TINGKAT SOCIAL INFLUENCE DAN KUALITAS INFORMASI DALAM PENGGUNAAN ARTIFICIAL INTELLIGENCE-CHATBOT
Abstract
ABSTRAK
Artificial Intelligence (AI) berkembang pesat dan memainkan peran penting dalam dunia pendidikan. Penelitian ini bertujuan untuk mengetahui tingkat dari social influence dan kualitas informasi terhadap penggunaan chatbot AI. Penelitian ini menggunakan metode kuantitatif dengan pendekatan deskriptif. Populasi pada penelitian ini adalah guru Sekolah Menengah Atas se-Surakarta. Penelitian ini menggunakan teknik random sampling dengan jumlah sampel 110 guru. Pengumpulan data dilakukan melalui angket kuesioner, sedangkan analisis data menggunakan metode Structural Equation Modeling (SEM) berbasis Partial Least Squares (PLS). Hasil penelitian menunjukkan bahwa guru memiliki tingkat penerimaan yang tinggi terhadap penggunaan chatbot AI dalam pembelajaran. Selain itu, temuan penelitian mengindikasikan bahwa social influence memberikan pengaruh signifikan terhadap penggunaan chatbot AI dan kualitas informasi juga terbukti berperan signifikan dalam mendorong penggunaan chatbot AI pada konteks pendidikan.
Kata Kunci: Social Influence; Kualitas informasi; Penggunaan Chatbot AI
ABSTRACT
Artificial Intelligence (AI) is rapidly developing and plays a significant role in education. This study aims to determine the level of social influence and information quality on the use of AI chatbots. This study uses a quantitative method with a descriptive approach. The population in this study were high school teachers in Surakarta. This study used a random sampling technique with a sample size of 110 teachers. Data collection was carried out through questionnaires, while data analysis used the Structural Equation Modeling (SEM) method based on Partial Least Squares (PLS). The results show that teachers have a high level of acceptance of the use of AI chatbots in learning. Furthermore, the research findings indicate that social influence has a significant influence on the use of AI chatbots, and information quality has also been shown to play a significant role in encouraging the use of AI chatbots in educational contexts.
Keywords: Social Influence; Information Quality; Use of AI Chatbot
Keywords
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Abdalla, R. A. M. (2024). Examining awareness, social influence, and perceived enjoyment in the TAM framework as determinants of ChatGPT. Personalization as a moderator. Journal of Open Innovation: Technology, Market, and Complexity, 10(3).
Almulla, M. A. (2024). Investigating influencing factors of learning satisfaction in AI ChatGPT for research: University students perspective. Heliyon, 10(11).
Bilquise, G., Ibrahim, S., & Salhieh, S. M. (2024). Investigating student acceptance of an academic advising chatbot in higher education institutions. Education and Information Technologies, 29(5), 6357–6382.
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75.
Camilleri, M. A. (2024). Factors affecting performance expectancy and intentions to use ChatGPT: Using SmartPLS to advance an information technology acceptance framework. Technological Forecasting and Social Change, 201.
Çelik, K., & Ayaz, A. (2022). Validation of the Delone and McLean information systems success model: a study on student information system. Education and Information Technologies, 27(4), 4709–4727.
Changalima, I. A., Amani, D., & Ismail, I. J. (2024). Social influence and information quality on Generative AI use among business students. International Journal of Management Education, 22(3).
Cokins, G., Oncioiu, I., Türkes, M. C., Topor, D. I., Capusneanu, S., Pastiu, C. A., Deliu, D., & Solovastru, A. N. (2020). Intention to use accounting platforms in romania: A quantitative study on sustainability and social influence. Sustainability (Switzerland), 12(15).
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.
Harnawati, H., & Hidayati, U. (2024). Persepsi Mahasiswa Calon Guru Matematika terhadap Pemanfaatan Teknologi Kecerdasan Buatan dalam Konteks Pembelajaran. JagoMIPA: Jurnal Pendidikan Matematika Dan IPA, 4(1), 50–59.
Hasan, M. R., Chowdhury, N. I., Rahman, M. H., Syed, M. A. Bin, & Ryu, J. (2024). Understanding AI Chatbot adoption in education: PLS-SEM analysis of user behavior factors. Computers in Human Behavior: Artificial Humans, 2(2).
Jami Pour, M., Mesrabadi, J., & Asarian, M. (2022). Meta-analysis of the DeLone and McLean models in e-learning success: the moderating role of user type. Online Information Review, 46(3), 590–615.
Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024). Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students. Computers and Education: Artificial Intelligence, 6.
Lee, S. W., Sung, H. J., & Jeon, H. M. (2019). Determinants of continuous intention on food delivery apps: Extending UTAUT2 with information quality. Sustainability (Switzerland), 11(11).
Sekretariat GTK. (2018). 40 Persen Guru yang Siap dengan Teknologi. Gtk.Kemendikbud.Go.Id.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. In Source: MIS Quarterly, 27(3).
DOI: https://doi.org/10.31932/ve.v16i2.5294
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