Kajian Keterlambatan Bus Rapid Transit Dengan Pendekatan Pohon Keputusan Dan Bayesian Networks Pada Sistem Metrobus Istanbul
Kata Kunci:
Bus Rapid Transit, Pohon Keputusan, Bayesian Network, Transportasi Publik, KeterlambatanAbstrak
Sistem transportasi umum merupakan komponen penting dari infrastruktur perkotaan yang mendorong mobilitas dan pembangunan. Sistem Bus Rapid Transit (BRT) menawarkan solusi untuk mengatasi tantangan yang dihadapi oleh layanan bus tradisional. Namun, keterlambatan dalam sistem BRT dapat mengganggu efisiensi dan keandalannya. Tujuan dari penelitian ini adalah untuk menganalisis faktor-faktor kritis yang mempengaruhi keterlambatan dalam sistem Bus Rapid Transit (BRT), khususnya pada sistem Metrobus Istanbul. Studi ini dapat memberikan wawasan yang dapat ditindaklanjuti untuk mengoptimalkan operasi dan meningkatkan keandalan layanan BRT. Pohon Keputusan mengidentifikasi parameter kritis yang mempengaruhi keterlambatan, sedangkan Bayesian Networks dapat menjelaskan ketergantungan sebab akibat antar variabel. Bayesian Precedence Network yang diusulkan mengintegrasikan kedua pendekatan ini. Penelitian ini menggunakan berbagai sumber data yang beragam yang dianalisis dengan GeNIe Modeler. Hasil penelitian menunjukkan bahwa analisis keputusan efektif digunakan untuk mengukur ketidakpastian dan menilai faktor-faktor penting yang menjadi dasar perencanaan dan optimalisasi angkutan umum. Hasil penelitian selanjutnya adalah dengan tingkat keterisian penumpang sebesar 43% dapat menghasilkan probabilitas 76% untuk tidak ada keterlambatan, namun arus lalu lintas yang tinggi dapat menurunkan probabilitas tersebut menjadi 55%. Sebaliknya, kondisi cuaca yang cerah meningkatkan probabilitas tersebut menjadi 80%, sedangkan kondisi hujan dan efisiensi operasional yang tidak optimal meningkatkan risiko keterlambatan. Secara keseluruhan, studi ini memberikan cetak biru untuk mengatasi tantangan transportasi publik, memberdayakan perencana transportasi dan pembuat kebijakan untuk menciptakan jaringan angkutan umum yang lebih efisien dan dapat diandalkan.Unduhan
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Xu, Q., Liu, S., & Li, Z. (2013). Bayesian Network Models for Transportation Planning. Springer Science & Business Media.
Azam, M., Nadeem, M., Asmah Hassan, S., & Che Puan, O. (2023). Impacts of Bus Only Lanes on Signalized Intersection Under Heterogeneous Traffic Conditions. Suranaree Journal of Science and Technology, 30(1), 010185(1-11). https://doi.org/10.55766/sujst-2023-01-e01617
Barzal, V., Rößler, M., Wastian, M., Breitenecker, F., & Popper, N. (2023). Analysis of Train Delays using Bayesian Networks. SNE Simulation Notes Europe, 33(2), 89–92. https://doi.org/10.11128/sne.33.sn.10645
Bayesfusion. (2024). GeNIe Modeler. GeNIe Modeler.
Buchel, B., & Corman, F. (2021). Probabilistic Bus Delay Predictions with Bayesian Networks. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 3752–3758. https://doi.org/10.1109/ITSC48978.2021.9564537
Corman, F., & Kecman, P. (2018). Stochastic prediction of train delays in real-time using Bayesian networks. Transportation Research Part C: Emerging Technologies, 95, 599–615. https://doi.org/10.1016/j.trc.2018.08.003
de Oña, J., de Oña, R., & López, G. (2016). Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation. Transportation, 43(5), 725–747. https://doi.org/10.1007/s11116-015-9615-0
Fernandez, R. (2011). Experimental study of bus boarding and alighting times. European Transport Conference, 1–14.
