Stunting Risk Factor Analysis Using Seemingly Unrelated Regression (SUR) Integrated with Machine Learning - Wiyanti, Wiwik; Zenklinov, Amanatullah Pandu; Seleki, Jacob Stevy; Ramadhani, Sausan; Jimy, Valensius; Arifin, Samsul (Jurusan Matematika FMIPA UNM, 2025)
Stunting is a disorder in children caused by chronic nutritional problems. Stunting is usually characterized by a child’s failure to grow and develop optimally. In Indonesia, the government is focusing on addressing of stunting case, as it aims to develop the superior of human resources. In Tangerang regency is currently holding a “Gebrak Tegas” program to address the problem of stunting. The causes of stunting required scientific study to help the government understand the scientific factors that causing stunting. Therefore, this study aims to analyze the factors causing stunting the children in the Tangerang regency. The data analysis method in this study use the Seemingly Unrelated Regression (SUR), which is integrated with a machine learning, namely Random Forest. The data used in this study were obtained from primary data through questionnaires. The subjects of this study were parents of stunting and non-stunting children who were at “Posyandu” under of “Kelapa dua” and “Binong” health centers. Sampling method in this study is purposive-random sampling. The results of the data analysis showed that the five variables from the factors measured had the most significant influence, namely nutritional, socio-economi, and pregnancy and childbirth history factors. Five variables that influence children stunting are animal protein, which has the highest probability of 87.5% when the children consumes protein once or twice a week. The children consume vitamin A twice has a 97% probability. The source of income for the parents, whether from the private or self-employment, has a probability of over 90%. Furthermore, the consumption of iron-boosting tablets by mother during pregnancy and the amount of income from the parents have a probability of 84%.