Analisis Paket Penjualan pada Kedai Kopi Menggunakan Algoritma Apriori

Abstract

The Indonesian coffee industry is experiencing rapid expansion with fierce competition between local and international outlets. This has encouraged SMEs to implement data-driven sales strategies, particularly product bundling, which increases transaction value. However, many people choose packages based on intuition rather than analyzing purchase data. This study implemented association rule mining through the Apriori Algorithm to examine coffee shop sales patterns. Using a minimum support of 75% and a confidence level of 60%, the study identified purchase patterns across 2-itemsets, 3-itemsets, and 4-itemsets, resulting in 79 significant association rules. The strongest rule was Croissant ⇒ Matcha_Latte with 100% confidence, 1.13 lift, and 8.89 conviction. The results provide a strategic foundation for targeted menu packages and promotional strategies.