| Autor: |
Syakur Muhammad Ali, Putra Adz Dzikry Pradana, Rochman Eka Mala Sari, Mufarrohah Fifin Ayu, Husni, Asmara Yuli Panca, Rachmad Aeri |
| Jazyk: |
English<br />French |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
BIO Web of Conferences, Vol 146, p 01082 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2117-4458 |
| DOI: |
10.1051/bioconf/202414601082 |
| Popis: |
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 toddlers using data from 473 samples collected from health centers in Bangkalan Regency. The classification includes categories such as Good Nutrition, Excess Nutrition, Obesity, and Risk of Excess Nutrition. The SVM model achieved an accuracy of 76% in predicting nutritional status. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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