PENERAPAN METODE NAIVE BAYES UNTUK KLASIFIKASI STATUS GIZI BALITA

Abdul Aziz; Mhd Furqan; M. Fakhriza

doi:10.46576/syntax.v5i2.5568

PENERAPAN METODE NAIVE BAYES UNTUK KLASIFIKASI STATUS GIZI BALITA

Abdul Aziz, Mhd Furqan, M. Fakhriza

Abstract

Stunting is a serious condition that affects the growth and development of children due to malnutrition and repeated infections, which results in delayed physical growth, decreased cognitive abilities, and decreased immunity. The problem of stunting is a top priority in the field of public health in Indonesia. This study aims to design an Android-based application that can monitor the nutritional status of toddlers using the Naive Bayes method, which is known to be effective in classifying data based on probability. Monitoring focuses on preventing stunting through analysis of weight, height, age, and gender parameters. The application developed functions as a tool for health workers and integrated health posts in monitoring the nutritional status of toddlers more efficiently and accurately. By using input data such as date of birth, gender, weight, and height, this application is able to identify the nutritional status of children, whether they are normal, malnourished, or overweight. This system functions in real-time and is built with the Java programming language. The data used in this study are gender, age, height, and weight derived from monitoring the nutritional status of toddlers at the Puskesmas Kecamatan Sinunukan, Kabupaten Mandailing Natal. The data obtained from this study amounted to 100 data points. The evaluation results show that the system is able to classify stunting data based on 3 classes, namely "normal nutrition", "undernutrition", and "overnutrition" with an accuracy of 90%.

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DOI: https://doi.org/10.46576/syntax.v5i2.5568