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Analysis of the Potential for Plagiarism Among Master's Students in Accounting at XYZ University in the Era of Artificial Intelligence: A Fraud Diamond Model Perspective Andrianus Andrianus
Interdisciplinary Social Studies Vol. 5 No. 3 (2026): Interdisciplinary Social Studies
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/iss.v5i3.1147

Abstract

The rapid advancement of artificial intelligence (AI) has transformed higher education by providing students with powerful tools to support academic writing, information retrieval, and learning activities. While AI enhances efficiency and productivity, it also raises significant concerns regarding academic integrity, particularly with respect to the increasing potential for plagiarism. This study aims to analyze the potential for plagiarism among Master of Accounting students at XYZ University in the era of artificial intelligence through the Fraud Diamond framework, which comprises four dimensions: pressure, opportunity, rationalization, and capability. A qualitative case study approach was employed, involving nine Master of Accounting students as primary informants and several lecturers as supporting informants. Data were collected through semi-structured interviews, analyzed using thematic analysis and pattern matching, and validated through source triangulation. The findings reveal that all four Fraud Diamond dimensions contribute to the potential for AI-assisted plagiarism. Academic pressure emerged as the most influential factor, followed by opportunity, which is created by limited AI detection capabilities and inconsistent academic supervision. Rationalization was reflected in students' perceptions of AI as a legitimate academic aid, while capability was associated with digital literacy and technical competence in the utilization of AI tools. The study concludes that AI is not the primary cause of plagiarism but rather an enabling technology that amplifies pre-existing academic misconduct risk factors. Accordingly, universities should strengthen academic integrity policies, improve AI literacy, establish clearer ethical guidelines, and develop more effective AI governance frameworks to promote the responsible use of artificial intelligence in higher education.