Penerapan Algoritma Apriori Untuk Rekomendasi Produk Bagi Pelanggan Toko Online Berbasis Website - Ana Hanapi; Rafika Sari; Mukhlis (Fakultas Teknik, Universitas Bhayangkara Jakarta Raya, 2023)
Today, almost all activities in various sectors of life have been transformed into digital systems to support various related activities. Consideration of the efficiency of dissemination of information outreach and data management that can be recorded properly is the main reason for switching to a digital system. In the economic sector, global business developments are rife with the use of digital devices in marketing various products to increase marketability. Based on this, this research was conducted to apply the Apriori algorithm association data mining to provide product recommendations for online shop customers. The CodeIgniter framework and the waterfall method are used to build a website-based information system. Sampling data was obtained from transaction data at the Rizvenastore store which was used for the database using MySql. The application of the a priori algorithm can form association rules as a reference in-store product promotions and decision support in providing product recommendations to customers based on predetermined minimum support and confidence values. From testing the system using the black box method, the results obtained for all activities on all actors can run as expected.