Rekomendasi Produk Menggunakan Algoritma Apriori (Studi Kasus: Viera Oleh-Oleh)

Tri Agnesti (Politeknik Caltex Riau)
Puja Hanifah (Politeknik Caltex Riau)

Proceeding Applied Business and Engineering Conference
Vol. 10 (2022): 10th Applied Business and Engineering Conference

Viera Souvenirs is one of the largest gift shops in the city of Pekanbaru which has been establishedsince 2015. This shop provides various types of food, wet cakes, snacks and drinks typical of the city ofPekanbaru. Many people who have shopped at Viera Souvenirs have experienced difficulties when shopping,such as not getting information about product prices and what products are recommended, incomplete allproduct lists on the online ojek application and admin responses that are not quick to respond. In order tomaintain and increase sales turnover, a recommendation system is built to help customers find out informationabout what products and products are often sought after and maintain customer comfort in shopping. A priorialgorithms are implemented on sales transaction data that will produce rules that produce information aboutselected products that are recommendations. On feature testing using blacbox gives the result that all featuresare working properly. In the lift ratio test, the results were obtained, there were 88 rules that had an lift ratio >1. From the results of the questionnaire given to 20 respondents, it can be concluded that this system hassucceeded in helping consumers to determine which products they want to buy.