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All Journal Bit (Fakultas Teknologi Informasi Universitas Budi Luhur)
Oktalia Kumala Sari
Universitas Mercu Buana
Computer Science & IT Electrical & Electronics Engineering

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Web-Based Application Using Apriori for Bundling Recommendations of Special Products Oktalia Kumala Sari; Anis Cherid
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 20, No 2 (2023): SEPTEMBER 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v20i2.2444

Abstract

Data Mining can be utilized in various disciplines, such as Solo Latri Grocery Store, to boost sales and determine grocery sales. The current problem is that the determination of basic food sales at Toko Sembako Solo Latri cannot determine customer purchasing patterns or the number of customers who purchase basic food at the same time. This research seeks to develop a web-based application that integrates the Apriori algorithm into the recommendation process for bundling basic food products. Latri Grocery Store will create a model or association rule to increase sales. By utilizing the Crisp-DM method, it is possible to obtain important information regarding the pattern of transactions made simultaneously using the Apriori algorithm. This investigation is supported by a dataset of sales transactions for the period February 1 to April 20, 2023. Our results show that the Apriori algorithm with a minimum support value of 50% and a minimum confidence value of 50% produces the best seven item set combinations. The best result is a support value of 95.38 percent, a confidence value of one hundred percent, and a lift ratio of 1.97.
Co-Authors Anis Cherid