Analisis Data Mining Untuk Klasterisasi Data Rekam Medis Menggunakan Algoritma K-Means Pada Rumah Sakit Sylvani Binjai

Abstract

Medical record is a record of the history of patients who take treatment in hospitals or clinics. RSU Sylvani has many patients, every month and makes patient history data accumulate in the medical record data, but there is no follow-up benefit from the available data. Even though these data have great potential to provide new information and valuable insights if explored with data mining using the k-means clustering method. The amount of data that was tested was 893 data and produced 4 groups from the variables of disease diagnosis, gender and address. Where group 1 totaled 268 data with a diagnosis center for hypertension and female gender at the Pepper Garden address. Group 2 totaled 289 data with a diagnosis center for Asthma and female gender at the Hero's address. Group 3 totaled 185 data with GERD disease diagnosis center and male gender at Kebun Pepper address. group 4 totaling 151 data with a diagnosis center for Prostate Enlargement disease and male sex at Kebun Pepper address.