<![CDATA[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.]]>
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