An Integrated Machine Learning Framework for Early Prediction of Student Academic Performance in University Management Systems
Published in The Indonesian Journal of Computer Science, Vol. 15 No. 2 (2026). Applies supervised machine learning — an SVM model with an RBF kernel — to classify over 1,000 students into academic-standing tiers as an early-warning mechanism for university management systems, reaching 96.06% test accuracy.
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