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All Journal Jurnal Penelitian Pendidikan
Putra, Anggy Trisnawan
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Prediction of Blood Sugar Levels in Type 2 Diabetes Mellitus Patients Based on Diet and Medication Compliance Using Naive Bayes and BAT Algorithms Dewi, Meilina Taffana; Putra, Anggy Trisnawan
Jurnal Penelitian Pendidikan Vol. 42 No. 2 (2025): October 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpp.v42i2.32305

Abstract

Type 2 diabetes mellitus poses a significant global health especially in Indonesia  challenge, primarily due to patient non-adherence and limited monitoring. Therefore,  technology-based approaches play a crucial role in detecting potential blood sugar  elevations early, enabling faster and more targeted interventions. This study introduces an integrated predictive framework that combines a Naive Bayes classification algorithm with a Bat-inspired metaheuristic (BAT) for automated feature selection. Optimized by the BAT algorithm, the system achieved high performance: 95% accuracy, 0.94 precision, 0.96 recall, 0.95 F1 score, and 0.90 Cohen's Kappa, indicating near-perfect agreement with actual outcomes. These results confirm the potential of the Naive Bayes and BAT approaches as reliable clinical decision support tools for proactive diabetes management.
Co-Authors Dewi, Meilina Taffana