The Frequent Pattern Growth Algorithm in the Film Recommendation System

Angelyna Angelyna (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Arham Aulia Nugraha (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Karima Marwazia Shaliha (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Muhammad Humam Wahisyam (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Tri Kurnia Sandi (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Acep Razif Andriyan (Teknik Informatika, UIN Sunan Gunung Djati Bandung)

Gunung Djati Conference Series
Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020

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.