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All Journal International Journal of Advances in Applied Sciences
Maradjabessy, Prita Nurkhalisa
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Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Determining the retail sales strategies using association rule mining Yanti, Roaida; Maradjabessy, Prita Nurkhalisa; Qurtubi, Qurtubi; Rachmadewi, Ira Promasanti
International Journal of Advances in Applied Sciences Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i3.pp530-538

Abstract

Competitive competition in the retail industry requires retailers to maintain improvements and formulate accurate strategies to maintain their competitiveness. A small number of daily visitors visit retail store Y if compared to other retail stores, which leads to decreased store revenue due to the small number of products sold. Therefore, it is crucial to formulate the right business strategy to increase sales by utilizing customer shopping behavior derived from transaction data. The method used is association rule mining (ARM) with a frequent pattern growth (FP-growth) algorithm to determine consumer buying patterns. Data processing results generate five valid rules that meet the specified criteria for an association relationship. Utilization rules are acknowledged by determining retail sales strategies by recommending store layouts, shopping catalogs, and voucher discounts to attract customers.
Co-Authors Qurtubi Qurtubi, Qurtubi Rachmadewi, Ira Promasanti Yanti, Roaida