Support Vector Machine (SVM) For Toddler’s Nutritional Classification in Palu City

Andi Hendra (Department of Information Technology, Faculty of Engineering, Tadulako University, Jalan Soekarno Hatta Km.9 Palu, Central Sulawesi, Indonesia.)
Gazali Gazali (Faculty of Education and Teacher Training, Tadulako University, Jalan Soekarno Hatta Km.9 Palu, Central Sulawesi, Indonesia.)

INSIST (International Series on Interdisciplinary Research)
Vol 1, No 1 (2016)

Abstract—Toddlers are groups who are vulnerable about the health nutrition problems. Nutritional status of children is one of the indicators that can describes the level of social welfare in the city. Nutritionists are the people that can determined the nutritional status. The problem that arises is the limited number of the nutrition experts in each area, this problem causes the children’s malnutrition in the Palu city is detected in very slow condition. The aims of this study is to help the health professionals in the health centers or the hospitals to determine the children’s nutritional status computerized, so the malnutrition problem in the Palu city can be detected earlier. Besides that, to help the government in policy making about nutrition of the toddlers in Palu city. This study uses a Support Vector Machine (SVM) which implemented in computer-based software application to analyze nutrition of the toddlers.Keywords—Nutrition, Software, Support Vector Machine (SVM), Toddlers, Palu city.