Penerapan Market Basket Analysis pada Data Transaksi Online Retail Menggunakan Algoritma Apriori dan FP-Growth dengan Kerangka CRISP-DM
Keywords:
Data Mining, Customer Intelligence, Market Basket Analysis, Apriori, FP-Growth, CRISP-DMAbstract
This study uses Market Basket Analysis (MBA) to identify customer purchasing patterns in online retail data. Both Apriori and FP-Growth algorithms generated 218 identical association rules, but FP-Growth showed faster computational performance. The results can be applied to product bundling, cross-selling, and more effective inventory management.
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