Penerapan K-means Clustering pada Penjualan dan Pajak BBM di DKI Jakarta

Pramudya Aziz Wisnuadi (Universitas Duta Bangsa Surakarta)
Bagus Irfanzah Arda Nugraha (Universitas Duta Bangsa Surakarta)
Hiskia Kus Setiawan (Universitas Duta Bangsa Surakarta)
Dwi Hartanti (Universitas Duta Bangsa Surakarta)

Prosiding Seminar Nasional Teknologi Informasi dan Bisnis
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023

Fuel oil (BBM) is part of the main merchandise originating from refined petroleum and natural gas, either through direct extraction or processing of crude oil. Tax is an obligation that must be paid by an individual or company to the state based on coercion by law. In this study, the method used is K-Means Clustering data mining, which functions to group data that has been collected into several parts, the K-Means Clustering mechanism is implemented with the RapidMiner tool. Sources of data recorded on the Jakarta Open Data website, especially data on fuel sales and taxation for DKI Jakarta are used in this study. The criterion used is the determination of the center of gravity randomly. The iteration process is carried out 7 times, so that the first cluster with the highest number of elements is formed, including 195 items and the second with 9 items.