Rekomendasi Produk Menggunakan Algoritma Apriori (Studi Kasus: Viera Oleh-Oleh)
Keywords:Apriori Algorithm, Black box, Lift ratio, Product Recommendation, User Acceptance Testing (UAT), and Viera Souvenirs.
Viera Souvenirs is one of the largest gift shops in the city of Pekanbaru which has been established
since 2015. This shop provides various types of food, wet cakes, snacks and drinks typical of the city of
Pekanbaru. 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 all
product lists on the online ojek application and admin responses that are not quick to respond. In order to
maintain and increase sales turnover, a recommendation system is built to help customers find out information
about what products and products are often sought after and maintain customer comfort in shopping. A priori
algorithms are implemented on sales transaction data that will produce rules that produce information about
selected products that are recommendations. On feature testing using blacbox gives the result that all features
are 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 has
succeeded in helping consumers to determine which products they want to buy.
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