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Imam Fahrurrozi
Program Studi Komputer dan Sistem Informasi, Departemen Teknik Elektro dan Informatika, Sekolah Vokasi, Universitas Gadjah Mada
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science

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Journal : Jurnal Nasional Teknologi Terapan

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Perbandingan Metode Collaborative Filtering dan Hybrid Semantic Similarity Imam Fahrurrozi; Estu Muh Dwi Admoko; Anang Susilo
Jurnal Nasional Teknologi Terapan (JNTT) Vol 2, No 3 (2018): NOVEMBER
Publisher : Penelitian dan Pengabdian Kepada Masyarakat Sekolah Vokasi Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (173.711 KB) | DOI: 10.22146/jntt.44938

Abstract

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.
Co-Authors Anang Susilo Atikah Suriani Estu Muh Dwi Admoko Muhammad Rifqi Al Fauzan Rendra Dwi Firmansyah Ronald Adrian Tika Erna Putri