Sistem Rekomendasi Suku Cadang Berdasarkan Item Based Filtering

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Christian Wibisono
Lucky Surya Haryadi
Juan Elisha Widyaya
Swat Lie Liliawati


Replaceable spare part on workshop have many transaction and possibility thus recommender system is needed to simplify the selection process. We propose recommender system with item collaborative filtering, with high data sparsity. With Single Value Decomposition we reduce the matriks to improve the system and decrease “noise” value. Model will be evaluated using MAE, RMSE, and FCP metrics. The results of recommendation model are MAE = 1.2752, RMSE = 1.4882, dan FCP = 0.4947.


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How to Cite
C. Wibisono, L. S. Haryadi, J. E. Widyaya, and S. L. Liliawati, “Sistem Rekomendasi Suku Cadang Berdasarkan Item Based Filtering”, JuTISI, vol. 7, no. 1, Apr. 2021.