Analysis of Data Mining Using K-Means Clustering Algorithm for Product Grouping

Authors

  • chilakala Hari Krishna Author
  • Dr.J.Vanitha Vani Author
  • Chejarla Ravi Author

Keywords:

Data mining, K-Means Algorithm, Clustering, Stock.

Abstract

Rizki Barokah Store is one of the stores that every day sell a variety of basic materials of daily necessities such as food, drinks, snacks, toiletries, and so on. However, some problems occur in the Rizki Barokah Store is often a build-up of product stocks that resulted in the product has expired.This is due to an error in making decisions on the product stock. In addition to these problems, with the amount of sales data stored on the database, the store has not done data mining and grouping to know the potential of the product. Whereas data-processing technology can already be done using data mining techniques. To overcome the period of the land, the technique used in data mining with the clustering method using the algorithm K-means. With the use of these techniques, the purpose of this research is to grouping products based on products of interest and less interest, advise on the stock of products, and know the products of interest and less demand.

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Published

12-10-2019

How to Cite

Analysis of Data Mining Using K-Means Clustering Algorithm for Product Grouping. (2019). International Journal of Information Technology and Computer Engineering, 7(4), 57-64. https://ijitce.org/index.php/ijitce/article/view/118