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All Journal INFORMATIKA KOMMAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Penelitian Ilmu komputer AMMA : Jurnal Pengabdian Masyarakat APPA : Jurnal Pengabdian Kepada Masyarakat
Meidy Fajar Wahyu
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Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing

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Journal : INFORMATIKA

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IMPLEMENTASI ALGORITMA NAIVE BAYES UNTUK PROGRAM CEGAH STUNTING (STUDI KASUS: PUSKESMAS BOJONGSARI DEPOK) Asha Riska Amalia; Meidy Fajar Wahyu
Informatika: Jurnal Teknik Informatika dan Multimedia Vol. 5 No. 2 (2025): Oktober : JURNAL TEKNIK INFORMATIKA DAN MULTIMEDIA
Publisher : LPPM Politeknik Pratama Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/informatika.v5i2.1378

Abstract

Stunting in toddlers remains a major public health challenge in Indonesia as it has long-term impacts on children’s growth and quality of life. Manual detection through community health posts often requires considerable time, is prone to errors, and lacks practical tools that can be independently used by the community. This study aims to develop an application based on the Naïve Bayes algorithm to support early detection of stunting risk among toddlers in the Bojongsari Community Health Center, Depok. The research employed a quantitative descriptive approach using the CRISP-DM method, involving data collection of children aged 0–59 months through observation, interviews, and documentation, followed by data cleaning, modeling with Naïve Bayes, and evaluation based on accuracy. The results indicate that the application successfully classifies toddlers’ nutritional status into normal or stunting categories with good accuracy, while providing a simple and user-friendly interface for independent use. The findings conclude that the implementation of the Naïve Bayes algorithm is effective in accelerating stunting risk detection and enhancing community participation in prevention efforts, which ultimately contributes to more efficient health services and reduced stunting prevalence.   
Co-Authors Amin Hidayat Amin Hidayat Amin Hidayat Asha Riska Amalia Lely Andriyanto Lely Panca Andriyanto nanang nanang Nanang Nanang Ripal, Muhammad Riski Yuda Samudra