Region Grouping Based on Sales Results Using K-Means Algorithm at PT RMK

In the development of the business world which is always evolving and full of competition, the business actors must always think about how to continue to survive in developing their business scale. PT. RMK is a company engaged in the distribution of mobile phone credit vouchers, PT RMK wants to develop their business by identifying the sales area which their good at. Therefore, to support the company's business development, this study aims to help PT RMK to find out the potential sales areas in Bogor Regency using data mining. The stages of data mining work from data collection, data selection, modeling stage using the K-means clustering algorithm, and evaluation to the implementation phase. The results achieved are based on the K-Means Algorithm clustering of Cluster 2 which results in the sub-districts of Gunung Putri and Cileungsi being the areas with the most superior potential. It can be concluded that Gunung Putri and Cileungsi sub-districts are the sub-districts that display the most superior potential graph. The conclusion is the k-means algorithm clustering method can be used in grouping potential sales areas in sub-districts in Bogor district based on total sales transaction data