Utilization of Data Mining on MSMEs using FP-Growth Algorithm for Menu Recommendations

Existing transaction data is only recorded and stored as a sales memorandum, so it has not been utilized optimally. The used history. availability of lot having pattern transactions that are similar to MSME Cafe Over Limit will be by using mining science. This research uses the association rules method. Implementation fp-growth get item combinations. purpose this make easier for MSMEs determine menu recommendations customers. algorithm process many 2038 with minimum support value 10%, while confidence 50%. So there 3 rules, namely "if you order Mariam chocolate cheese milk then customer Kopsus Overlimit", from rule form 10.79%, 54.19% lift ratio 0.93. Furthermore Overlimit tofu at grandma's house", produce 34.69%, specified 59.76%, 1.15. last house, orders occurs, 66.7% results study found two best over-limit Kopsus, he house" Kopsus". Based on formed, can concluded categorized valid reference in food beverage Limit. useful applied MSMEs, especially terms recommendations.