Web-Based Bus Ticket Reservation Information System Using the Collaborative Filtering Algorithm
DOI:
https://doi.org/10.58466/wnvsh708Keywords:
Information System, Bus Ticket Reservation, Collaborative Filtering, Smart Seat Booking, WebsiteAbstract
This study aims to design and develop a web-based bus ticket reservation information system that implements a Collaborative Filtering algorithm in a smart seat booking feature. The system was developed to address the limitations of manual ticket reservation processes, including restricted access to information, long queues, and low service efficiency. The research employed the Research and Development (R&D) method using the Waterfall model, which consisted of observation, interviews, literature review, system design, implementation, and testing. System evaluation was conducted through Unit Testing, System Testing, and User Acceptance Testing (UAT). The results indicate that the system successfully provides real-time departure schedule information, facilitates online ticket reservations, and generates seat recommendations based on user preferences. All major system functions achieved a 100% success rate during testing. UAT involving 30 respondents produced a user satisfaction score of 91%, while the Collaborative Filtering algorithm achieved a seat recommendation accuracy of 85%. The system also reduced ticket booking queue times by up to 70% compared with the previous manual process..
References
[1] K. C. Laudon and J. P. Laudon, Management Information Systems: Managing the Digital Firm. Pearson, 2020. [Online]. Available: https://books.google.co.id/books?id=SZSpxAEACAAJ
[2] R. Stair and G. Reynolds, Principles of Information Systems. in MindTap Course List Series. Cengage Learning, 2018. [Online]. Available: https://books.google.co.id/books?id=av66DQAAQBAJ
[3] A. Fadhliansyah, E. Wibowo, and K. Panji, “Perancangan Sistem Pemesanan Makanan Berbasis Web pada UMKM dengan Framework Laravel,” DBESTI J. Digit. Bus. Technol. Innov., vol. 2, no. 2, pp. 246–251, 2025, doi: 10.54914/dbesti.v2i2.1950.
[4] F. Ricci, L. Rokach, and B. Shapira, Recommender Systems Handbook. Springer US, 2015. [Online]. Available: https://books.google.co.id/books?id=hGb_CgAAQBAJ
[5] J. Herlocker, J. A. Konstan, and J. Riedl, “An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms,” Inf. Retr. Boston., vol. 5, no. 4, pp. 287–310, 2002, doi: 10.1023/A:1020443909834.
[6] S. Pohan, “Synergistic Model of Parent and Teacher Collaboration in Elementary School Character Education,” Fitrah J. Pendidik., vol. 1, no. 1, pp. 1137–1150, 2025.
[7] J. W. Creswell and C. N. Poth, Qualitative Inquiry and Research Design: Choosing Among Five Approaches. SAGE Publications, 2024. [Online]. Available: https://books.google.co.id/books?id=nFr2EAAAQBAJ
[8] M. B. Miles, A. Huberman, M. and Saldana, and Johnny, Qualitative Data Analysis: A Methods Sourcebook, 4th ed. Thousand Oaks, CA: SAGE Publication, 2020.
[9] P. M. Shrestha, “Impact of Service Quality on Customer Satisfaction and Loyalty,” Manag. Dyn., vol. 24, no. 2, pp. 71–80, 2021, doi: 10.3126/md.v24i2.50041.
[10] K. Wau, “Pengembangan Sistem Informasi Persediaan Gudang Berbasis Website Dengan Metode Waterfall,” J. Tek. Komputer, Agroteknologi Dan Sains, vol. 1, no. 1, pp. 10–23, 2022, doi: 10.56248/marostek.v1i1.8.
[11] U. Flick, “Triangulation in Data Collection,” in The SAGE Handbook of Qualitative Data Collection, 2018. doi: 10.4135/9781526416070.n34.
[12] A. Bharadwaj, O. A. El Sawy, P. A. Pavlou, and N. Venkatraman, “Digital Business Strategy: Toward a Next Generation of Insights,” Manag. Inf. Syst. Q., vol. 37, no. 2, pp. 471–482, Jun. 2013, doi: 10.25300/MISQ/2013/37:2.3.
[13] P. Gomber, R. J. Kauffman, C. Parker, and B. W. Weber, “On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services,” J. Manag. Inf. Syst., vol. 35, no. 1, pp. 220–265, Jan. 2018, doi: 10.1080/07421222.2018.1440766.
[14] J. Aravind, A. Lukose, J. Joseph, M. S. Bindhya, and B. Simon, “Bibliometric Mapping of Social Media Banking: Analyzing Research Trends and Developments,” J. Scientometr. Res., vol. 14, no. 2, pp. 493–509, doi: 10.5530/jscires.20251462.
[15] I. Sommerville, Software Engineering, Global Edition. Pearson Education, 2016. [Online]. Available: https://books.google.co.id/books?id=W_LjCwAAQBAJ
[16] B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, “Item-based collaborative filtering recommendation algorithms,” in Proceedings of the 10th International Conference on World Wide Web, in WWW ’01. New York, NY, USA: Association for Computing Machinery, 2001, pp. 285–295. doi: 10.1145/371920.372071.
[17] D. Norman, The Design of Everyday Things: Revised and Expanded Edition. Basic Books, 2013. [Online]. Available: https://books.google.co.id/books?id=I1o4DgAAQBAJ
[18] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User Acceptance of Information Technology: Toward A Unified View1,” Manag. Inf. Syst. Q., vol. 27, no. 3, pp. 425–478, Sep. 2003, doi: 10.2307/30036540.
[19] L. Satchell, P. Morris, C. Mills, L. O’Reilly, P. Marshman, and L. Akehurst, “Evidence of Big Five and Aggressive Personalities in Gait Biomechanics,” J. Nonverbal Behav., vol. 41, no. 1, pp. 35–44, 2017, doi: 10.1007/s10919-016-0240-1.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Novtra Refiardiansyah Nasution, Aninda Muliani Harahap, Adnan Buyung Nasution
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
