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

Dublin Core

Title

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

Subject

Data mining; K-Means Algorithm; Clustering; Stock

Description

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.

Creator

Mohammad Imron a,*, Uswatun Hasanah a, Bahrul Humaidi a

Date

2020

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Citation

Mohammad Imron a,*, Uswatun Hasanah a, Bahrul Humaidi a, “Analysis of Data Mining Using K-Means Clustering Algorithm for Product Grouping,” Repository Horizon University Indonesia, accessed June 5, 2025, https://repository.horizon.ac.id/items/show/9204.