Implementation of K-Means Clustering in Online Retail based on Recency, Frequency, and Monetary - Karima Marwazia Shaliha; Angelyna Angelyna; Arham Aulia Nugraha; Muhammad Humam Wahisyam; Tri Kurnia Sandi (UIN Sunan Gunung Djati Bandung, 2021)
During a pandemic like today, many changes have occurred, one of which is the increasing number of online buying and selling sites. Each Online Store offers a variety of products and services with a variety of attractive offers, competing fiercely to attract enthusiasts. With the occurrence of a pattern of change in society, it is necessary to carry out a grouping to obtain information in order to determine a better sales strategy. The grouping process uses techniques from data mining, namely Clustering with the K-Means algorithm based on the Recency Frequency Monetary (RFM) algorithm, it is hoped that by analyzing the three attributes and implementing the K-Means algorithm, it can provide an accurate output and in accordance with the objectives of this study.