Aplikasi Pengenalan Pola Pembelian Konsumen Menggunakan Kombinasi Algoritma FP-Growth Dan ECLAT Method (FEM) - Florida Nirma Sanny Damanik; Andrew Sagita; Harianto -; Andy Syaputra (Fakultas Informatika, 2018)
Sales data stored in enterprise databases are usually stored as archives or documentation. In the case of retail companies, data mining science can be used to extract new information from sales database, ie consumer purchase pattern analysis. The algorithm that can be used to analyze consumer purchase pattern is FEM algorithm using combination of Frequent Pattern Growth (FP-Growth) and Eclat algorithm. The construction of FP-Tree tree structure is done by using FP-Growth algorithm, while the process of extraction of items purchased (frequent itemset) is done by using Eclat algorithm. The application designed can be used to analyze consumer purchase pattern by generating associative rules using FEM algorithm through the Analysis form and printing the consumer purchase pattern through the purchase pattern report.