ANALISIS POLA PERSEBARAN HIPERTENSI DI SUMATERA UTARA DENGAN MENGGUNAKAN ALGORITMA K-MEANS

The fluctuating spread of hypertension requires accurate mapping for the allocation of medical resources. Often, regions with a consistent level of cases escape government attention compared to regions experiencing the highest case spikes in a specific year. Addressing this issue, this study aims to cluster 33 regencies/cities in North Sumatra using the K-Means Clustering algorithm to map the stability of disease spread based on 5-year historical data 2020–2024. The features used include mean prevalence X_1, growth rate X_2, and fluctuation level X_3. Data normalization was carried out using Min-Max Normalization and measured using Euclidean Distance. System testing reached convergence at the 3rd iteration, grouping regions into three clusters: High Priority C1; 15 regions, Medium Priority C2; 9 regions, and Low Priority C3; 9 regions. Quality evaluation using Silhouette Score resulted in a global average score of +0.3941 Weak Structure. The developed web-based system serves as a decision support tool for health authorities in formulating targeted medical intervention strategies.