Sistem Pakar Berbasis Web untuk Diagnosis Stunting pada Balita Menggunakan Metode Naïve Bayes
DOI:
https://doi.org/10.30865/jurikom.v13i2.9130Keywords:
Diagnosis, Expert System, Flask, Naïve Bayes, StuntingAbstract
Stunting is a health problem caused by chronic malnutrition that affects children's physical growth and cognitive development. This condition has become a serious concern because it impacts the quality of human resources in the future. This study aims to develop an expert system for diagnosing Stunting using the Naïve Bayes method to assist healthcare workers in the early detection of at-risk toddlers. The research data were obtained from Posyandu in Babul Makmur District, Southeast Aceh Regency, consisting of 170 training data and 30 testing data. The system was developed using the Python programming language with the Flask framework and SQLite database. The input variables consisted of seven symptoms (G01–G07), including age, weight, height, gender, and other supporting factors. The testing results showed that the Naïve Bayes method achieved an accuracy of 86.66%, with 26 out of 30 test data correctly classified according to expert diagnoses. This system can be used as a decision-support tool for healthcare workers to accelerate diagnosis and improve the effectiveness of Stunting management, particularly in areas with limited healthcare resources.
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