Implementation of FP-Growth Algorithms for Promo Package Determination in a Scooter Motorcycle Workshop Business - I Gusti Ngurah Bagus Picessa Kresna Mandala; I Ketut Adi Purnawan; I Made Agus Dwi Suarjaya (Politeknik Negeri Batam, 2025)
This study applies the FP-Growth algorithm to design bundled promotions for a scooter motorcycle accessory store and workshop in Denpasar, Bali. FP-Growth was chosen for its efficiency in mining frequent itemsets without generating candidate sets. From 23,381 transaction records (January-August 2024), the algorithm identified 16 association rules using a minimum support of 1% and confidence of 50%. These rules were selected based on lift values and product relevance. One notable example is the association between