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Febriansyah .
Institiut Teknologi Pagar Alam
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Journal : Jurnal Informatika Universitas Pamulang

 1 
Implementasi Metode Naive Bayes untuk Klasifikasi Kondisi Gizi Balita Febriansyah, Febriansyah
Jurnal Informatika Universitas Pamulang Vol 9 No 2 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v9i2.39676

Abstract

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.
Co-Authors Abdi NAsrullah Anggriani, Yesi Pitaloka Anggun Budiastuti Arif, Alfis Asep Syaputra Asep Syaputra Dedi Setiadi Donny Oktavianus, Donny Edowinsyah Efan Efan Fenny Etrawati Hamzah Hasyim Inda Anggraini Indah Yuliana Intan Juwita Kasman Kasman Kasman Lesi Anggraini Muntari, Siti Nanda S. Prawira Nasrullah, Abdi Nely Murniati Rahmatillah Razak Sasmita Sasmita Syerina Raihatul Jannah Tri Susanti Tri Susanti Widya Lionita