Sistem Rekomendasi Suku Cadang Berdasarkan Item Based Filtering
Christian Wibisono, Lucky Surya Haryadi, Juan Elisha Widyaya, Swat Lie Liliawati · Jurnal Teknik Informatika dan Sistem Informasi · 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.