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All Journal Jurnal Riset dan Inovasi Pembelajaran
Muhammad Haris
Information Technology Study Program, Faculty of Computer Science and Information Technology, Universitas Muhammadiyah Sumatera Utara, Medan, Indonesia
Chemistry Education Languange, Linguistic, Communication & Media Mathematics Other

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Predicting High School Student Interest in Private Universities Using Markov Chains and Data Mining Hevlie Winda Nazry S; Muhammad Haris; Fatma Sari Hutagalung
Jurnal Riset dan Inovasi Pembelajaran Vol. 6 No. 2 (2026): May - August 2026
Publisher : Education and Talent Development Center Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/jrip.v6i2.5696

Abstract

This study examines senior high school (SMA) students interest in attending private universities in Medan using an Educational Data Mining (EDM) approach. A first-order Markov chain model integrated with data mining techniques maps transitions among five states (Exploration, Consideration, Application, Re-enrollment, and Non-PTS migration) of student preferences. A stratified random sample of 2,850 SMA students was surveyed with a 20-item Likert questionnaire, and secondary historical enrollment data were used. K-Means clustering and decision tree algorithms were applied for data preprocessing and feature extraction. The Markov model achieved 89.47% accuracy, 88.20% precision, 90.15% recall, and an RMSE of 0.0824. The steady-state projection indicates 52.09% of students eventually enroll in private universities (PTS) while 47.79% go to public universities (PTN) or other non-PTS pathways; the remaining ~0.12% probability is distributed across the other three states, confirming that the 52.09% and 47.79% outcomes are dominant. These results have practical implications for private university policymakers in formulating data-driven recruitment strategies and mitigating the “leaky pipeline” of applicants.
Co-Authors Fatma Sari Hutagalung Hevlie Winda Nazry S