Nutritional Status; Infants and Toddlers; LightGBM; Posyandu; Nutrition Prediction; Doko Village; Monitoring Application
Abstract
This study aims to implement a nutritional status index for infants and toddlers in Doko Village, Kediri Regency, using the LightGBM algorithm. Child health issues in Indonesia, particularly stunting, are a serious concern due to chronic malnutrition, recurring infections, and insufficient psychological stimulation during early developmental stages. Doko Village was selected as the research location due to significant challenges related to child nutrition in the area. The LightGBM algorithm was chosen for its ability to process large and imbalanced datasets while providing accurate predictions. The data used in this study comes from weight and height measurements of children at the local Posyandu. The main objective of this research is to develop a predictive model that can help healthcare workers identify children at risk of malnutrition, enabling more precise interventions. Additionally, this study developed a web-based application to monitor nutritional status in real-time, which is expected to improve the quality of life for children in Doko Village and nearby areas facing similar challenges.
Copyright (c) 2023 Muhammad Thoriqulhaq, Mohammad Idhom, Kartika Maulida
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