Implementasi Data Mining Naïve Bayes untuk Sistem Peringatan Dini Hasil Belajar Siswa Sekolah Dasar - S, Adyatma Ramadhani; Hilda, Atiqah Meutia; Elly, Muhammad Jafar; Mintarsih, Nani (Jurnal Ilmiah Informatika Komputer, 2025)
This study aims to apply data mining techniques using the Naïve Bayes algorithm to classify student learning outcomes as an early warning system. The classification model was developed using 90 student score records and grouped into two categories, namely “Good” and “Poor”. The experimental results show that the Naïve Bayes model achieved 100% accuracy, precision, and recall. These findings indicate that the proposed model is capable of consistently classifying student learning outcomes and has the potential to serve as a decision support tool for teachers and school administrators.