Conversational Recommender System for Impromptu Tourists to Recommend Tourist Routes Using Haversine Formula

Authors

DOI:

https://doi.org/10.30865/mib.v5i4.3229

Keywords:

Recommender System, Traveler, preference, Conversational Recommender System (CRS), Haversine Formula

Abstract

In this paper, we use two terms to describe tourists, i.e. planned tourists and impromptu tourists. Planned tourists are tourists who intentionally travel. Meanwhile, impromptu tourists are those who accidentally become tourists because they are in a new area for an activity. Previously, tourists who were going to travel usually relied on the services of travel agents to get recommendations for tourist attractions, different from impromptu tourists this was not done before. Impromptu tourists sometimes do not have much time to carry out tourism activities so that impromptu tourists only visit the closest tourist attractions from their location. Lack of experience in a new area and only relying on information on the internet makes it difficult for tourists to find tourist attractions based on their preferences. One solution to this problem is that a system is needed that can recommend tourist attractions in terms of distance by considering tourist preferences. In this study, we developed a conversational recommender system (CRS) to obtain user preferences. For the method we use the Haversine Formula to calculate the distance. The results of this study are a web application that recommends tourist attractions and routes to several tourist attractions, which can be done at one time. Based on the evaluation of the time complexity in the route search, linear complexity is obtained which shows good performance with optimal conditions.

Author Biography

Z K Abdurahman Baizal, Telkom University, Bandung

School of Computing

References

L. Marlinda, “Sistem Pendukung Keputusan Pemilihan Tempat Wisata Yogyakarta Menggunakan Metode ELimination Et Choix Traduisan La RealitA (ELECTRE),†Jurnal.Umj.Ac.Id/Index.Php/Semnastek, no. November, pp. 1–7, 2016, [Online]. Available: https://media.neliti.com/media/publications/174107-ID-none.pdf.

E. D. Pratiwi, M. S. Sugandi, U. Telkom, T. I. Simbolik, and T. I. Simbolik, “Perilaku Komunikasi Antara Pemandu Wisata Dan Wisatawan Dalam,†vol. 8, no. 1, pp. 691–703, 2021.

A. Arief, Widyawan, and B. Sunafri Hantono, “Rancang Bangun Sistem Rekomendasi Pariwisata Mobile dengan Menggunakan Metode Collaborative Filtering dan Location Based Filtering,†Jnteti, vol. 1, no. 3, 2012, [Online]. Available: http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/129.

B. D. Fatmawatie and Z. K. A. Baizal, “Tourism recommender system using Case Based Reasoning Approach (Case Study: Bandung Raya Area),†J. Phys. Conf. Ser., vol. 1192, no. 1, pp. 0–7, 2019, doi: 10.1088/1742-6596/1192/1/012050.

R. R. Al Hakim, A. Muchsin, A. Pangestu, and A. Jaenul, “Pendekatan Postulat Jarak Terdekat Rumah Sakit Rujukan Covid-19 di BARLINGMASCAKEB Indonesia Menggunakan Haversine Formula,†KONSTELASI Konvergensi Teknol. dan Sist. Inf., vol. 1, no. 1, pp. 12–19, 2021, doi: 10.31849/semaster.v1i1.6033.

Z. K. A. Baizal, K. M. Lhaksmana, A. A. Rahmawati, M. Kirom, and Z. Mubarok, “Travel route scheduling based on user’s preferences using simulated annealing,†Int. J. Electr. Comput. Eng., vol. 9, no. 2, pp. 1275–1287, 2019, doi: 10.11591/ijpeds.v9i2.pp1275-1287.

L. A. Selano, S. Nadjamuddin, and W. K. Bandung, “Aplikasi Pencarian Objek Wisata Bandung Raya Berbasis Mobile ( Study Kasus : Dinas Kebudayaan Dan Pariwisata Kota Bandung , Kabupaten Bandung , Kabupaten Bandung Barat , Kabupaten Sumedang Dan Kota Cimahi ),†2017, vol. VII, no. 1, pp. 30–43.

A. Kurniawan, D. O. Siahaan, and A. Wibisono, “Sistem Promosi Pariwisata Menggunakan Ontologi,†J. Tek. ITS, vol. 2, no. 1, p. 146539, 2013, [Online]. Available: http://ejurnal.its.ac.id/index.php/teknik/article/view/2740.

Z. K. A. Baizal, D. Tarwidi, and B. Wijaya, “Tourism Destination Recommendation Using Ontology-based Conversational Recommender System.â€

R. Systems et al., “Tourism recommendation system based in user’s profile and functionality levels,†J. Phys. Conf. Ser., vol. 2, no. 1, pp. 93–97, 2019, doi: 10.1088/1742-6596/1192/1/012020.

M. S. Ayundhita, Z. K. A. Baizal, and Y. Sibaroni, “Ontology-based conversational recommender system for recommending laptop,†J. Phys. Conf. Ser., vol. 1192, no. 1, 2019, doi: 10.1088/1742-6596/1192/1/012020.

M. S. Aktas, M. Pierce, G. C. Fox, and D. Leake, “A web based conversational case-based recommender system for ontology aided metadata discovery,†Proc. - IEEE/ACM Int. Work. Grid Comput., pp. 69–75, 2004, doi: 10.1109/GRID.2004.6.

S. Suriati and M. Dwiastuti, “Context-aware recommender system based on ontology for recommending tourist destinations at Bandung Context-aware recommender system based on ontology for recommending tourist destinations at Bandung,†2016.

R. Sastriani, Z. K. A. Baizal, and ..., “Ontology-Based Semantic Search on Tourism Information Search System,†Indones. J. …, vol. 5, no. March, pp. 103–114, 2020, doi: 10.21108/indojc.2020.5.1.397.

S. Purnama, D. A. Megawaty, and Y. Fernando, “Penerapan Algoritma A Star Untuk Penentuan Jarak Terdekat Wisata Kuliner di Kota Bandarlampung,†J. Teknoinfo, vol. 12, no. 1, p. 28, 2018, doi: 10.33365/jti.v12i1.37.

A. Fauzi, F. Pernando, and M. Raharjo, “Penerapan Metode Haversine Formula Pada Aplikasi Pencarian Lokasi Tempat Tambal Ban Kendaraan Bermotor Berbasis Mobile Android,†J. Tek. Komput., vol. 4, no. 2, pp. 56–63, 2018, doi: 10.31294/jtk.v4i2.3512.

S. Subandijo, “Efisiensi Algoritma dan Notasi O-Besar,†ComTech Comput. Math. Eng. Appl., vol. 2, no. 2, p. 849, 2011, doi: 10.21512/comtech.v2i2.2835.

H. Kabetta, “Analisis Kompleksitas Waktu Algoritma Kriptografi Elgamal Dan Data Encryption Standard,†Teknikom, vol. 1, no. 1, pp. 13–18, 2017, doi: 10.31227/osf.io/saq

Downloads

Published

2021-10-26

Issue

Vol. 5 No. 4 (2021): Oktober 2021

Section

Articles

License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).