Movie recommendation using user-based collaborative filtering algorithm / Nur Ayuni Izlin Mat Ishor - Mat Ishor, Nur Ayuni Izlin (2019)
Movie recommendation is a software program known as tools that are used for providing a suggestion for movie consumers in making a decision on a movie to watch. The program will use community opinion and help other users to be more effective in identifying the recommendation based on their preferences from a possible enormous set of choice. As we know, everybody loves watching a movie, the needs of the suggestion of movie highly demand from the movie consumer. Sometimes, they will ask other opinions for recommending a movie. Based on the studies, Malaysian are unfamiliar with movie recommendation engine. Thus, the study is to explore how the recommendation engines will work and use user-based collaborative filtering as an algorithm for the movie recommendation. Evaluation for this study is to evaluate the of reliability result of recommendation engine by using the approach algorithm. It will calculate the aggregate value of similarities and the calculation will recommend a movie for the user. In developing the system, data was collected to obtain information and to produced recommendation to user. The system has been tested by the real user and it produced output with 70% of accuracy of prediction in recommending a movie to user. This prototype is very helpful for them making a decision based on the suggestion as display by the prototype of this project.