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Arif Hernawan
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Computer Science & IT

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DATA MINING UNTUK PENGELOMPOKAN JENIS USAHA DI RUMAH BUMN BATAM MENGGUNAKAN METODE CLUSTERING Arif Hernawan; Fauzi, Rahmat
Computer Science and Industrial Engineering Vol 8 No 3 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

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Abstract

Business actors in Indonesia are generally categorized into large businesses and small and medium enterprises or often known as UKM. There is one State-Owned Enterprise that has the role of gathering and encouraging UKM players to upgrade their classes to be more prosperous, namely Rumah BUMN Batam. The research objective is to classify the types of UKM based on the frequency of sales, so that later the company can carry out further promotions for UKM that get a low number of orders. The k-means clustering algorithm can be used by Rumah BUMN Batam to facilitate the grouping of types of business and the frequency of orders for UKM per year. The author uses the Knowledge Discovery in Database (KDD) process which consists of data cleaning, data integration, data selection, data transformation, data mining, pattern evaluation, and knowledge presentation.
Co-Authors Rahmat Fauzi