The Frequent Pattern Growth Algorithm in the Film Recommendation System - Angelyna Angelyna; Arham Aulia Nugraha; Karima Marwazia Shaliha; Muhammad Humam Wahisyam; Tri Kurnia Sandi; Acep Razif Andriyan (UIN Sunan Gunung Djati Bandung, 2021)
In order to decrease the covid-19 rate, people choose to stay at home. Watching movies with family can be an alternative to fill activities during a pandemic. But sometimes it’s hard to determine the film to be watched. To overcome this a recommendation system is needed. This research is shown to build a system recommendation for film recommendations next will be witnessed. This system created using the Frequent Pattern Growth Algorithm which will do filtering later against several films based on the user’s viewing history. The results of testing the recommendation system using the FP-Growth algorithm work well and can show a minimum support value of 0.973 and a confidence value of 0.291, where the size of this value affects the resulting pattern output.