Penerapan Metode K-Means Clustering Dalam Pengelompokan Data Pasien Rawat Inap Peserta BPJS Di Rumah Sakit Umum Daerah Kabupaten Kaur

Abstract

The Kaur Regency Regional General Hospital is one of the health institutions where the majority of patients are members of the Social Security Administering Agency for Health. The problem with data management is that it is still done manually, where the data is captured and written in books, so that the goal is to make it difficult for hospital management to make decisions related to optimal service for patients, as well as the lack of information obtained by the hospital regarding information on the diseases most frequently suffered by hospitalized patients. inpatients, especially patients participating in the Social Security Administration. Applying the K-Means Clustering Method in grouping data on inpatients participating in the Social Security Administering Agency at the Kaur Regency Regional General Hospital can find out information on the results of grouping data on inpatients participating in the Social Security Administering Agency which is divided into 2 groups, namely few and many based on age, gender and class level of the Social Security Administering Body, and can also help evaluate data on the most and least inpatients at the Kaur Regency Regional General Hospital based on grouping results by looking at age, gender and class level of the Social Security Administering Body and the patient's illness. .  Based on the results of testing on 30 data on inpatients participating in the Social Security Administration, grouping results were obtained, namely Cluster I with 20 patients and Cluster II with 10 patients. Where Cluster I (a lot of treatment) is dominated by women in the age group 40 – 59 years and the Social Security Administering Body class level III with Type 2 DM. Meanwhile, Cluster II (a little treatment) is dominated by men who are in the age group 20 – 39 years and Social Security Administering Agency level III class with dyspepsia syndrome and gero