Abstract: The emergence of data mining techniques has encouraged researchers to attempt to apply them in the educational sector to discover knowledge from the students' data available to higher institutions of learning. This research work aims to develop a hybrid model that predicts academic performance based on admission pattern, thereby assessing the effectiveness of selected algorithms using metrics like Accuracy, Precision, Recall, and F1 Score. The study......
Keywords—Decision tree, Random forest, K-Nearest Neighbors, Academic performance, Hybrid Algorithm
[1].
Aman, F., Rauf, A., Ali, R., Iqbal, F., & Khattak, A. M. (2019, July). A predictive model for predicting students academic performance. In 2019 10th International conference on information, intelligence, systems and applications (IISA) (pp. 1-4). IEEE.
[2].
Baek, C., & Doleck, T. (2022). Educational data mining: A bibliometric analysis of
[3].
an emerging field. IEEE Access, 10, 31289-31296.
[4].
Cruz, M. E. L. T., & Encarnacion, R. E. (2021). Analysis and prediction of students'
[5].
academic performance and employability using data mining techniques: A research travelogue. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 16, 117-131.
