Implementasi Algoritma K-Means untuk Menentukan Persediaan Barang pada Poultry Shop

Firman Nurdiyansyah, Ismail Akbar

Abstract


Maintaining inventory so that the goods do not get empty is one of the ways to maintain customer satisfaction. To do this, company management must be able to analyze which items are selling well and which items are not selling well, especially in the sales department. It is not easy to CV. Muria PS because it has a large number of items, so it takes a little computational technique to simplify the problem. The K-Means clustering algorithm was chosen to solve this problem because it can group the products sold and still available into several clusters. Of the three clusters formed, cluster 1 consists of two items, cluster 2 consists of 9 items, and the remaining 25 items are included in cluster 3. From these results, CV management can take advantage of this. Muria PS to increase inventory stock and sales strategy.

Keywords


Data Mining; Clustering; K-Means; Sale; Goods.

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References


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DOI: https://doi.org/10.26905/jtmi.v7i2.6377

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