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All Journal Eksplorasi Teknologi Enterprise & Sistem Informasi (EKSTENSI)
Rusina Widha Febriana
Universitas Anwar Medika
Computer Science & IT

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Sistem Prediksi Risiko Stunting Menggunakan Bayesian Network Berbasis GIS Rusina Widha Febriana; Endang Setyati
Eksplorasi Teknologi Enterprise & Sistem Informasi (EKSTENSI) Vol. 1 No. 1 (2022): November
Publisher : FIKOM - Bung Karno University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (595.934 KB) | DOI: 10.59039/ekstensi.v1i1.2

Abstract

Stunting is one of the nutritional issues faced in the world. Stunting is a chronic nutritional problem caused by food intake that does not suit nutritional needs. Indonesia has a high commitment to stunting prevention efforts so that Indonesian children can grow and develop optimally and innovate and compete at the global level. The effort was demonstrated through the National Strategy of accelerating Stunting Prevention, known as Stranas Stunting, implemented in 2018 – 2024. The system was developed to be able to identify stunting supporting factors so that it can provide accurate information. And the system also displays data in the form of maps, to make it easier to perform analysis in a room. Spatial data is displayed using GIS (Geographic Information System). The study's result was that 75% of children grew up normally, while the other 25% predicted to suffer from stunting. The dominant factor affecting stunting is 57% of children with short anthropometry, 51% of children who do not get exclusive breast milk, 66% of mothers' knowledge of nutrition is not good, 69% of foster care patterns by mothers themselves, 80% of pregnant women with a diet less than three times, 99% of pregnant women not infected with the disease, and 54% of pregnant women with anthropometry less than mid-upper arm circumference (MUAC).
Co-Authors Endang Setyati