doi: 10.7752/jpes.2024.01001.
Habibi, Akhmad, Muhaimin Muhaimin, Bernadus Kopong Danibao, Yudha Gusti Wibowo, Sri Wahyuni, and Ade Octavia. 2023. “ChatGPT in Higher Education Learning: Acceptance and Use.” Computers and Education: Artificial Intelligence 5(December):100190. doi: 10.1016/j.caeai.2023.100190.
Hair, Joe F., Marko Sarstedt, Lucas Hopkins, and Volker G. Kuppelwieser. 2014. “Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool in Business Research.” European Business Review 26(2):106–21. doi: 10.1108/EBR-10-2013-0128.
Hanycz, Shaun A., and Pavel Antiperovitch. 2025. “A Practical Review of Generative AI in Cardiac Electrophysiology Medical Education.” Journal of Electrocardiology 90(February):153903. doi: 10.1016/j.jelectrocard.2025.153903.
Hassan, A. 2023. “The Usage of Artificial Intelligence in Education in Light of the Spread of ChatGPT.” Pp. 687–702 in Contributions to Management Science. Vol. Part F1640.
Hunde, Mekonnen Kenate, Addisalem Workie Demsash, and Agmasie Damtew Walle. 2023. “Informatics in Medicine Unlocked Behavioral Intention to Use E-Learning and Its Associated Factors among Health Science Students in Mettu University , Southwest Ethiopia : Using Modified UTAUT Model.” Informatics in Medicine Unlocked 36:101154. doi: 10.1016/j.imu.2022.101154.
Kaswan, K. S., J. S. Dhatterwal, K. Malik, and A. Baliyan. 2023. “Generative AI: A Review on Models and Applications.” Pp. 699–704 in 2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023.
Kazi, K. S. L. 2024. “ChatGPT: An Automated Teacher’s Guide to Learning.” Pp. 1–20 in AI Algorithms and ChatGPT for Student Engagement in Online Learning.
Klimova, Blanka, and Victor Paiva Luz de Campos. 2024. “University Undergraduates’ Perceptions on the Use of ChatGPT for Academic Purposes: Evidence from a University in Czech Republic.” Cogent Education 11(1). doi: 10.1080/2331186X.2024.2373512.
Lin, Shu Min, Hsin Hsuan Chung, Fu Ling Chung, and Yu Ju Lan. 2023. Concerns About Using ChatGPT in Education. Springer Nature Switzerland.
Mulatiwi, Tri, Didi Supriadi, and Rahmat Mulyanto. 2025. “Implementation of Committee Partnerships on AI-Based School Policies at Public Junior High School.” International Journal of Engineering, Science and Information Technology 5(1):46–50. doi: 10.52088/ijesty.v5i1.627.
Namatovu, Afulah, and Mahadih Kyambade. 2025. “Leveraging AI in Academia: University Students’ Adoption of ChatGPT for Writing Coursework (Take Home) Assignments through the Lens of UTAUT2.” Cogent Education 12(1):2485522. doi: 10.1080/2331186X.2025.2485522.
Ortiz-bonnin, Silvia, and Joanna Blahopoulou. 2025. “ChatGPT Usage in Higher Education Students.” Social Psychology of Education 1–21. doi: 10.1007/s11218-025-10080-2.
Rus, D. 2025. “From Chips to Thoughts: Building Physical Intelligence into Robotic Systems.” Pp. 16–22 in Digest of Technical Papers - IEEE International Solid-State Circuits Conference.
Shahzad, Muhammad Farrukh, Shuo Xu, and Iqra Javed. 2024. “ChatGPT Awareness, Acceptance, and Adoption in Higher Education: The Role of Trust as a Cornerstone.” International Journal of Educational Technology in Higher Education 21:1–24. doi: 10.1186/s41239-024-00478-x.
Sobaih, Abu Elnasr E., Ibrahim A. Elshaer, and Ahmed M. Hasanein. 2024. “Examining Students’ Acceptance and Use of ChatGPT in Saudi Arabian Higher Education.” European Journal of Investigation in Health, Psychology and Education 14(3):709–21. doi: 10.3390/ejihpe14030047.
Strzelecki, Artur. 2023. “Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology.” Innovative Higher Education 49:223–45. doi: 10.1007/s10755-023-09686-1.
Tan, A. A., M. Huda, M. A. Rohim, T. R. R. Hassan, A. Ismail, and M. Siregar. 2025. “Chat GPT in Supporting Education Instruction Sector: An Empirical Literature Review.” Pp. 13–26 in Lecture Notes in Networks and Systems. Vol. 1054 LNNS.
Truong, Thanh Cong, and Quoc Bao Diep. 2023. “Technological Spotlights of Digital Transformation in Tertiary Education.” IEEE Access 11(May):40954–66. doi: 10.1109/ACCESS.2023.3270340.
Venkatesh, Viswanath, Michael G. Morris, Gordon B. Davis, and Fred D. Davis. 2003. “User Acceptance of Information Technology: Toward a Unified View.” MIS Quarterly: Management Information Systems 27(3):425–78. doi: 10.2307/30036540.
Wijaya, Lianna, Cheng Kin Meng, and Rudolf Gruenbichler. 2026. “Post-Pandemic Digital Health in Indonesia: A Dual_Model Study of Task-Technology Fit and UTAUT on Telemedicine Use.” Procedia Computer Science 277:3002–11. doi: 10.1016/j.procs.2026.02.336.
Yu, Chen Wei, Cheng Min Chao, Che Fu Chang, Rueg Juen Chen, Po Chung Chen, and Yi Xuan Liu. 2021. “Exploring Behavioral Intention to Use a Mobile Health Education Website: An Extension of the UTAUT 2 Model.” SAGE Open 11(4):1–12. doi: 10.1177/21582440211055721.
Zacharis, Georgios, and Kleopatra Nikolopoulou. 2022. “Factors Predicting University Students’ Behavioral Intention to Use ELearning Platforms in the Post-Pandemic Normal: An UTAUT2 Approach with ‘Learning Value.’” Education and Information Technologies 27(9):12065–82. doi: 10.1007/s10639-022-11116-2.
Zheng, Hao, Feifei Han, Yi Huang, Yonghe Wu, and Xinyi Wu. 2025. Factors Influencing Behavioral Intention to Use e ‑ Learning in Higher Education during the COVID ‑ 19 Pandemic : A Meta ‑ Analytic Review Based on the UTAUT2 Model. Vol. 30. Springer US.
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