Singular value decomposition model application for e-commerce recommendation system : Aplikasi model dekomposisi nilai tunggal untuk sistem rekomendasi e-commerce

Wervyan Shalannanda; Rafi Falih  Mulia; Arief Insanu  Muttaqien; Naufal Rafi  Hibatullah; Annisabelia  Firdaus

doi:10.35313/jitel.v2.i2.2022.103-110

Authors

Wervyan Shalannanda Institut Teknologi Bandung
Rafi Falih Mulia Institut Teknologi Bandung
Arief Insanu Muttaqien Institut Teknologi Bandung
Naufal Rafi Hibatullah Institut Teknologi Bandung
Annisabelia Firdaus Institut Teknologi Bandung

DOI:

https://doi.org/10.35313/jitel.v2.i2.2022.103-110

Keywords:

e-commerce, recommendation system, matrix-factorization, SVD, RMSE

Abstract

A recommendation system is one of the most important things in today’s technology. It can suggest products that match the user’s preferences. Many fields utilize this system, including e-commerce, using various algorithms. This paper used the matrix factorization-based algorithm, singular value decomposition (SVD), to make a recommendation system based on users’ similarities. Afterward, we implement the model against the ModCloth Amazon dataset. The results imply that the SVD algorithm yields the best accuracy compared to other matrix factorization-based algorithms with root mean square error (RMSE) of 1.055586. Then, we optimized the SVD algorithm by changing the hyperparameters of the algorithm to generate better accuracy and yield a model with an RMSE value of 1.041784.

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