Application of K-Means Clustering Algorithm in Grouping Inventory Data at Putra Shop

Authors

  • Deki Hari Nusti Universitas Dehasen Bengkulu
  • indra kanedi Department of Informatics, Faculty of Computer Science, Universitas Dehasen Bengkulu
  • Eko Prasetiyo Rohmawan

DOI:

https://doi.org/10.53697/jkomitek.v1i1.104

Keywords:

k-means clustering, algoritma, pengelompokan data

Abstract

Putra Mart store is one of the supermarkets in Bintuhan City., on Jl. South Kaur Cold Water. Putra shop is one of the shops engaged in supplying goods to small shops in Bengkulu City. The goods supply system at Toko Putra still uses a manual system in recording data, both data on availability of goods, data for store partners, and data on supply of goods to store partners. To help increase the supply of goods at Toko Putra, there needs to be an application that can determine what items should be in Toko Putra by looking at transaction data for supply of goods to store partners. Determination of stock of goods is done by grouping data on supply of goods through 2 groups, namely large groups and small groups. The application for grouping supply data at Toko Putra was created using the Visual Basic .Net programming language and SQL Server 2008 database by applying the K-Means Clustering Method. The grouping is done based on data on supply of goods per year obtained from Toko Putra. The application is able to analyze goods supply data by producing 2 clusters, namely Many and Few through the K-Means Clustering method approach. In addition, the results of this grouping can help the Putra Shop in managing inventory at the Putra Shop by looking at the results of the clustering that has been done. Based on the results of the tests that have been carried out, the application for grouping data on supply of goods at Toko Putra can provide information based on 2 groups, namely many and few. From the supply data in 2020, the results obtained are Cluster C1 as many as 4 and Cluster C2 as many as 13

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Published

2021-06-29

How to Cite

Nusti, D. H. ., kanedi, indra, & Rohmawan, E. P. (2021). Application of K-Means Clustering Algorithm in Grouping Inventory Data at Putra Shop. Jurnal Komputer, Informasi Dan Teknologi, 1(1), 29–38. https://doi.org/10.53697/jkomitek.v1i1.104

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