Penerapan Teori Graf dalam Optimasi Jaringan Transportasi Perkotaan : Systematic Literature Review (SLR)

Authors

  • Fara Syifa Nabila Siregar Universitas Islam Negeri Sumatera Utara
  • Shilva Syahbina Universitas Islam Negeri Sumatera Utara
  • Andespa Siregar Universitas Islam Negeri Sumatera Utara
  • Sahrul Romadona Universitas Islam Negeri Sumatera Utara
  • Siti Salamah Br Ginting Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.61132/arjuna.v3i6.2631

Keywords:

Graph Theory, PRISMA, Systematic Literature Review, Transportation Optimization, Urban Networks

Abstract

The increasingly complex growth of urban mobility requires an analytical approach that can optimize transportation networks effectively and sustainably. Graph theory is one of the mathematical methods widely used in modeling road network structures and analyzing inter-node connectivity to obtain more efficient routing and network optimization solutions. This study aims to systematically review the development of graph theory application in urban transportation network optimization through the Systematic Literature Review (SLR) method. The review was conducted following the PRISMA 2020 protocol for articles published between 2020 and 2025. A total of ten articles met the inclusion criteria and were analyzed in depth. The review results show that graph algorithms such as Dijkstra, Bellman–Ford, Floyd–Warshall, Minimum Spanning Tree (MST), Graph Neural Network (GNN), and the hybrid Dijkstra–A* method can improve route efficiency, reduce travel time, improve navigation accuracy, and strengthen congestion prediction capabilities. In general, graph theory has proven to be an effective and adaptive approach in supporting urban transportation network planning and management. Further research is recommended to integrate graph theory with real-time traffic data and artificial intelligence technology to improve the accuracy and responsiveness of modern transportation systems.

Downloads

Download data is not yet available.

References

Agusnur, A. (2025). Peran Teori Graf dalam Perancangan Jaringan Transportasi Cerdas. Jurnal Matematika Dan Aplikasi, 1(1), 33–39.

Ahsanti, A., Insyafilla, A., Fatimah, N. N., Wahyuni, W. C. D., & Rahmadi, D. (2025). Optimalisasi Jaringan Jalan Antar Kecamatan dengan Minimum Spanning Tree dan Algoritma Prim di Kabupaten Ngawi. Basis : Jurnal Ilmiah Matematika, 4(1), 1–11. https://doi.org/10.30872/basis.v4i1.1451

Amelia Vega S. Meliala, R., Nabila Harahap, S., Haikal Al-Majid, M., & Harliana, P. (2024). Optimalisasi Rute Transportasi Menggunakan Algoritma Graf. JATI (Jurnal Mahasiswa Teknik Informatika), 8(6), 12625–12632. https://doi.org/10.36040/jati.v8i6.11996

Chulasoh, B. S., Bukhori, M. I., & Muttaqin, P. S. (2025). Penerapan Bellmann-Ford Algorithm Dalam Pencarian Rute Terpendek Distribusi Suku Cadang Di Kota Bandung. Jurnal Ilmiah Teknologi Infomasi Terapan, 11(3), 137–144. https://doi.org/10.33197/jitter.vol11.iss3.2025.2935

Feng, Y., Zhang, W., & Zhu, J. (2023). Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems. Applied Sciences (Switzerland), 13(24). https://doi.org/10.3390/app132413090

Gorji, M. A., Akbarzadeh, M., & Shetab-Boushehri, S. N. (2022). Evaluation and improvement of the urban transportation networks resilience in short-term non-recurring traffic congestion: a novel graph connectivity-based criteria. Transportation Engineering, 10(May), 100152. https://doi.org/10.1016/j.treng.2022.100152

Grujic, Z., & Grujic, B. (2025). Optimal Routing in Urban Road Networks: A Graph-Based Approach Using Dijkstra’s Algorithm. Applied Sciences (Switzerland), 15(8). https://doi.org/10.3390/app15084162

Guze, S. (2019). Graph theory approach to the vulnerability of transportation networks. Algorithms, 12(2). https://doi.org/10.3390/A12120270

