PERBANDINGAN METODE COLLABORATIVE FILTERING DAN HYBRID JIANG-CONRATH

Penulis

  • Imam Fahrurrozi Program Studi Komputer dan Sistem Informasi/Departemen Teknik Elektro dan Informatika/Sekolah Vokasi, Universitas Gadjah Mada, Indonesia Penulis
  • Alviska Galuh Nurwana Program Studi Komputer dan Sistem Informasi/Departemen Teknik Elektro dan Informatika/Sekolah Vokasi, Universitas Gadjah Mada, Indonesia Penulis

DOI:

https://doi.org/10.61805/fahma.v17i1.82

Kata Kunci:

recommender system, collaborative filtering, jiang-conrath, combination, cold-start item, sparsity data

Abstrak

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 hybrid jiang-conrath 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.

Unduhan

Data unduhan tidak tersedia.

Referensi

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Unduhan

Diterbitkan

31-01-2019

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Cara Mengutip

PERBANDINGAN METODE COLLABORATIVE FILTERING DAN HYBRID JIANG-CONRATH. (2019). Jurnal Informatika Komputer, Bisnis Dan Manajemen, 17(1), 67-76. https://doi.org/10.61805/fahma.v17i1.82

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