Implementasi Metode Naive Bayes untuk Klasifikasi Kondisi Gizi Balita - Febriansyah, Febriansyah (Teknik Informatika Universitas Pamulang, 2024)
The determination of a toddler's nutritional status involves calculating weight and height based on age. Naïve Bayes is a machine learning algorithm for classification problems in data mining that utilizes probability mathematics (also known as Bayes' theorem) to distinguish between different classes. This system is designed to facilitate the nutrition staff at the Pajar Bulan Village Health Center in more accurately storing data and automatically determining the nutritional status of toddlers. The system is developed using the Rapid Application Development (RAD) method, which comprises three phases: requirements planning, design workshop, and implementation. The classification system for toddler nutritional status using the Naive Bayes algorithm aims to provide more accurate information to address malnutrition in toddlers. The data processing with the Naive Bayes algorithm results in the development of a system for classifying the nutritional status of toddlers at the Pajar Bulan Village Health Center.