Halyal, S., Mulangi, R. H., Harsha, M. M., & Laddha, H. (2022). Study on Travel Time Characteristics of Hubli-Dharwad Bus Rapid Transit System in Comparison with Heterogeneous Traffic Lane (pp. 701–712). https://doi.org/10.1007/978-981-16-4396-5_61
Huen, K., Tighe, S., & McCabe, B. (2005). Incorporating User Delay Cost in Project Selection: A Canadian Case Study. 1st Annual Inter-University Symposium on Infrastructure Management, 1–21.
Istanbul Metropolitan Municipality. (2023). Istanbul Metropolitan Municipality. Https://Www.Ibb.Istanbul/En.
Jayakumar, M., & Maji, A. (2023). Decision Tree Analyses of Safety and Comfort Perceptions for Public Transportation in Kalyan-Dombivli Region of Maharashtra. Transportation in Developing Economies, 9(2), 14. https://doi.org/10.1007/s40890-023-00184-9
Kavalov, R. (2019, October 25). Predicting NJ Transit Delays Using Decision Trees. Medium.
Koller, D., & Friedman, N. (2009). Probabilistic Graphical Models: Principles and Techniques Adaptive Computation and Machine Learning series. MIT Press.
Lauría, E. J. M. (2008). An Information-Geometric Approach to Learning Bayesian Network Topologies from Data. In Innovations in Bayesian Networks (pp. 187–217). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-85066-3_8
Levinson, H., Zimmerman, S., Clinger, J., & Rutherford, G. (2002). Bus Rapid Transit: An Overview. Journal of Public Transportation, 5(2), 1–30. https://doi.org/10.5038/2375-0901.5.2.1
Niedermayer, D. (2008). An Introduction to Bayesian Networks and Their Contemporary Applications. In Innovations in Bayesian Networks (pp. 117–130). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-85066-3_5
Seeherman, J., Sisiopiku, V. P., & Skabardonis, A. (2012). Assessment of the Impact of Weather on Freeway Operations in California. Proceedings of the 91st Transportation Research Board Annual Meeting.
Shoman, M., Aboah, A., & Adu-Gyamfi, Y. (2020). Deep Learning Framework for Predicting Bus Delays on Multiple Routes Using Heterogenous Datasets. Journal of Big Data Analytics in Transportation, 2(3), 275–290. https://doi.org/10.1007/s42421-020-00031-y
Stutz, J., & Cheeseman, P. (1994). A Short Exposition on Bayesian Inference and Probability. National Aeronautic and Space Administration Ames Research Centre: Computational Sciences Division.
Ulak, M. B., Yazici, A., & Zhang, Y. (2020). Analyzing network-wide patterns of rail transit delays using Bayesian network learning. Transportation Research Part C: Emerging Technologies, 119, 102749. https://doi.org/10.1016/j.trc.2020.102749
Vuchic, V. R. (2007). Urban Transit Systems and Technology. Wiley. https://doi.org/10.1002/9780470168066
Wang, J., Han, Y., & Li, P. (2022). Integrated Robust Optimization of Scheduling and Signal Timing for Bus Rapid Transit. Sustainability, 14(24), 16922. https://doi.org/10.3390/su142416922
Wu, W., Luo, X., & Shi, B. (2023). Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops. Systems, 11(7), 366. https://doi.org/10.3390/systems11070366
Xu, Q., Liu, S., & Li, Z. (2013). Bayesian Network Models for Transportation Planning. Springer Science & Business Media.
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2024-12-11
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Karakurt, A. (2024). Kajian Keterlambatan Bus Rapid Transit Dengan Pendekatan Pohon Keputusan Dan Bayesian Networks Pada Sistem Metrobus Istanbul. Jurnal Teknik Sipil, 21(1), 01–18. Diambil dari http://224305.koshikahk.tech/index.php/jts/article/view/9943
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