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All Journal JASa (Jurnal Akuntansi, Audit dan Sistem Informasi Akuntansi)
Huey, Kan Wen
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Computer Science & IT Economics, Econometrics & Finance

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Integration of Artificial Intelligence and Data Mining in Accounting Information Systems for Analysis of New Student Uptake Patterns: An Open University Case Study Paramitha, Diky; Riyani, Etik Ipda; Huey, Kan Wen
JASa (Jurnal Akuntansi, Audit dan Sistem Informasi Akuntansi) Vol. 10 No. 1 (2026): April
Publisher : Program Studi Akuntansi Universitas Langlangbuana Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36555/jasa.v10i1.2992

Abstract

Increased enrollment of new students is an important measure of the university's ability to meet the needs of Education. To remain relevant and competitive, institutions are increasingly expected to incorporate artificial intelligence (AI) technologies that improve data-driven decision-making. The combination of data mining methods and Accounting Information Systems, which utilize computational techniques to analyze vast data sets can reveal hidden patterns. This study investigates the application of artificial intelligence in creating a direct data mining tool that aims to identify trends in new student enrollment at the Open University. Using a research and development approach, the study examined admissions data from 2022 to 2024 to uncover underlying patterns and significant factors influencing enrollment dynamics. The results show that AI-integrated applications significantly improve the efficiency of data analysis while improving the reliability and usability of institutional data for strategic purposes. The study contributes to a larger conversation about how aligning AI implementation with institutional goals can drive innovation, accountability, and responsiveness in the context of open and distance learning. In summary, the findings imply that incorporating AI into data management and development processes provides greater clarity regarding future trends, making AI a powerful forecasting and decision-making resource for higher education institutions.
Co-Authors Etik Ipda Riyani Etik Ipda Riyani, Etik Ipda Riyani Paramitha, Diky