PREDIKSI PEMAKAIAN CITY GAS RUMAH TANGGA MENGGUNAKAN METODE KLASIFIKASI NAIVE BAYES (STUDI KASUS: PT. SARANA PEMBANGUNAN ENERGI MADANI)

Abstract

In 2016 natural gas was distributed in 3,713 houses in Limapuluh District, Pekanbaru. This number is spread in 4 villages in Limapuluh District Pekanbaru, namely Rintis, Sekip, Tanjung Rhu, and Pesisir. The unwise usage city gas will have impact on the size of the use of city gas, this will also affect the depletion of the supply of natural gas due to the bigger demand for city gas than its supply. The purpose of this study is to build a system that can predict household city gas usage by using the Naive Bayes Classification method. The working principle of the Naive Bayes method is to calculate a set of probabilities by adding up the frequencies and combinations of datasets that have been made. This system was built with the PHP programming language, MySQL as a database server, and UML as a system design. Data was collected by distributing questionnaires to 97 houses with a span of 2 months, September and Oktober 2019. Total data used are 194 data. Then the results obtained percentage of 70,1030% for accuracy of predictions with good feasibility, where from 194 data tested there were 136 data that were successfully predicted correctly. The manual calculation test is performed and the system calculation produces a similar usage level