AFRIDO, - and MUHAMMAD RIZKI, - and Ismu Kusumanto, - and Nazaruddin, - and Misra Hartati, - and Fitra Lestari Nohirza, - (2022) TURNITIN_Application of Data Mining Using the K-Means Clustering Method in Analysys of Consumer Shopping Patterns in Increasing Sales (case study: Abie JM Store, Jaya Mukti Morning Market, Dumai City). IEOM Society International.

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Abstract

This study applied Data Mining method to cluster sales transactions at Abie JM Stores experienced a decline in sales. Therefore, a strategy was needed to increase sales again. One way that can be done to determine customer needs is to analyze sales transaction data. The sales transaction data can be further processed to obtain more helpful information to increase income, sales, and purchase turnover. Data mining by using k-means grouping or clustering. Data mining can be used to find. solutions in making sales decisions to increase revenue. Sales data storage stores a large number of sales transaction records, where each record provides products purchased by consumers in each sales transaction. From the calculation results, it can be concluded that the k-means clustering method can support the system well. Therefore we need a data processing process using a data mining technique. This study's data collection process uses the interview process and shopping transaction data collection

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