Data Mining Analysis To Determine The Inventory Of Food Sales During The Pandemic With The K-Means Clustering Method

David C. Hutajulu (Program Studi Sistem Informasi, Fakultas Teknologi Dan Ilmu Komputer, Universitas Prima Indonesia)
Yulianus Zega (Program Studi Sistem Informasi, Fakultas Teknologi Dan Ilmu Komputer, Universitas Prima Indonesia)
Unggul Siregar (Program Studi Sistem Informasi, Fakultas Teknologi Dan Ilmu Komputer, Universitas Prima Indonesia)
Jepri Banjarnahor (Program Studi Sistem Informasi, Fakultas Teknologi Dan Ilmu Komputer, Universitas Prima Indonesia)

INFOKUM
Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence

Currently, many businesses are no longer operating because people no longer shop directly for direct sales, but now many people shop online. This is one of the problems faced by sales that do not market their goods online, so there has been a buildup of inventory for the last 2 years during this pandemic. It is difficult for the company to know which types of goods will be sold a lot and a little every day because the system is still in use only for input. So with that there needs to be a system that solves the problem. In this study, the K-Means method will be used to determine the most sales. This system has carried out the clustering process with the K-Means method by utilizing the data of past items. The results of this research in cluster 1 with a value of Cluster 1 -> 358.64 245.9775 while in Cluster 2, Cluster 2 -> 45.39 22.824285714286.