IMPLEMENTATION ON STUNTING DATA CLUSTERING OF TODDLERS USING K-MEDOIDS CLUSTERING ALGORITHM

Abstract

The state of chronic malnutrition in toddlers as measured by the World Health Organization (WHO) standard in 2005, based on height for age, which is a combination of short and very short terms with a Z-score <- 2 standard deviations. The results of the Indonesian Nutrition Status Study (SSGI) of the Ministry of Health show that 24.5% of infants under 5 years old (toddlers) in West Java will experience stunting in 2021. Nearly a quarter of toddlers whose height is below the standard for their age. The data used in this study were obtained from the Ministry of Home Affairs' Bangda Action by monitoring the implementation of 8 convergence actions for stunting reduction interventions. The direction of this research refers to grouping data on the distribution of the number of stunting in the Regency and City of Cirebon based on data collection results in 2022. In this study, the data were processed by applying the K-Medoids clustering algorithm or called Partitioning Around Medoids (PAM) by using the partition clustering method for grouping a set of n objects into several k clusters. From the results of grouping with 3 clusters, the DBI value was -2.427, wherein in the high-level stunting cluster there were 102 villages. In contrast, the medium-level percentage cluster was 103 villages, and the low-level stunting percentage cluster was 241 villages. This research is expected to provide information to the government regarding the classification of stunting under five so that it can determine which villages still need treatment in reducing stunting.