Tourism Recommendation System using Weighted Hybrid Method in Bali Island
Abstract
Tourism is a promising sector for global economic growth, as it has shown resilience during the global crisis. In Bali, tourism is a leading sector alongside agriculture and industry, making a significant contribution to regional and community development. However, Bali's popularity as a sought-after tourist destination also raises the need for an information system that can provide destination recommendations. To overcome the problem of information overload, a recommendation system is needed. This study tested the tourism recommendation system in Bali using the Weighted Hybrid technique which combines two methods, namely Collaborative Filtering and Content-Based using the weighted value technique. Collaborative Filtering, Content-Based, and Weighted Hybrid approaches will be compared in this study to improve the performance and accuracy of current recommendation systems. Utilizing the MAE, MSE, and RMSE values, the evaluation is carried out by comparing the evaluation matrices of the three Collaborative Filtering, Content-Based, and Weighted Hybrid methods. With MAE, MSE, and RMSE values of 0.4854, 0.4034, and 0.6351 respectively, the evaluation findings show that the Weighted Hybrid technique beats Collaborative Filtering and Content-Based with a weight value of 0.4.
Keywords
Full Text:
PDFReferences
V. Paramarta, R. Roro Vemmi Kesuma Dewi, F. Rahmanita, S. Hidayati, and D. Sunarsi, “Halal Tourism in Indonesia: Regional Regulation and Indonesian Ulama Council Perspective,â€, vol 10, pp. 497-505, Feb. 2021, doi: 10.6000/1929-4409.2021.10.58.
A.A.A Ribeka Martha Purwahita, Putu Bagus Wisnu Wardhana, I Ketut Ardiasa, and I Made Winia, “Dampak Covid-19 terhadap Pariwisata Bali Ditinjau dari Sektor Sosial, Ekonomi, dan Lingkungan (Sebuah Tinjauan Pustaka),†Jurnal Kajian dan Terapan Pariwisata, vol. 1, no. 2, pp. 68–80, May. 2021, doi: 10.53356/diparojs.v1i2.29.
F. Ricci, B. Shapira, and L. Rokach, “Recommender systems: Introduction and challenges,†in Recommender Systems Handbook, Second Edition, Springer US, 2015, pp. 1–34. doi: 10.1007/978-1-4899-7637-6_1.
J. Cristy Patty, E. Thea Kirana, M. Sandra Diamond Khrismayanti Giri, M. Teknik Informatika, and U. Atma Jaya Yogyakarta, “Recommendations System for Purchase of Cosmetics Using Content-Based Filtering,†International Journal of Computer Engineering and Information Technology, vol. 10, no. 1, pp. 1–5, Jan. 2018, [Online]. Available: www.google.com
A. Paullier and R. Sotelo, “A recommender systems’ algorithm evaluation using the lenskit library and movielens databases,†in IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB, IEEE Computer Society, pp. 1-7, Oct. 2020. doi: 10.1109/BMSB49480.2020.9379914.
F. Fessahaye et al., “T-RECSYS: A Novel Music Recommendation System Using Deep Learning.â€, pp. 1-6, Jan. 2019, doi: 10.1109/ICCE.2019.8662028
R. Singh and S. Vijaykumar, “A Recommender System for YouTube Video based on deep neural network,†International Journal of Computer Sciences and Engineering, vol. 7, no. 6, pp. 160–163, Jun. 2019, doi: 10.26438/ijcse/v7i6.160163.
R. H. #1 and Z. K. A. B. #2, “E-Commerce Recommender System on the Shopee Platform Using Apriori Algorithmâ€, vol. 7, no. 2, pp. 53-64, Aug. 2022, doi: 10.34818/indojc.2022.7.2.650.
M. H. Mohamed, M. H. Khafagy, and M. H. Ibrahim, “Recommender Systems Challenges and Solutions Survey,†in Proceedings of 2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019, Institute of Electrical and Electronics Engineers Inc., Feb. 2019, pp. 149–155. doi: 10.1109/ITCE.2019.8646645.
