K-MEANS ALGORITHM IMPLEMENTATION FOR CLUSTERING OF PATIENTS DISEASE IN KAJEN CLINIC OF PEKALONGAN - Anindya Khrisna Wardhani (Jurusan Teknologi Informasi Universitas Semarang, 2016)
In determining the consistency of health data, can use data mining techniques that can dig the hidden information from multidimensional data sets that have been obtained. In addition, data wich connected with other data can also be done by these data mining techniques. One of the data mining techniques is quite well known namely clustering. The methods are quite popular in data mining techniques that called k-means method. It is used to facilitate medical recorder for analyzing the general health situation of population groups in archiving health care data. The results of this analysis, the clustering of the disease based on age, sex, duration of disease and disease diagnosis.This research used tool Rapid Miner 5.3.Based on the data from clinic centers Kajen Pekalongan, the result of clustering is 376 items of acute and 624 unacute diseases from 1000 total of data.