ANALISIS IMPLEMENTASI ALGORITMA CLUSTERING SQUEEZER PADA SISTEM REKOMENDASI ITEM-BASED COLLABORATIVE FILTERING; ITEM-BASED COLLABORATIVE FILTERING RECOMMENDATION SYSTEM WITH SQUEEZER CLUSTERING ALGORITHM IMPLEMENTATION ANALYSIS

Supangat, Hero Satriya, Lukman Heryawan

2016 | Skripsi | FMIPA

The amount of data and the diversity of a very large data information gave rise to new problems for the user, namely the difficulty of retrieving relevant data for the user. Recommendation system using an algorithm of the item-based collaborative filtering is one of the system that are capable of providing recommendations data based on predictions from value similarity between items. Using clustering method to group similar data between each other is one way to improve the accuracy and number of recommendations. In this research will be applied to the use of clustering algorithm with a Squeezer. Application of clustering will be conducted on MovieLens’s dataset that will be processed to produce recommendations by using item-based collaborative filtering algorithm which then calculated by Mean Absolute Error (MAE) as an indicator of accuracy and the number of recommendations that are generated and compared with the results of the recommendation without clustering. The results of this research show that the implementation of clustering algorithm with squeezer increases the number of predictions with the average increase in value of 3.563% with the greater tendency of value of the threshold on the process of the formation of the cluster, the number of recommendations has increased and decreased accuracy with an average rating of 0.76% with the tendency of the larger value of the threshold on the process of the formation of clusters, value of MAE generated increases.

Kata Kunci : Recommendation system; collaborative filtering; clustering, squeezer