Personalized Indonesian movie recommendation system based on ratings using association rules
There is a raise of popularity watching movies online in online streaming websites such as iFlix, netFlix, etc using various devices such as computer, laptop, tablet and even phone. With the raise of popularity, the movie contents and users grows equivalently as according that cause difficulties for users to find their personal favorite movies out of so many movies available. This research objective is to develop a personalized recommendation system based on movie ratings. We extract the association rules using apriori based on the processed data gathered from the movie, post process it to fit the result to then show the recommendation contents based on the calculation. By utilizing and tuning the association rules, experiment result shows that this calculation produces reliable recommendation movie contents.rn
B02495 | (Rack Thesis) | Available |
No other version available