Clustering Sales Patterns of Best Selling and Less Selling Products at El Jhon Bengkulu Stores Using the K-Medoid Method

Agung Laksono Ridwan (Fakultas Ilmu Komputer, Universitas Dehasen Bengkulu)
Siswanto Siswanto (Universitas Dehasen Bengkulu)
Rizka Tri Alinse (Universitas Dehasen Bengkulu)

Jurnal Komputer, Informasi dan Teknologi
Vol. 2 No. 2 (2022): Desember

The clustering application of the best-selling and less-selling product sales patterns at the El Jhon Bengkulu Store can provide information on the best-selling and less-selling product sales patterns as a basis for consideration in product inventory management at the El John Store. Based on 40 total product sales and inventory data in April 2022, the results obtained that 9 data entered cluster C1 (22.5% best selling products) and 31 data entered C2 cluster (77.25% less selling products). Based on the results of the tests that have been carried out, the functionality of the product inventory is running well as expected, and can provide information on the results of product data clustering into 2 groups, namely Best Selling and Less Selling