Web Recommended System Library Book Selection Using Item Based Collaborative Filtering Method

The recommendation system is one feature that is widely used by software today. The recommendation system is Beneficial for users to make it easier for users to make a book selection by providing book recommendations that may be following the desired book preferences. The recommendation system in this research uses the Item Based Collaborative Filtering method, where this method is the result of combining Collaborative Filtering and Item Based. Collaborative Filtering uses the rating matrix to calculate ratings, and Item Based uses book attributes to calculate similarity attributes between books.The collaborative filtering method has been used successfully in several applications. The Collaborative Filtering method predicts user preferences for items in a word-of-month manner, i.e. user preferences are determined by considering opinions in the form of preference ratings.Based on the results of tests conducted, the minimum MAE generated by the system is 0.018 with a maximum accuracy of 99.63% contained in the first test, meaning that the more variable data rating data, the higher the MAE value generated.