PREDIKSI PEMAKAIAN CITY GAS RUMAH TANGGA MENGGUNAKAN METODE KLASIFIKASI NAIVE BAYES (STUDI KASUS: PT. SARANA PEMBANGUNAN ENERGI MADANI)
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Date
2020-09
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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
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Keywords
City Gas, Naive Bayes, Inventory, Prediction, Household