Pengelompokkan Penyakit Pasien Menggunakan Algoritma K-Means - Rahayu Anggraini; Elin Haerani; Jasril Jasril; Iis Afrianty (JURIKOM (Jurnal Riset Komputer), 2022)
Health is one of the most important factors besides education and income. Everyone has the same human rights to get good health services. A government agency that functions to serve all people who need medical services in Indonesia, namely the puskesmas. Ujung Batu Health Center which is located in Ujung Batu sub-district, Rokan Hulu Regency as one of the government agencies. The Ujung Batu health center stores patient medical record data, only sorting out the disease. Therefore, the medical record data needs to be processed using clustering or grouping using the K-Means method. This algorithm partitions the data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped. into another cluster. The data used consisted of 3875 records and 5 attributes, namely Gender, Participant Type, Diagnosis, Return Status, Address. From the test using the K-means algorithm, the clustering results show that cluster 1 has 710 data while cluster 2 has 3165 data. The results of the study show that the use of 2 clusters is the best cluster with a Silhouette Coefficient value showing results with a SC value of 0.646.