Pencarian Frequent Itemset pada Analisis Keranjang Belanja Menggunakan Algoritma FP-Growth

Lusa Indah Prahartiwi


 Market basket analysis (also known as association rule mining) is one method of data mining that focuses on finding purchase patterns by extracting associations or transaction data from a store. Market basket analysis found products purchased together in the same bucket. Association rules is a procedure for finding relationships between items that exist on a dataset. This research uses Supermarket dataset and data processing using Rapid Miner software. The method used in the frequent itemset search is the FP-Growth Algorithm. Experimental results using FP-Growth Algorithm found that the combination of beer spirits-frozen foods and snack foods is a frequent itemset with an lift ratio of 2,477   Keywords: FP-Growth, Market Basekt Analysis




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