Perbandingan Metode Collaborative Filtering dan Hybrid Semantic Similarity

Imam Fahrurrozi (Program Studi Komputer dan Sistem Informasi, Departemen Teknik Elektro dan Informatika, Sekolah Vokasi, Universitas Gadjah Mada)
Estu Muh Dwi Admoko (Program Studi Komputer dan Sistem Informasi, Departemen Teknik Elektro dan Informatika, Sekolah Vokasi, Universitas Gadjah Mada)
Anang Susilo (Program Studi Komputer dan Sistem Informasi, Departemen Teknik Elektro dan Informatika, Sekolah Vokasi, Universitas Gadjah Mada)

Jurnal Nasional Teknologi Terapan
Vol 2, No 3 (2018): NOVEMBER

Recommender system is a component which has been developed for online commerce purposes. In this issue, one of the popular methods that has been widely used is collaborative filtering. However, this method has some drawbacks and needs to be improved. Therefore, in this research a combination of Collaborative Filtering (CF) and semantic similarity method has been compare with original CF, and the result expected reducing some deficiencies on the original collaborative filtering method. Based on the performance tests, the results conclude that the combination can reduce some weaknesses on the original collaborative filtering, especially on the cold-start item and sparsity issue.