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Dhea Tara Monika
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering

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Penerapan Data Mining Menggunakan Algoritma K-Means Clustering Untuk Analisa Penjualan Di Toko Nibras House Kertaharja Muhamad Fatchan; Dhea Tara Monika
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Abstract Nibras House Kertaharja is a retail store that sells of muslim clothes, but the owner doesn’t know what products are best selling in his store. Data on sales, purchases, expenses at the store are not well organized, so the data is only as an archive. One of the way to find out which products are selling less and best selling based on available data is through the use of Data Mining. Data Mining can assist in data processing, one of the technique that is often used is clusterization using the K-means algorithm. The purpose of this research is to help owners find out what products are best selling at Nibras House Kertaharja. The data used in this study is Nibras House Kertaharja sales from March - June 2023 as many as 243 data in excel. The data will be grouped into 3 clusters which are categorized as less in demand, in demand, and very in demand. The data is processed in the RapidMiner and the results obtained based on cluster category are cluster_0 with 204 products, cluster_1 with 35 products, cluster_2 with 4 products.
Co-Authors Muhamad Fatchan