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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Bulletin of Computer Science Research Jurnal Ilmu Komputer Journal of Information System, Technology and Engineering
Ibrahim, Irawan
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Computer Science & IT

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Journal : Bulletin of Computer Science Research

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Penerapan Algoritma Naive Bayes Untuk Sistem Klasifikasi Status Gizi Bayi Balita Abas, Mohamad Ilyas; Lamusu, Rizal; Pranata, Widya Eka; Syahrial, Syahrial; Ibrahim, Irawan; Hasyim, Wahyudin; Kiayi, Verliana
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.508

Abstract

Infants and toddlers are in a critical period of rapid growth and development, often referred to as the "golden age." During this stage, regular nutritional assessments are essential to monitor health status and detect potential nutritional problems early. This study aims to classify the nutritional status of infants and toddlers using the Naïve Bayes algorithm, a probabilistic classification method based on Bayes' theorem with a strong assumption of attribute independence. The main attributes used in the classification system include age, weight, and height. The dataset consists of 700 records of infants and toddlers collected from previous observations. The results show that the Naïve Bayes algorithm can be effectively implemented for nutritional status classification, achieving a system accuracy of 88.14%. This indicates that the method performs well and has the potential to be utilized in decision support systems for child health monitoring.
Co-Authors Daulima, Mohamad Rizki Ghani, Hilmasyah Gobel, Alvian Van Handayani, Tri Pratiwi Hasyim, Wahyudin Kango, Riklan Kiayi, Verliana Lamusu, Rizal Lasaruddin, Alter Lestari, Gita Maku, Rubiyanto Mohamad Ilyas Abas Poha, Rahmad A Pranata, Widya Eka SYAHRIAL SYAHRIAL Syahrial Syahrial Umar Sako, Umar