Ensemble Quick Robust Clustering Using Links for Clustering Hypertension Patients at a Health Center - Niftayana, Neli; Fajri, Mohammad; Gamayanti, Nurul Fiskia (Universitas Bumigora, 2025)
Hypertension is a chronic disease with a high risk of cardiovascular complications and requires treatment according to patient characteristics. At the health center, the number of hypertensive patients is 6953, the highest recorded. Therefore, this study aims to classify and determine the characteristics of hypertensive patients at a health center. The method used in this study is Ensemble Quick Robust Clustering Using Links. This method combines the clustering results of Quick Robust Clustering Using Links and Agglomerative Nesting. Where this method is more efficient in clustering. The results of this study show the number of clusters in the Quick Robust Clustering Using Links method is 3, Agglomerative Nesting is 3 and in the Quick Robust Clustering Using Links Ensemble produces 9 clusters with the following distribution: Cluster 1 shows low hypertension, cluster 2 shows high hypertension, cluster 3 to cluster 6 shows high hypertension, cluster 7 shows moderate hypertension, cluster 8 shows high hypertension and cluster 9 shows moderate hypertension. Thus, grouping patients based on a combination of numerical and categorical variables can provide more detailed information about the severity of hypertension.