Abstract
The growth of e-commerce has resulted in massive product information and huge volumes of data. This results in data overload problems. In the case of e-commerce, consumers or users spend a lot of time choosing the goods they need. The urgent question to be answered at this time is how to provide solutions related to intelligent information restrictions so that the existing information is truly information that is by preferences and needs. This research performs information filtering by applying the singular value decomposition method and the Pearson similarity technique to the book recommendation system. The data used is the Book-Crossing Dataset which is the reference dataset for many research recommendation systems. The resulting recommendations are then compared with e-commerce recommendations such as amazom.com. Based on the results of the study obtained data that the results of the recommendations in this study are very good and accurate.
Highlights
Data lembaga riset pasar e-marketer, jumlah pengguna internet di Indonesia diproyeksikan mencapai 175 juta orang pada tahun 2019, atau sekitar 65,3% dari total penduduk 268 juta jiwa
The growth of e-commerce has resulted in massive product information
This results in data overload problems
Summary
Proses faktorisasi matrik akan memfaktorkan sebuah matriks menjadi lebih dari satu matriks yang lebih kecil (Wang et al, 2017). Singular Value Decomposition atau yang lebih dikenal sebagai SVD, adalah salah satu teknik dekomposisi berkaitan dengan nilai singular (singular value) suatu matriks. Matrik A = UΣ VT adalah sebuah Singular Value Decomposition untuk A dengan U merupakan matriks orthogonal m x m, V matriks orthogonal n x n dan Σ matriks diagonal m x n bernilai riil tak negatif yang disebut nilai-nilai singular. Teorema tersebut juga menyatakan bahwa matriks Amxn dapat dinyatakan sebagai dekomposisi matriks yaitu matriks U, ∑ dan V. Matriks ∑ merupakan matriks diagonal dengan elemen diagonalnya berupa nilai-nilai singular matriks A, sedangkan matriks U dan V merupakan matriks-matriks yang kolom-kolomnya berupa vektor singular kiri dan vektor singular kanan dari matriks A untuk nilai singular yang bersesuaian
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