Enhancing Sales Determination for Coffee Shop Packages through Associated Data Mining: Leveraging the FP-Growth Algorithm

The coffee shop business offers a diverse range of and food options. However, customers often experience delays during transactions due to the extensive selection menu items combinations. This inconvenience not only discomforts new but also hampers their likelihood returning, potentially impacting overall turnover. To address this issue, study aims establish association rules by combining least most popular for upcoming month. These will serve as guideline creating shopping packages that streamline decision-making process. FP-Growth algorithm is employed analyze sales transaction data from January March 2023, comprising 2,336 in .csv format. Among generated rules, two stand out with highest support confidence values. first rule exhibits value 0.3% 70.0%, while second showcases 0.4% 69.2%. By considering these alongside existing options, owners can effectively curate cater customer preferences. It anticipated elevate quality service, attract greater number customers, subsequently enhance