Analisis Resiko Stunting Di Kota Tangerang Menggunakan Metode Regresi Linier dan Support Vector Machine

Abstract

Stunting remains a significant public health issue in Indonesia, particularly in Tangerang City, affecting the physical and cognitive development of children. This problem requires serious attention due to its long-term impacts on children's quality of life and their potential in the future.This study aims to analyze the risk factors contributing to the occurrence of stunting in Tangerang City using Linear Regression and Support Vector Machine (SVM) methods. The research question focuses on identifying and predicting the main risk factors influencing the prevalence of stunting. The research method employs Linear Regression Algorithm and Support Vector Machine Algorithm. The study population consists of children under five years old registered at community health centers in Tangerang City. Data samples were collected from 5,376 children, with 80% (4,300 children) used for training and 20% (1,076 children) for model testing. Several socio-economic and health variables were considered as potential risk factors, including household income, maternal education level, access to clean water and sanitation, dietary diversity, and the presence of antenatal care. Data analysis revealed performance differences between the two models used. The SVM model achieved a significantly higher accuracy of 89% with a standard error of 0.4, demonstrating strong predictive capability. In contrast, the Linear Regression model yielded a lower accuracy of 74% with a standard error of 1.5. This difference highlights the potential advantages of SVM in capturing complex and non-linear relationships within the dataset. These findings can inform targeted interventions and policy recommendations to address the causes of stunting in Tangerang City. Further research could explore a broader range of risk factors.