Penerapan Metode Naïve Bayes Untuk Mendeteksi Secara Dini Stunting Pada Balita
DOI:
https://doi.org/10.29408/jit.v8i2.30385Keywords:
Naive Bayes, Stunting, Rapidminer, K-Nearest Neighbor, ToddlersAbstract
This study focuses on early detection of stunting in toddlers at integrated health service posts (posyandu) in the Paninggilan Utara Ciledug Tangerang area using the Naive Bayes method. Stunting is a chronic nutritional problem that arises due to prolonged malnutrition. Early detection of stunting in toddlers is very important because it can have an impact on the growth and development of toddlers in the long term. The study used a dataset of 250 toddler records collected randomly from 17 posyandus in the Paninggilan Utara Ciledug Tangerang area. Toddlers were divided into three age groups: Group A (0-11 months), Group B (12-35 months), and Group C (36-59 months). The Naive Bayes method, which is a statistical classification technique, is used to detect early the possibility of stunting in infants under five years old. So that earlier medical action can be given to overcome the stunting condition. The results of the study showed that the Naive Bayes method obtained a higher accuracy of 94.80% compared to the K-Nearest Neighbor (KNN) method which had an accuracy of 85.80%. The high accuracy and speed of the Naive Bayes method make it a suitable tool for screening and early detection of stunting in toddlers
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