IMPLEMENTASI DATA MINING PENGELOMPOKAN JENIS PENYAKIT PASIEN MENGGUNAKAN METODE CLUSTERING (STUDI KASUS : PUSKESMAS SAMBIREJO) - Shelly Maulia; Budi Serasi Ginting; Anton Sihombing (Jurnal Informatika Kaputama (JIK), 2021)
Disease is a condition where there is an abnormal body condition, which causes the loss of normal healthy conditions. Data mining is a process of finding information by identifying patterns in data sets. The process of finding information can be done by grouping the data using the Clustering method with the K-Means algorithm. The K-Means method is a method in group analysis where the data is grouped based on k groups (k = 1,2,3..k). The purpose of this study was to facilitate the classification of which types of diseases were most common to patients at Puskesmas Sambirejo Langkat Regency based on age, village and disease name in patient data for 2017-2019. From the results of program analysis that has been tested using matlab and the variables have been determined, it can be seen that, for cluster 1 the results of grouping the patient's disease type are 366 data, namely between the ages of 24-40 years, in the village of Sambirejo, with the name bronchitis. For cluster 2, the results of grouping the patient's disease type were 376 data, namely between the ages of 24-40 years, in the peace village, with the name hyperuricemia disease. For cluster 3, the results of grouping the type of patient's disease are 258 data, namely between the ages of 24-40 years, in a prosperous village, with the name hyperuricemia disease.