Recommender System for Tourist Destinations in Indonesia Using Matrix Factorization Method

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Published: Oct 1, 2024
DOI: https://doi.org/10.62527/jitsi.5.3.254
Keywords:
Recommendation system, matrix factorization, alternating least square, tourist destinations, collaborative filtering

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Danny Matthew Saputra
Universitas Sriwijaya
Nadya Angelia
Universitas Sriwijaya
Novi Yusliani
Universitas Sriwijaya

Abstract

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.

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How to Cite
Saputra, D. M., Angelia, N., & Yusliani, N. (2024). Recommender System for Tourist Destinations in Indonesia Using Matrix Factorization Method. JITSI : Jurnal Ilmiah Teknologi Sistem Informasi, 5(3), 122 - 127. https://doi.org/10.62527/jitsi.5.3.254
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Vol. 5 No. 3 (2024)
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Articles
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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