Muhammad Lutfi
Universitas Kebangsaan Republik Indonesia

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Klasifikasi Status Gizi Balita Menggunakan Naïve Bayes Classification di Kelurahan Padasuka Ciomas Bogor Muhammad Lutfi; Nana Suryana; Isep Saepudin; Adam Husain; Sri Handayani
Journal Data Science, Technology, Informatics and Security Vol 3 No 1 (2025): Journal Data Science, Technology, Informatics and Security (Juni 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i1.4265

Abstract

Life is characterized by symptoms of growth and development. The health status of each individual is different. In this case, one of the efforts to improve health status is to improve nutritional status. Nutritional status is a state of the body related to food consumption patterns and the use of nutrients that are tailored to the body's needs. Improving nutritional status is useful for increasing body resistance and making normal growth. In actualizing the daily nutritional status of children under five at the posyandu, it is usually obtained through anthropometric measurements, namely by using the BW/U index or body weight compared to age to determine nutritional status. However, in anthropometric measurements, it was found that there was confusion in the determination of nutritional quality, so that in order to get accurate results, a data mining method was needed, namely the Naive Bayes Classification (NBC) Algorithm which would be implemented in the study. This research is expected to help posyandu cadres in Padasuka sub-district, Ciomas sub-district, Bogor district in determining the nutritional status of toddlers better and more accurately.