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All Journal JUTIK : Jurnal Teknologi Informasi dan Komputer
Taqiyuddin Ahmad Al Aufa
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Social Sciences

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ANALISIS ADOPTION RATE PENGGUNAAN MICROSOFT COPILOT DALAM KEGIATAN AKADEMIK MAHASISWA SURABAYA MENGGUNAKAN METODE EXTENDED TAM Achmad Naufal Ferdiansyah; Taqiyuddin Ahmad Al Aufa; Ahmad Faiq Shalahuddin Wafa
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.3968

Abstract

The advancement of artificial intelligence (AI) technology has introduced Microsoft Copilot as a supportive tool for students' academic activities. This study aims to analyze the factors influencing the adoption rate of Microsoft Copilot Bing among university students in Surabaya using the Extended Technology Acceptance Model (Extended TAM). A quantitative approach was employed through a Likert-scale questionnaire distributed to 100 purposively selected respondents. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software. The findings reveal that Attitude Toward Use Copilot serves as a central mediator that significantly affects Intention to Use Copilot. Key predictors influencing this attitude include Perceived AI Enjoyment, Usefulness, and Intelligence. However, Perceived AI Trust and Personal Competence did not show a direct significant effect on users’ attitudes. To address discriminant validity issues, a model refinement process was conducted by simplifying overlapping indicators. The results highlight the importance of enjoyable user experiences, perceived usefulness, and AI intelligence in shaping students’ intention to adopt the technology. This research provides practical implications for technology developers and educational institutions in designing strategies to integrate AI-based tools effectively in academic environments.
Co-Authors Achmad Naufal Ferdiansyah Ahmad Faiq Shalahuddin Wafa