Sistem Rekomendasi Suku Cadang Berdasarkan Item Based Filtering - Christian Wibisono; Lucky Surya Haryadi; Juan Elisha Widyaya; Swat Lie Liliawati (Maranatha University Press, 2021)
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.