Perbandingan Metode Apriori Dan Frequent Pattern Growth Dalam Mengetahui Pola Pembelian Konsumen
Year: 2024
Type: article
Abstract: The problem that usually arises in a minimarket is that products have not been placed according to consumer habits in buying several products simultaneously. As a result, consumers feel confused in finding the position of the product needed and can experience delays in the transaction process. The purpose of this study is to find consumer purchasing patterns in the case of Toko Alwi Jaya, Tenggarong by comparing the Apriori Algorithm and the FP-Growth Algorithm and knowing the combination between items with the highest frequency so that consumer purchasing patterns are known. The data used in this study amounted to 600 transactions in the form of consumer shopping receipts. The results of this study indicate that the FP-Growth algorithm is the best for determining consumer purchasing patterns at Alwi Jaya Store, Tenggarong, as it produces higher confidence and lift ratio values compared to the Apriori algorithm. Specifically, FP-Growth achieves a confidence value of 47.06%, higher than Apriori's 41.18%, and a lift ratio of 3.79, higher than Apriori's 3.32.
Authors: Mohammad Ichsan Madani, Amin Padmo Azam Masa, Hario Jati Setyadi
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409496460