Pengelompokan Data Pasien Test Urine Dengan Metode Clustering Pada Kantor Badan Narkotika Nasional Kota Binjai

Abstract

Data Mining is a data processing technique by digging various information from a set of stored data. Urine test is a means to determine whether or not a patient is related to narcotic abuse. The National Narcotics Agency (BNN) of Binjai City is an Indonesian non-ministerial government agency (LPNK) that has duties in the fields of prevention, eradication of abuse and illicit trafficking, psychotropic substances, precursors, and other addictive substances except for tobacco and alcohol addicts. The writing of this report uses the clustering method which is one of the data mining techniques for grouping data on the Urine Test Patient at the Binjai City BNN Office. By using the k-means algorithm clustering method. By applying 20 alternative data for urine test patients and giving the number of clusters as many as 3, and utilizing the 3 main criteria as research in this report, the number of cluster 1 is 5 data, cluster 2 is 9 data. And cluster 3 of 6 data. This urine test patient data grouping system is designed with the MATLAB application programming language.