Penerapan Market Basket Analysis pada Data Transaksi Online Retail Menggunakan Algoritma Apriori dan FP-Growth dengan Kerangka CRISP-DM
Alfia Budi Putro, Abiyyu, Iqbal Mustofa, Muhammad, Mirano, Nauval
Abstrak
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.
Penerbit
CV. Ruang Publikasi Ilmiah
Kata kunci
Data Mining, Customer Intelligence, Market Basket Analysis, Apriori, FP-Growth, CRISP-DM; Data Mining, Customer Intelligence, Market Basket Analysis, Apriori, FP-Growth, CRISP-DM