Prediction of Stunting Children Based on Parental Conditions Using Support Vector Machine Method With Case Study in Tabanan Regency-Bali
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Abstract
Stunting is one of the nutritional problems faced by children in the world. Stunting is a condition where the child's height is below the established standard and is a chronic nutritional problem caused by food intake that is not in accordance with nutritional needs. The state of Indonesia has a high commitment to preventing stunting so that Indonesian children can grow and develop optimally accompanied by ready emotional, social and physical abilities. to learn. This effort is shown through the National Strategy for the Acceleration of Stunting Prevention or known as Stranas Stunting, which will be implemented in 2018-2024. Tabanan Regency is one of the priority cities in the 2020 Stranas Stunting program. To give a good and efficient result, the researchers conducted research on how to predict stunting children based on the condition of their parents using the Support Vector Machine method. In this study, the data used is data from the Tabanan district office where the data is 300 data consisting of 22 variables tested with 3 kernel models from the Support Vector Machine to find the highest accuracy. In this study, The trial was carried out 15 times with Matlab and the highest accuracy value was obtained using 18 variables from a total of 22 variables of 0.9889 or 98.89%, and the kernel with the highest accuracy was using a polynomial.
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