KLASIFIKASI DATA KEJADIAN LUAR BIASA CAMPAK MENGGUNAKAN METODE DECISSION TREE C4.5

Abstract

Classification is a technique of learning on data mining which is given by classifier to build a rule of classification. Classification that has been done for understanding the region is KLB or Non KLB base on surveilance data from mealess diseases in a region. The data got from healt Departmen DIY province and the data colects are 648 datas, and then devided by 2 path, they are data training and data testing. The problem in a papper is how the Decission Tree C.45 can used to classify in a KLB or Non KLB. The purpose of clasification to understand the performance of Decission tree C.45 algorithm in doing classification of KLB Region a disease. Classification of tthis paper is to clasify Kejadian Luar Biasa Campak of the KLB or Non KLB. The result of classification was done, the level performance is 84.4037%, base on the result of data testing in a 10-Fold Cross Validation, the result is 96%. So the algorithm can be used to clasify for the KLB data.