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Implementation of The Apriori Algorithm on X Cafe Sales Transactions for Product Bundling Package Recommendations Sadiah, Halimah Tus; Purnama, Delta Hadi; Erniyati, Erniyati
International Journal of Quantitative Research and Modeling Vol 6, No 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.882

Abstract

Bundling packages are a marketing strategy in which several products are combined at a more attractive price than if purchased separately. This strategy effectively increases sales, attracts new customers, and levels up the average transaction value. Cafe X, located in Bogor, is a coffee shop that has not yet had a product bundling strategy package to increase product sales. This study aims to implement the Apriori algorithm on sales transactions at Cafe X to bundle product recommendations. The research stages consist of data collection, preprocessing, implementation of an apriori algorithm, and extracting association rules. In this study, a website-based apriori algorithm was implemented. Users can enter the minimum support value, minimum confidence value, and the recommended menu for product bundling. Based on the research results, it is produced for data input on the application with menu recommendations in the form of Tsuin Iced Coffee and Chicken Strips menus with a minimum support of 50% and a minimum Confidence of 90% can produce recommendations for 3 product bundling packages, including Package 1 recommendations are Tsuin Iced Coffee, Chicken Strips, Hot Barbeque Chicken. Package 2 recommendations are Tsuin Iced Coffee, Chicken Strips, and Nachos. Package 3 recommendations are Tsuin Iced Coffee, Chicken Strips, Hot BBQ chicken and Nachos.
Implementation of the First In First Out (FIFO) Algorithm in the Sandal and Shoe Product Inventory (Stock) Application Sadiah, Halimah Tus; Purnama, Delta Hadi; Ishlah, Muhamad Saad Nurul
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.552

Abstract

This study addresses the optimization of inventory management for sandal and shoe products, at CV Diva Karya Mandiri Warehouse, which covers of five key features: a dashboard, master data management, transaction data, reporting, and user management. The First In First Out (FIFO) algorithm is specifically applied to the transaction feature, ensuring timely disbursement in line with the order of receipt. It is implemented using Rapid Application Development (RAD) methodology, which consists of Planning Requirements, User Design, Construction, and Cutover phases. The developed inventory application offers two access levels: administrators with comprehensive access and warehouse managers with limited access for viewing, searching, and filtering item data. This study successfully implementing the FIFO algorithm, with 95% Blackbox testing result achieved through boundary value analysis approach.Top of Form
Implementation of The Apriori Algorithm on X Cafe Sales Transactions for Product Bundling Package Recommendations Sadiah, Halimah Tus; Purnama, Delta Hadi; Erniyati, Erniyati
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.882

Abstract

Bundling packages are a marketing strategy in which several products are combined at a more attractive price than if purchased separately. This strategy effectively increases sales, attracts new customers, and levels up the average transaction value. Cafe X, located in Bogor, is a coffee shop that has not yet had a product bundling strategy package to increase product sales. This study aims to implement the Apriori algorithm on sales transactions at Cafe X to bundle product recommendations. The research stages consist of data collection, preprocessing, implementation of an apriori algorithm, and extracting association rules. In this study, a website-based apriori algorithm was implemented. Users can enter the minimum support value, minimum confidence value, and the recommended menu for product bundling. Based on the research results, it is produced for data input on the application with menu recommendations in the form of Tsuin Iced Coffee and Chicken Strips menus with a minimum support of 50% and a minimum Confidence of 90% can produce recommendations for 3 product bundling packages, including Package 1 recommendations are Tsuin Iced Coffee, Chicken Strips, Hot Barbeque Chicken. Package 2 recommendations are Tsuin Iced Coffee, Chicken Strips, and Nachos. Package 3 recommendations are Tsuin Iced Coffee, Chicken Strips, Hot BBQ chicken and Nachos.