Multidimensional Log-Linear Modeling (Case Study: Gender, Age, Head Circumference, and Nutritional Status Among Early Childhood Children) - Yoka, Ranara Athalla; Usman, Mustofa; Chasanah, Siti Laelatul; Widiarti; Handayani, Vitri Aprilla (Integra: Journal of Integrated Mathematics and Computer Science, 2025)
Poor nutritional status tends to increase the risk of morbidity and mortality among children in developing countries. Therefore, data on these rates can be an important indicator in describing the condition of undernutrition in a community. Log-linear model analysis can be used to categorize data on nutritional status. Based on data obtained from the Rajabasa Indah Health Center area, Rajabasa Subdistrict, Bandar Lampung City, there are 418 children who have examined at the Posyandu. The analysis model conducted in this study involves four variables, each variable is categorized into several categories according to predetermined criteria. Gender with two categories (male and female), age with two categories (1-12 months and 13-60 months), head circumference with two categories (normal and abnormal), and nutritional status with three categories (undernourished, well-nourished, and overnourished). This study aims to determine the best model using log-linear analysis that can explain the relationship between the four variables. The results obtained are the best model for the data involved in the [UG][LG][J] structure, the structure describes the interaction between age and nutritional status and head circumference and nutritional status.