Hemdan, S. M., Ramadan, M., & Othman, A. (2025). Exploring Aswan’s Transportation Network through Graph Theory: Metrics and Insights. Aswan University Journal of Sciences and Technology, 5(2), 27–36. https://doi.org/10.21608/aujst.2025.352776.1163

Lin, Z., Cao, Y., Liu, H., Li, J., & Zhao, S. (2021). Research on optimization of urban public transport network based on complex network theory. Symmetry, 13(12). https://doi.org/10.3390/sym13122436

Marpaung, F., & Sari, N. (2021). Maximal Flow Of Transportation Network In Medan City Using Ford-Fulkerson Algorithm. International Journal of Science, 100–106. http://ijstm.inarah.co.id

Maulana, A. (2025). Penerapan Kruskal Minimum Spanning Tree Pada Optimasi Rute Wisata Bojong Kabupaten Tegal. 2(1).

Mochammad Darip, Sigit Auliana, Anam, A. K., Parimin, & Anugerah Agung. (2024). Comparison of BFS and DFS Algorithm for Routes to Historical-Cultural Tourism Locations in Banten Province. Journal of Advances in Information and Industrial Technology, 6(2), 113–122. https://doi.org/10.52435/jaiit.v6i2.560

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., Antes, G., Atkins, D., Barbour, V., Barrowman, N., Berlin, J. A., Clark, J., Clarke, M., Cook, D., D’Amico, R., Deeks, J. J., Devereaux, P. J., Dickersin, K., Egger, M., Ernst, E., Gøtzsche, P. C., … Tugwell, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7). https://doi.org/10.1371/journal.pmed.1000097

Monteiro, J., Robertson, G., & Atkinson, B. (2012). Networks in transportation - Theory. Canadian Transportation Research Forum, 1–21.

Muthuvel, P., Pandiyan, G., Manickam, S., & Rajesh, C. (2025). Optimizing Road Networks: A Graph-Based Analysis with Path-finding and Learning Algorithms. International Journal of Intelligent Transportation Systems Research, 23(1), 315–329. https://doi.org/10.1007/s13177-024-00453-w

Odiagbe, M., Osanaiye, O., & Oshiga, O. (2025). Traffic Prediction and Congestion Control Using an Enhanced-Graph Neural Network. International Journal of Transport Development and Integration, 9(3), 645–655. https://doi.org/10.18280/ijtdi.090317

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Bmj, 372. https://doi.org/10.1136/bmj.n71

Pinandito, A., Kharisma, A. P., Akbar, M. A., & Saputra, M. C. (2024). Peningkatan Performa Komputasi Sistem Navigasi Transportasi Publik Pada Perangkat Bergerak Melalui Penerapan Teknik Kompresi Data dan Penyederhanaan Graf. Jurnal Teknologi Informasi Dan Ilmu Komputer, 11(6), 1185–1196. https://doi.org/10.25126/jtiik.2024118054

Tampubolon, A. J., Ricardo, E., Simbolon, D. S., Pasaribu, A., Panggabean, J., & Sipayung, S. P. (2025). Implementasi Algoritma Dijkstra Menentukan Rute Terpendek Dari Unika St. Thomas Menuju Kantor dinas kependudukan Kota Medan. Jurnal Minfo Polgan, 14(1), 1274–1286. https://doi.org/10.33395/jmp.v14i1.14997

Yang, H., Li, Z., & Qi, Y. (2024). Predicting traffic propagation flow in urban road network with multi-graph convolutional network. Complex and Intelligent Systems, 10(1), 23–35. https://doi.org/10.1007/s40747-023-01099-z

Downloads

Published

2025-12-30

How to Cite

Fara Syifa Nabila Siregar, Shilva Syahbina, Andespa Siregar, Sahrul Romadona, & Siti Salamah Br Ginting. (2025). Penerapan Teori Graf dalam Optimasi Jaringan Transportasi Perkotaan : Systematic Literature Review (SLR). Jurnal Arjuna : Publikasi Ilmu Pendidikan, Bahasa Dan Matematika, 3(6), 159–169. https://doi.org/10.61132/arjuna.v3i6.2631

Similar Articles

<< < 3 4 5 6 7 8 9 10 11 12 > >> 

You may also start an advanced similarity search for this article.