Penerapan Algoritma K-Means Untuk Pengelompokkan Minat Konsumen Gas LPG Pada Pangkalan Sudiawati

Abstract

Pangkalan Sudiawati is one of the shops engaged in the sale of LPG Gas products domiciled in Harapan Indah, North Bekasi. The goods sold at the Sudiawati base are 3 Kg and 12 Kg LPG Gas. These problems can be solved by using one of the techniques in data mining, namely the K-Means Clustering algorithm. This research is intended to assist Pangkalan Sudiawati in selling 3 Kg and 12 Kg LPG gas to consumers, to group sales data in order to maximize stock management. The data is processed by manual calculations using the K-Means algorithm and using Microsoft Excel 2019 Software. These results can be used to improve stock management
and sales strategies at Pangkalan Sudiawati.