<![CDATA[Stunting is a chronic nutritional problem that impacts children's physical growth and development and is a public health challenge in Indonesia. This study integrates Exploratory Data Analysis (EDA) and K-Modes Clustering to map the nutritional status of toddlers in stunting cases in Asahan Regency. EDA was used to explore data distribution, identify relationships between nutritional status indicators, and identify risk factor patterns, while K-Modes was used to group toddlers based on shared categorical characteristics. The dataset used included sociodemographic variables (gender, age category, parental education and occupation) and nutritional status indicators (weight/age, height/age, weight/height). The analysis results showed a moderate positive correlation between weight/age and height/age (0.32) and a strong negative correlation between weight/age and weight/height (-0.50), indicating a link between stunting and wasting. The application of K-Modes resulted in three main clusters: Cluster 0, dominated by female toddlers with normal nutritional status but low parental education; Cluster 1 consists of infant girls with low weight for age and short height for age, despite most parents having a high school education; Cluster 2 contains infant boys with very low weight for age and very short height for age, and relatively low maternal education. The profile of each cluster was analyzed to identify dominant characteristics relevant for intervention. This integrative approach demonstrates that the combination of EDA and K-Modes is able to provide a comprehensive picture of variations in toddler nutritional status, thus serving as a basis for planning more targeted promotive and stunting prevention strategies at the regional level.]]>
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