Open AccessImplementasi Algoritma Apriori untuk Rekomendasi Kombinasi Produk Penjualan
Author(s) -
Andre Setiawan,
Farica Perdana Putri
Publication year - 2020
Publication title -
ultimatics : jurnal ilmu teknik informatika/ultimatics : jurnal teknik informatika
Language(s) - English
Resource type - Journals
eISSN - 2581-186X
pISSN - 2085-4552
DOI - 10.31937/ti.v12i1.1644
Subject(s) - computer science , database transaction , apriori algorithm , association rule learning , transaction data , database , data mining , recommender system , lift (data mining) , process (computing) , information retrieval , programming language
Analyzing and systematically extracting essential information from recording transactions is important for a business, including online stores. Sometimes, some online stores offer a product package that is not suitable for the customer. It happens because they did not process the data transaction to observe the association between products on a package. A web-based recommendation system was build using the CodeIgniter framework with PHP programming language. The system developed using Market Basket analysis that can determine the combination of products. Apriori algorithm used as a technique to analyze the relationship between products based on the data transaction. The lift ratio value generated from the rule is 1.18, which means that the rule has the power of relationships between items. We evaluate the system using USE questionnaire with usefulness results is 90.83%, ease of use 89.09%, ease of learning 95%, and satisfaction 90.94%, which strongly agree in every aspect.