PERANCANGAN SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI PRODUK BUNDLING DAN CROSS- SELLING PADA PROGRAM “TEBUS MURAH” UNTUK QUICK-COMMERCE PT.X

• Main Author: Muhammad Iqbal, Fahmi
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/77681
• Institution: Institut Teknologi Bandung

PT. X is a quick commerce company implementing a hyperlocal strategy focused on providing concentrated services within specific geographical boundaries. PT. X currently has twenty-five dark store locations to serve their customers. PT. X's customer satisfaction strategy includes offering discounts on bundled products, both for single-type products (wholesale) and product pair bundling. Additionally, PT. X currently has a cross-selling program named "Tebus Murah" that appears on the customer's checkout menu. However, the decision-making process for product bundling and cross-selling lack a solid foundation. Nevertheless, PT. X plans to select products for the "Tebus Murah" program based on their popularity. The design of the Decision Support System (DSS) in this study will be based on the market basket analysis (MBA) model with multi-dimensional association rule mining using the Apriori algorithm, considering the time range as input. The DSS designed in this study will accommodate location and time range inputs to be analyzed. The designed MBA model can accommodate the determination of products for single-product bundling, cross-product bundling, and products for the "Tebus Murah" program. Recommendations for single- product bundling are generated based on the mode value search and its occurences. Recommendations for cross-product bundling are produced based on association rule generation with a minimum support value of 0.001 and a minimum lift of 1. Recommendations for the "Tebus Murah" program are generated based on frequent itemsets generation, then the occurrence is identified. The DSS is designed with three main menus: data input menu, product bundling recommendations menu, and product recommendations for the "Tebus Murah" program menu. The data input menu accommodates data filtering based on service location and time range. The product bundling recommendations menu contains bundling recommendations for single-product and cross-product. The product recommendations menu for the "Tebus Murah" program contains popular products sorted by their occurences.