IJIIS: International Journal of Informatics and Information Systems
Vol 3, No 1: March 2020

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

Mohammad imron (Amikom University Purwokerto, Indonesia)
Uswatun Hasanah (Amikom University Purwokerto, Indonesia)
Bahrul Humaidi (Amikom University Purwokerto, Indonesia)



Article Info

Publish Date
01 Mar 2020

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.

Copyrights © 2020






Journal Info

Abbrev

IJIIS

Publisher

Subject

Computer Science & IT

Description

The IJIIS is an international journal that aims to encourage comprehensive, multi-specialty informatics and information systems. The Journal publishes original research articles and review articles. It is an open access journal, with free access for each visitor (ijiis.org/index.php/IJIIS/); ...