SISTEM REKOMENDASI PAKET MINUMAN BERDASARKAN PESANAN PELANGGAN DENGAN METODE FREQUENT PATTERN GROWTH

Abstract

It is proposed that a beverage package is determined based on customer orders by looking for different frequent itemset patterns in the transaction data that has occurred. These data can be analyzed to be more useful. The method used is the association method. With the predicted beverage package the company can increase sales. With so many transaction data stored, the difficulty in managing data requires a method called the association method. Frequent Pattern Growth Algorithm is an alternative algorithm that is quite effective for finding the set of data that most often appears (frequent itemset) in a large data set. The test results from the Frequent Pattern Growth method can determine a number of packages that meet the minimum value of support and confidence with a combination of two itemset