2024
DOI: 10.1051/bioconf/202414601082
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Multiclass classification of toddler nutritional status using support vector machine: A case study of community health centers in Bangkalan, Indonesia

Muhammad Ali Syakur,
Adz Dzikry Pradana Putra,
Eka Mala Sari Rochman
et al.

Abstract: Monitoring child development is vital in Indonesia due to its large child population and varying socio-economic and geographical conditions. Malnutrition adversely affects children's growth and development, with ongoing challenges in remote areas despite government efforts. This study addresses the need for accurate nutritional status classification to improve intervention strategies. This study applies the Support Vector Machine (SVM) classification method to analyze and classify nutritional status of toddler… Show more

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