Film Recommendation Analysis with Sequential Pattern Discovery Algorithm Using Equivalence classes (SPADE)

Aisyah Amini Nur (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Akbar Hidayatullah Harahap (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Ihsan Muttaqin Bin Abdul Malik (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Muhammad Irfan Nur Imam (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Muhammad Thariq Sabiq Bilhaq (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Angelyna Angelyna (Teknik Informatika, UIN Sunan Gunung Djati Bandung)

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

Currently, the internet is the most essential thing in human life. So that there is a change in human needs, one of which is enjoying entertainment. With the internet, enjoying entertainment can be done anywhere and anytime, one of the entertainment is movies. With the internet, many service providers provide movie watching sites online. So that people become interested and use it a lot to watch movies online. With the increase in film fans, a film recommendation system is required to make a film recommendation pattern based on previous movie viewing. Therefore, this study aims to provide recommendations for viewing films using the pattern recognition method that often occurs. The technique used is sequence pattern mining using SPADE to find patterns from a group of data. SPADE's advantage is its speed in finding sequence frequencies that can be used as movie recommendation data from previous shows.