Application of K-Means Clustering Algorithm for Disease Grouping at Blessing Dental Care Clinic - Fransiska, Cintiya Aulya; Dafid, Dafid (Politeknik Negeri Lhokseumawe, 2025)
Blessing Dental Care Clinic is a clinic that provides dental practice services and general practitioner practices located in Palembang. This clinic offers general care and dental care managed by experienced doctors in their fields. The focus of the data used is medical record data, especially from general practice. Grouping large data into several groups based on similar pattern characteristics by utilizing the K-Means Clustering algorithm in CRISP-DM data mining was chosen to be more effective in handling various complaints of various diseases through the Clustering process. The results showed that the form of cluster 1 was 220 dominant data in the respiratory disease category, cluster 2 was 335 dominant data in the cardiovascular disease category, cluster 3 was 584 dominant data in the cardiovascular disease category, cluster 4 was 363 dominant data in respiratory disease, cluster 5 was 70 dominant data in respiratory disease, cluster 6 was 254 dominant data in cardiovascular disease and cluster 7 was 165 dominant data in ENT disease. In cluster 7 with an SSE value of 3189.16, the decrease is getting smaller and the spread pattern is starting to be optimal with a tendency for the pattern to be more spread out.