Penerapan Sistem Dinamis dalam Menganalisis Tarif Tol Krian-Legundi-Manyar-Bunder

Ahmad Mujaddid Alfani, Dwi Sukma Donoriyanto, Isna Nugraha

Abstract


Sebuah jalan tol sudah selesai dibangun di Krian-Legundi-Bunder-Manyar untuk memperlancar lalu lintas dikarenakan seringnya terjadi kemacetan. Kemacetan adalah suatu keadaan dimana pada suatu ruas jalan mengalami antrian kendaraan hingga volume ruas jalan tidak mencukupi. Kemacetan yang terjadi dijalan raya legundi disebabkan banyaknya kendaraan besar yang melewati jalur tersebut. Salah satu tujuan penulis melakukan penelitian yaitu untuk mengukur efektivitas kebijakan publik dalam analisis tarif jalan tol ini. Sistem dinamis digunakan sebagai metode untuk penelitian ini. Dikarenakan dapat mempelajari interaksi struktur, mengubahnya menjadi model matematika, dan mensimulasikannya untuk menangkap perilaku historis. Hasil perhitungan saturasi kemacetan diperoleh sebelum dan sesudah selesainya pembangunan jalan tol. Hasil perancangan model simulasi lalu lintas menunjukkan bahwa penggunaan jalan tol sangat efisien dan dapat menghilangkan masalah kemacetan. Hal ini disebabkan adanya penurunan kejenuhan kemacetan dan cenderung meningkat dari tahun ke tahun, namun dalam jumlah yang lebih sedikit. Karena itu penulis merekomendasikan kepada pengendara roda empat agar menggunakan jalan tol.


Keywords


Program simulasi

References


Adipraja, P. F. E., & Sulistyo, D. A. (2018). View of Pemodelan Sistem Dinamik untuk Prediksi Intensitas Hujan Harian di Kota Malang. Jurnal Ilmiah Teknologi Informasi Asia, 12. https://jurnal.stmikasia.ac.id/index.php/jitika/article/view/272/205

Banks, J., Carson II, J. S., Nelson, B. L., & Nicol, D. M. (2020). Discrete-Event System Part I . Introduction to Discrete-Event System Simulation. Discrete-Event System Simulation, 1, 1–325.

Faradibah, A., Faradibah, A., & Suryani, E. (2019). Pengembangan Model Simulasi Sistem Dinamik Untuk Meningkatkan Efisiensi Sistem Operasional Transportasi. Ilkom Jurnal Ilmiah, 11(1), 67–76. Https://Doi.Org/10.33096/Ilkom.V11i1.413.67-76

Gao, J., Jia, L., & Guo, J. (2019). Applying System Dynamics to Simulate the Passenger Flow in Subway Stations. Discrete Dynamics in Nature and Society, 2019. https://doi.org/10.1155/2019/7540549

Hartono, Saptaningtyas, F. Y., & Krisnawan, K. P. (2018). Dynamical analysis of Lorenz System on traffic problem in Yogyakarta, Indonesia. Journal of Physics: Conference Series, 983(1), 012092. https://doi.org/10.1088/1742-6596/983/1/012092

Hasan, N., Suryani, E., & Hendrawan, R. (2015). Analysis of Soybean Production And Demand to Develop Strategic Policy of Food Self Sufficiency : A System Dynamics Framework. Procedia - Procedia Computer Science, 72, 605–612. https://doi.org/10.1016/j.procs.2015.12.169

He, S.-K., & Li, J. (2019). A Study of Urban City Traffic Congestion Governance Effectiveness Based on System Dynamics Simulation *. International Refereed Journal of Engineering and Science, 8, 37–47. www.irjes.com

Hossain, T., & Hasan, K. (2019). Assessment of Traffic Congestion by

Traffic Flow Analysis in Pabna Town Assessment of Traffic Congestion by Traffic Flow Analysis in Pabna Town. October. https://doi.org/10.11648/j.ajtte.20190403.11

Khotimah, B. K. (2015). Teori Simulasi Dan Pemodelan: Konsep Aplikasi dan Terapan. In Aplikasi Dan Terapan Fakultas Teknik Prodi Teknik Informatika Universitas Trunojoyo Madura: Wade Group (Pertama). Wade Group.

Kim, H., Jeon, J., & Yeo, G. (2018). Forecasting Model of Air Passenger Demand Using System Dynamics. Journal of Digital Convergence, 16(5), 137–143. https://doi.org/10.14400/JDC.2018.16.5.137

Liang, Z., & Wakahara, Y. (2014). Real-time urban traffic amount prediction models for dynamic route guidance systems. Eurasip Journal on Wireless Communications and Networking, 2014(1), 1–13. https://doi.org/10.1186/1687-1499-2014-85/FIGURES/8

Mittal, P., Singh, Y., & Sharma, Y. (2015). Analysis of Dynamic Road Traffic Congestion Control (DRTCC) Techniques. American Journal of Engineering Research (AJER), 4(10), 40–47. www.ajer.org

Moganarangan, N., Balaji, N., Suresh Kumar, R. G., Balaji, S., & Palanivel, N. (n.d.). Study on Static and Dynamic Traffic Control Systems. Retrieved November 15, 2022, from http://www.ijpam.eu

Qiu, Y., Shi, X., & Shi, C. (2015). A system dynamics model for simulating the logistics demand dynamics of metropolitans: A case study of Beijing, China. Journal of Industrial Engineering and Management, 8(3), 783–803. https://doi.org/10.3926/jiem.1325

Rahman, M. R., & Akhter, S. (2016). Bi-Directional Traffic Management with Multiple Data Feeds for Dynamic Route Computation and Prediction System.

Sapiri, H., Zulkepli, J., & Ahmad, N. (n.d.). Introduction to system dynamic modelling and vensim software. 168. Retrieved November 15, 2022, from https://www.uumpress.com.my/introduction-to-system-dynamic-modelling-and-vensim-software?search=Introduction to system dynamic modelling and vensim software

Sayyadi, R., & Awasthi, A. (2016). A system dynamics based simulation model to evaluate regulatory policies for sustainable transportation planning. Https://Doi.Org/10.1080/02286203.2016.1219806, 37(1), 25–35. https://doi.org/10.1080/02286203.2016.1219806

Yu, R., Wang, G., Zheng, J., & Wang, H. (2013). Urban Road Traffic Condition Pattern Recognition Based on Support Vector Machine. Journal of Transportation Systems Engineering and Information Technology, 13(1), 130–136. https://doi.org/https://doi.org/10.1016/S1570-6672(13)60097-5




DOI: http://dx.doi.org/10.28926/briliant.v8i3.1192

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