Penerapan Algoritma K-Means Dalam Clustering Produk Terlaris Pada Fr Parfum
DOI:
https://doi.org/10.30872/jsakti.v4i2.9075Keywords:
Data Mining, Parfum, Clustering, K-Means,Abstract
In sales activities, it is important to know which products are selling the best. FR Parfum is a perfume shop that sells quite a lot of perfumes, but the owner does not know which perfumes are the best-selling in his shop. The purpose of this study is to assist shop owners in knowing what perfumes are the best selling at FR Parfum. In this study, the K-Means algorithm with the Clustering method was used, the data were grouped into 3 clusters which were categorized as very in demand, in demand, and less in demand. The data is processed in the RapidMiner application and the results obtained based on the cluster division are cluster 0 which has a size of 30 millimetres, cluster 1 has a size of 7 milli, 10 milli and 12 millimetres, cluster 2 has a size of 20 millimetres. The data used in this study is the sales data of FR Parfum in 2021 as many as 1,655 data in excel format. And the results obtained show that cluster 1 is the highest with a total of 884 of the total sales of 183 7 milliliters, 165 10 milliliters sold and 536 12 milliliters sold. Baccarat perfume was the best selling 88, April Rose perfume was the best-selling sold 58, and the Cuddle perfume was the under-selling one, selling 1. (HY)References
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