Development of decision support system for subsidized electricity purchase using Naive Bayes method to improve company reputation (Case study in PT. PLN (Persero) Malang)

Abstract

Nowadays there are a lot of customers who are categorized as capable households (Rumah Tangga Mampu). The problem is, electricity rates increased to IDR 1,352,00/KWH for customers with average capacity (900 Volt Ampere). Central government spending the proportion of electricity subsidies tends to rocketed up from 2.5% in 2005 to 4.7% in 2012 APBN. For average electricity subsidies consume around 7% of central government spending. This condition shows that electricity subsidies are quite burdensome to the central government budget (Biro Analisa Anggaran dan Pelaksanaan APBN-Sekjen DPR-RI). Problems related to electricity consumed for the national industry gives impact on fluctuations in subsidies and inefficiencies at PT PLN require a comprehensive solution. In implementing the electricity subsidy distribution program that is right on target and foster the performance of PT. PLN in charge, it is necessary to hold a new breakthrough based on technology by creating a systemized system for new registration and re-registration for electricity consumers by bringing the data that has been determined by PT PLN. Next, the consumers will be trained to accessthe system to determine whether the consumer is eligible for subsidies or not. To overcome the problem the system is proposed the solution through the implementation of Naive Bayes. Based on the result, the system is feasible tocategorizefor whom the customer get subsidized electricity rate or not. The precise objectives and the system are able to improve the accuracy in selecting consumer tariff subsidy of electricity to the consumer the right target for PT PLN.