AN APPROACH TO IMPROVE LAYOUT STORE AND PRODUCT PLACEMENT USING COMBINATION OF APRIORI ALGORITHM AND PROFITED SEQUENTIAL PATTERN

Abstract

Two of the parameters of success in retail business are by seeing how the store facilitates the service response and attracts the customers to buy more products in the store. Market Basket Analysis is widely used to discover customers behavior by analyzing the co-occurring products items in customers shopping basket. Understanding customers behavior could be great knowledge to discover corresponding with help of Market Basket Analysis by using Apriori Algorithm. The minimum support and confidence of Apriori Algorithm applied in this research is 1% and 60% respectively has generated 15 rules. In this research, the result will be used to determine the efficient proposed layout to reduce the total people walking distance. After comparing the total people walking distance of the Initial Layout and Proposed Layout by using 7 data transactions as a sample, there is reduced length of people walking distance from 179.38 meters for initial layout to 64.38 for proposed layout. As a result, the improvement in percentage is about 64.97%. It means that the proposed layout consumes less walking distance if compared to the previous layout. Displaying products in certain level of shelf also has significant influence on customers’ buying behavior. Thus, another calculation applied into this research to determine the proper product display is Profited Sequential Pattern (PSP). There are 54 products generated, clustered as high PSP value by considering the support, gross margin and facing of product. Those products will be arranged into certain level of shelf based on its category. Tools used to discover the frequent items set is R studio with the help of Microsoft Excel. As the data used in this research as sample size for the analysis is 1061 transactions with 2836 observations.