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All Journal Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Jurnal Teknik Komputer AMIK BSI Jurnal Nasional Komputasi dan Teknologi Informasi INTI Nusa Mandiri Journal of Computer Science and Informatics Engineering Journal of Accounting Information System Jurnal Teknik Informatika dan Teknologi Informasi
Yunita Yunita
Universitas Bina Sarana informatika
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Neuroscience Social Sciences Transportation

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Comparative Analysis of Classification Algorithms for Predicting Student Examination Outcomes Based on Academic Datasets Imam Sugiharto; Sri Indri Wahyuni; Septian Tunijah Faradila; Yunita Yunita; Muhammad Ifan Rifani
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1780

Abstract

Current educational data utilization remains largely focused on final evaluations, resulting in delayed interventions for students at risk of academic failure. This study compares the performance of the Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), and Random Forest algorithms in classifying student examination outcomes as the foundation of an Early Warning System. A total of 6,607 Student Exam Performance records were extracted and processed using Mode Imputation, Label Encoding, and StandardScaler. The experimental results indicate that the SVM model with an RBF kernel achieved the highest accuracy of 76.40%, outperforming Random Forest (73.22%) and K-NN (71.94%). This superior performance is primarily attributed to SVM's ability to construct precise decision boundaries in high-dimensional feature spaces. Therefore, the SVM model is recommended as the primary analytical engine for the early detection of potential academic failure in educational institutions
Co-Authors Achmad Baroqah Pohan Achmad Baroqah Pohan Aliamat Aliamat Amelia Rachma Dita Andini Sahirah Azka Silviya Nita Besus Maula Sulthon Excelcis Novan Solomasi G Hana Khairunnas Hardiyan Hardiyan Hedrolis bago Hilda Amalia Hilda Amalia Ihsan Nur Rahman Imam Sugiharto Mahdiah Amelia Malik Adrianshyah Moranta Timotius Muhammad Ifan Rifani Nur Widia Rachmah Nurfarida Nurfarida Nuruzzahra Syaputri Raditya Ramadhan Al Riyadi Septian Tunijah Faradila Siti Zulaeha Sri Indri Wahyuni Sriyadi Sriyadi Suwanda Aditya Saputra Tessy Wicaksono Ushie Rahmadian Vania Ulfiah Nurfitriany Yuda Yanuar Firmasnyah