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All Journal Jurnal Informatika dan Teknik Elektro Terapan Indo-MathEdu Intellectuals Journal Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen Cosmic Jurnal Teknik SISFOTENIKA
Almurozy Mursidan
Teknik Informatika Universitas Indraprasta PGRI
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mathematics

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Journal : Indo-MathEdu Intellectuals Journal

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Klasifikasi Tingkat Prestasi Mahasiswa Pada Mata Kuliah Penambangan Data Menggunakan Naïve Bayes Putri, Basmallah Ramadhani Aisyah; Mursidan, Almurozy; Wardhana, Indra Sari Kusuma
Indo-MathEdu Intellectuals Journal Vol. 7 No. 1 (2026): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v7i1.5050

Abstract

This study aims to classify the academic achievement levels of students in Data Mining courses using the Naïve Bayes algorithm and to evaluate the performance of the resulting classification model. This study uses a quantitative approach with academic data from 190 students, including assignment scores, mid-term exam scores, and final exam scores. The classification process was carried out by applying the Naïve Bayes algorithm, while model evaluation was performed using accuracy metrics, classification reports, and confusion matrices. The test results showed that the Naïve Bayes model produced an accuracy rate of 73.68%. Based on the classification report, classes B and B+ showed the best performance with recall values of 1.00 and f1-scores of 0.87 and 0.95, respectively. Confusion matrix analysis showed that most of the data in classes B and B+ were classified correctly. The results of this study indicate that the Naïve Bayes algorithm is quite effective in classifying students' academic achievement levels and has the potential to be used as an academic evaluation tool in learning decision-making.
Co-Authors -, Dythyaningrum Dermawan, Reyhan Faza Dythyaningrum - Putri, Basmallah Ramadhani Aisyah Rabiati, Suhul Ramdhan, Vickry Suhul Rabiati Wardhana, Indra Sari Kusuma