Penerapan Association Rule Mining untuk Rekomendasi Promo Bundling dalam Sistem CRM Berbasis Online - Herdian, Gentala Virgiawan; Sulianta, Fery (Institut Teknologi Garut, 2025)
The online ordering system is an important strategy in improving service efficiency and customer loyalty, especially in micro businesses such as Coffee Kane. This study applies the Association Rule Mining (Apriori) algorithm within the CRISP-DM framework to identify customer purchasing patterns and design bundling promotions based on Customer Relationship Management (CRM). The data used is transaction history from the last two months. The analysis results produced a number of significant association rules, such as product combinations with the highest lift value of 31.50. These rules were implemented into the Laravel-based ordering system and automatically displayed to customers. This study shows that this data-driven approach not only improves the effectiveness of promotions but also strengthens customer engagement through an adaptive and personally relevant system.