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Analisis Cluster Penjualan Produk Operator Seluler Menggunakan Algoritma K-Medoids (Studi Kasus : Kantor Regional Sumbagteng Telkomsel Pekanbaru)
This study analyzes the clustering of cellular operator product sales using the K- Medoids algorithm, with a case study at the Sumbagteng Regional Office of Telkomsel Pekanbaru. The study area covers the provinces of Riau, West Sumatra, Jambi, and the Riau Islands. The sales data analyzed were from September 2022, encompassing various cellular operator products, such as Telkomsel, XL, Axis, Indosat, Tri, and Smartfren, including vouchers and starter packs. The clustering analysis aims to group product sales based on sales volume and sales region, with cluster quality evaluated using the Silhouette Index. The optimal number of clusters was determined using the elbow method derived from SSE calculations, yielding 3 clusters with an SSE value of 4.189. The results of the K-Medoids clustering revealed three clusters. Cluster 1 consists of 18 members with total sales of 4,594 units in Kampar, 1,323 units in Pekanbaru, and 514 units in Siak. Cluster 2 comprises 38 members with total sales of 1,601 units in Kampar, 1,108 units in Pekanbaru, and 135 units in Siak. Cluster 3 includes 76 members with total sales of 465 units in Kampar, 269 units in Pekanbaru, and 147 units in Siak. The total proximity distance of all data measured using the Euclidean distance is 11.246152. The average Silhouette Index value obtained is 0.432531, indicating that the clustering results are fairly good, as the value falls within the range of 0 to 1. These findings demonstrate that the K-Medoids algorithm provides relevant groupings for analyzing sales patterns of cellular operator products in the studied region.
Keywords: Clustering, Elbow Method, Euclidean distance, K-Medoids, Silhouette Index
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