Cluster Analysis of Naruna Ceramic Products Sales at Shopee Using the K-Means Clustering Algorithm Azizatur Rokhimah (a*), Abdiel Bellamy Thomas (a), Nikken Prima Puspita (a), Lucia Ratnasari (a), Siti Khabibah (a), Paulus Wisnu Anggoro (b)
a) Department of Mathematics, Faculty of Science and Mathematics, Universitas Diponegoro, Jl. Prof. Jacub Rais, Semarang, 50275, Indonesia
b) Department of Industrial Engineering, Faculty of Industrial Technology, Universitas Atma Jaya Yogyakarta, Jl. Babarsari No. 44, Sleman, Yogyakarta, 55281, Indonesia
*azizaturrokhimah[at]gmail.com
Abstract
Naruna Ceramic is a company in Salatiga, Central Java, that produces and sells various kinds of products made of clay. Naruna Ceramic products are available on e-commerce platforms, one of which is Shopee. The products by Naruna Ceramic include cups, plates, cutting boards, bowls, saucers, and spoons in various shapes and colors. The many types of products produced can cause the accumulation of several products because there are too many stocks of products that are less desirable to customers. The company needs to group each product to determine which items are most desirable and less desirable by customers on Shopee. This study uses the K-Means Clustering algorithm to form sales clusters by determining 3 clusters with cluster 1 being the most desirable product, cluster 2 being the quite desirable product, and cluster 3 being the least desirable product. So with data grouping, companies can find the most desirable, quite desirable, and less desirable products on Shopee. So that it makes it easier for companies to plan product stocks and there is no stockpiling of products.
Keywords: Naruna Ceramic Products- Data Mining- K-Means Clustering- Cluster
