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All Journal Jurnal Sistem Informasi dan Informatika (SIMIKA)
Nabiel Fauzan Ramadhan
Universitas Pembangunan Jaya
Computer Science & IT Control & Systems Engineering

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APLIKASI PROFILING KEBUTUHAN PELAJARAN TAMBAHAN SISWA SMA MENGGUNAKAN ALGORITMA RANDOM FOREST Nabiel Fauzan Ramadhan; Lathifah Alfat
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 9 No. 1 (2026): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v9i1.4094

Abstract

This study presents EduTrack, a profiling application that uses a Random Forest classifier to identify Indonesian high-school students’ needs for additional Math tutoring. The dataset consists of students’ chapter-wise Math scores, processed with Pandas and Scikit-learn and stored via SQLAlchemy. The backend is implemented in Flask, while the frontend employs Bootstrap with Chart.js for charts and DataTables for tabular display. Dummy evaluation yields model performance around 90% accuracy, with precision 88%, recall 91%, and F1-score 89% (Table 1, Figure 2). Evaluation metric formulas (precision = TP/(TP+FP), recall = TP/(TP+FN), F1 = 2 * precision * recall / (precision + recall)) are included for clarity. EduTrack is designed not only as a predictive tool, but also as a practical decision-support system for teachers. By visualizing student performance at the chapter level, the application enables educators to identify learning gaps more intuitively and implement timely interventions. This helps shift teaching strategies from reactive to proactive, ultimately supporting personalized learning and improving academic outcomes.
Co-Authors Lathifah Alfat