Implementation of the Apriori Algorithm for Film Recommendations based on Director and Movie Duration - Kamal Zaki Abdurrafi; Ryan Reliovani; Nina Nadia Syafitri Husein; Cecep Rafqi Al Husni; Muhammad Azka Khowarizmi; Karima Marwazia Shaliha (UIN Sunan Gunung Djati Bandung, 2021)
The Film Industry is an industry that never dies, in Indonesia itself for the past three years the number of film viewers has continued to increase. Reporting from the indonesia.go.id page in 2018 the number of film productions produced is almost 200 titles, from the large number of films produced, of course film lovers have different tastes for films, one way that can be used to increase attractiveness in films is the existence of film recommendation system based on film trends based on the director and how long the ideal film duration for prospective viewers. The algorithm chosen in this research is to find and determine the pattern of director selection and film duration available in 1001 data on film data, the data will be divided into lists consisting of 30 items. The results of this study are film recommendations based on a priori algorithm with the director and film duration as a reference for association rules. The results obtained from this study are that the apriori algorithm can be implemented in film recommendations based on the director and film duration.