Implementation of Data Mining to Classify the Consumer’s Complaints of Electricity Usage Based on Consumer’s Locations Using Clustering Method

Abstract

Abstract Data collected by PLN staff on customer’s complaints in the usage of electricity are very huge and accumulate. Previously, there was no information about these kinds of complaints in all sub-districts included inside the company, PT. PLN Binjai. On the other hand, each year company experienced problems to classify all complaints in order to obtain customers with information to later be used as a basis for making policy/decision. Data mining used clustering method and K-Means algorithm to classify the data so that important information is obtained from customer’s complaints on the electricity usage, using variable: types of complaints, power using by consumer and consumer’s region. Data was analyzed using Matlab to produce cluster centers and obtained a relationship between variables obtained with groups with high number of complaints. Results revealed that from 500 customers who have complained, cluster 1 had 218 complaints namely NT Fuse Putus with power used was 1300 watt and was located in Binjai.