Recommender System for Tourist Destinations in Indonesia Using Matrix Factorization Method

Saputra, Danny Matthew
Angelia, Nadya
Yusliani, Novi

JITSI : Jurnal Ilmiah Teknologi Sistem Informasi
Vol 5 No 3 (2024)

Indonesia has various tourist destinations. The large number of tourist destinations makes people confused about choosing a suitable tourist destination. The recommendation system is an appropriate way to help Indonesians choose tourist destinations that suit their preferences. One recommendation system method is matrix factorization. This research uses a matrix factorization algorithm, Alternating Least Square (ALS). The dataset used is Indonesia Tourism Destination from Kaggle. Based on research that has been carried out, this algorithm is successful in predicting tourist attractions that suit users. The evaluation results are an MAE value of 1.27203388032266, while the RMSE value is 1.475271987.