Grouping Patient Data Based On Work And Place Of Residence On Perceived Complaints

Abstract

Every day the Sawit Seberang Health Center serves many patients with various kinds of disease complaints from various areas in Sawit Seberang District. The number of patients can even reach tens of people in one day resulting in a large number of patient visit data. Limited information regarding the spread of diseases that are often suffered by patients in several areas at the Sawit Seberang Health Center has resulted in less optimal policy action, anticipation of treatment and prevention of disease in the community. To find information about grouping patient data based on work and place of residence for perceived complaints, a large or large data mining technique is needed, namely data mining techniques using the clustering method. The purpose of this study is to process and cluster patient data based on work, place of residence and complaints that are felt using the Clustering method, to analyze the results of applying data mining using K-Means Clustering in grouping patient data based on work, place of residence and complaints that are felt and find out the results of the settlement grouping patient data based on work and place of residence on perceived complaints using clustering and data mining methods.