Comparison of Apriori, Apriori-TID and FP-Growth Algorithms in Market Basket Analysis at Grocery Stores
Andi Ilhamsyah Idris, Eliyah A M Sampetoding, Valian Yoga Pudya Ardhana, Irene Maritsa, Adrisumatri Sakri, Hidayatullah Ruslan, Esther Sanda Manapa
Abstract
Market Basket Analysis is an analysis of consumer behavior specifically from a certain group/group. Market Basket Analysis is generally used as a starting point for seeking knowledge from a data transaction when we do not know what specific pattern we are looking for. Market Basket Analysis in this study is applied to the search for patterns of purchasing groceries at grocery stores and then analyzed by season. This study aims to compare the Apriori, Apriori TID and FP-Growth methods in determining consumer transaction behavior and calculating the quantity of consumer transactions in several seasons based on data obtained from the Market Basket Analysis database. In the results of this study, it is known that FP-Growth has the best performance among the other two algorithms, but uses more memory than other algorithms. The Apriori-TID algorithm uses lighter and faster memory than the Apriori Algorithm