Implementation Of ETL E-Commerce For Customer Clustering Using RFM And K-Means Clustering

E-commerce is the activity of selling and buying goods through an online system or online. One business models in which consumers sell products to other Customer (C2C) model. things that need be considered this model knowing level customer loyalty. By loyalty, company can provide several different treatments its customers so they maintain good relations with increase product purchase revenue. In study, author wants segment on data companies Brazil using K-Means clustering algorithm RFM (Recency, Frequency, Monetary) feature. There are also ETL stages research must carried out, namely taking from open public site (Kaggle), consist more than 9 tables (extract), then merging select some needs used (transform load), understanding by displaying it graphic form, conducting selection features / attributes. accordance proposed method, performs preprocessing, creates a get cluster. Based results has been done, number clusters 4 evaluation value silhouette score 0.470.