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Analisis Pengelompokkan Penjualan Rattan Furniture Pada PT. Hymsa Indotraco Berbasis Algoritma K-Means Clustering Krishna Febianda; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hymsa Indotraco is a rattan furniture manufacturing and exporter company in Indonesia, which has more than 5000 furniture collections. Production is based on orders from buyers. This raises a problem, namely management has difficulty determining the amount and type of raw materials available in accordance with customer orders. So, we need a method that can help the processing of sales data. This study aims to determine the pattern of grouping sales data using K-Means Clustering to get the results of grouping sales of rattan furniture that are most ordered, frequently ordered, and rarely ordered. In its implementation, RapidMiner tools are used. This clustering produces clusters that are rarely ordered as many as 678 products, clusters that are often ordered as many as 14 products, and the most ordered are as many as 15 products. Data evaluation was performed using the Davies-Bouldin Index with 3 clusters yielding 0.106. The results of this study are used as recommendations for companies to determine the supply of raw materials and products offered to customers.