Predicting Nutritional and Physical Stunting in Malang District: A Hybrid Model of Logistic Regression and Support Vector Machine Approaches

A toddler’s growth can be assessed in two aspects: nutritional status and physical status. On the physical side, stunting is a condition in which height is not in accordance with age. In this study, a hybrid bi-response model combining logistic regression (LR) and a support vector machine (SVM) was developed to assess its performance in classifying toddler status in Wajak Village, Malang Regency. The data used in this study were primary data collected from questionnaires completed by mothers of toddlers. The response variables in this study consist of two: nutritional status and physical stunting status in toddlers. The method used was a hybrid bi-response model combining LR and an SVM, both of which are supervised learning methods. This study found that hybrid LR and the SVM bi-response performed better at classifying data with two response variables than LR or an SVM alone with an accuracy of 94.43%, sensitivity of 92%, and specificity of 94.38%.