N. Rajabpour, A. Mohammadighavam, A. Naserasadi, and M. Estilayee, “TFR: A Tourist Food Recommender System based on Collaborative Filtering,†Int J Comput Appl, vol. 181, no. 11, pp. 30–39, Aug. 2018, doi: 10.5120/ijca2018917695.
L. Jiang, Y. Cheng, L. Yang, J. Li, H. Yan, and X. Wang, “A trust-based collaborative filtering algorithm for E-commerce recommendation system,†J Ambient Intell Humaniz Comput, vol. 10, no. 8, pp. 3023–3034, Aug. 2019, doi: 10.1007/s12652-018-0928-7.
K. Wahyudi, J. Latupapua, R. Chandra, and A. S. Girsang, “Hotel content-based recommendation system,†in Journal of Physics: Conference Series, Institute of Physics Publishing, vol. 1485, no. 1, May. 2020. doi: 10.1088/1742-6596/1485/1/012017.
J. Singh, “Collaborative filtering based hybrid music recommendation system,†in Proceedings of the 3rd International Conference on Intelligent Sustainable Systems, ICISS 2020, Institute of Electrical and Electronics Engineers Inc., Dec. 2020, pp. 186–190. doi: 10.1109/ICISS49785.2020.9315913.
A. Melese, “Food and Restaurant Recommendation System Using Hybrid Filtering Mechanism,†Monthly Journal by TWASP, vol. 4, no. 4, pp. 268–281, Apr. 2021, doi: 10.5281/zenodo.4712849.
I. K. G. Aryadi Pramarta and Z. K. A. Baizal, “HYBRID RECOMMENDER SYSTEM USING SINGULAR VALUE DECOMPOSITION AND SUPPORT VECTOR MACHINE IN BALI TOURISM.â€, vol. 7, no. 2, pp. 408-418, Jun. 2022, doi: 10.29100/jipi.v7i2.2770
Y. Amri, A. #1, Z. K. A. B. #2, A. Toto, and W. #3, “Tourism Recommender System using Weighted Parallel Hybrid Method with Singular Value Decompositionâ€, vol. 6, no 2, pp. 53-64, Sep. 2021, doi: 10.34818/indojc.2021.6.2.579.
W. Wang and Y. Lu, “Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model,†in IOP Conference Series: Materials Science and Engineering, Institute of Physics Publishing, vol. 324, no. 1, Apr. 2018. doi: 10.1088/1757-899X/324/1/012049.
D. Sarkar, Text Analytics with Python. Apress, 2019, pp. 1-674, doi: 10.1007/978-1-4842-4354-1.
G. Yunanda, D. Nurjanah, and S. Meliana, “Recommendation System from Microsoft News Data using TF-IDF and Cosine Similarity Methods,†Building of Informatics, Technology and Science (BITS), vol. 4, no. 1, pp. 277-284, Jun. 2022, doi: 10.47065/bits.v4i1.1670.
N. Ifada, T. F. Rahman, and M. K. Sophan, “Comparing collaborative filtering and hybrid based approaches for movie recommendation,†in Proceeding - 6th Information Technology International Seminar, ITIS 2020, Institute of Electrical and Electronics Engineers Inc., Oct. 2020, pp. 219–223. doi: 10.1109/ITIS50118.2020.9321014.
Hong-Quan Do, Tuan-Hiep Le, Byeongnam Yoon, “Dynamic Weighted Hybrid Recommender Systemsâ€. In 2020 22nd International Conference on Advanced Communication Technology (ICACT), pp. 644-650, Feb. 2020, doi: 10.23919/ICACT48636.2020.9061465
DOI: https://doi.org/10.30865/mib.v7i3.6409
Refbacks
- There are currently no refbacks.
Copyright (c) 2023 JURNAL MEDIA INFORMATIKA BUDIDARMA
This work is licensed under a Creative Commons Attribution 4.0 International License.
JURNAL MEDIA INFORMATIKA BUDIDARMA
Universitas Budi Darma
Secretariat: Sisingamangaraja No. 338 Telp 061-7875998
Email: mib.stmikbd@gmail.com
This work is licensed under a Creative Commons Attribution 4.0 International License.