<![CDATA[Acute Respiratory Infection (ARI) is a health issue characterized by an uneven distribution of cases across Luwu Regency; consequently, regional grouping is required to assist in prioritizing management efforts. This study aims to classify the distribution of ARI cases using the K-Means Clustering method and to visualize the results via an ArcGIS Online-based digital map. A quantitative method with a spatial-descriptive approach was employed, utilizing data on the number of ARI cases across 22 districts in Luwu Regency from 2023 to 2025, obtained from the Luwu Regency Health Office. The research process involved data collection and processing, the determination of three clusters (low, medium, and high) using the K-Means method, and the visualization of clustering results through ArcGIS Online. The findings demonstrate that the K-Means method effectively grouped districts into three categories based on the similarity of ARI case counts, while ArcGIS Online successfully presented an interactive digital map that facilitates the identification of the spatial distribution of ARI cases. Thus, the developed system provides easily understandable spatial information and supports monitoring, decision-making, and the formulation of ARI management strategies in Luwu Regency.]]>
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