Analisis Konektivitas dan Optimasi Rute Perjalanan Mahasiswa UMKO: Integrasi Jarak, Aksebilitas, dan Biaya Transportasi Berbasis Teori Graf
Abstract
This study focuses on spatial connectivity analysis and determining optimal travel routes for students of Muhammadiyah University of Kotabumi (UMKO), by integrating factors such as distance, accessibility, and transportation costs. A quantitative approach is applied using a graph theory framework, where location points are nodes (vertices), and road connections are edges (edges). Route optimization is performed using a weighted graph and shortest paths with multi-criteria weighting to generate the most efficient routes. The results show that transportation connectivity patterns to the UMKO campus exhibit varying degrees of centrality. The combination of cost and accessibility factors substantially influences route preferences, such that the physically shortest route is not always optimal when traffic congestion and road quality are considered as additional cost factors. The results of this study offer recommended strategies for students in managing their daily travel, as well as for universities and local governments in formulating more rational and effective transportation policies. This research contributes to the broader debate on urban mobility optimization and graph-based spatial analysis, highlighting the significance of multi-criteria evaluation in transportation planning in within the framework of higher education.
Keywords: Graph Theory, Shortest Path, Spatial Connectivity, Transportation Optimization, UMKO
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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
Attivilli, R., Noureen, A., Rao, V. S., & Urolagin, S. (2023). A Real-Time Graphical Representation of Various Path Finding Algorithms for Route Optimisation. Lecture Notes in Networks and Systems, 653 LNNS, 479–493. https://doi.org/10.1007/978-981-99-0981-0_37
Aulia, C. N., Laia, L. H., Rahmadani, N., Febriani, P., Tia, Z., & Munte, R. (2026). Pemahaman Konsep Mahasiswa Ditinjau dari Kemampuan Menyelesaikan Persamaan Diferensial Homogen. Jurnal Cendekia: Jurnal Pendidikan Matematika, 10(2), 766–777.
Chen, C., & Tong, H. (2022). Network Connectivity: Concepts, Computation, and Optimization. Synthesis Lectures on Learning, Networks, and Algorithms, 3(1), 1–165. https://doi.org/10.2200/s01154ed1v01y202111lna028
Daniel, C. B., Saravanan, S., & Mathew, S. (2020). GIS based road connectivity evaluation using graph theory. Lecture Notes in Civil Engineering, 45, 213–226. https://doi.org/10.1007/978-981-32-9042-6_17
Dusakaeva, S. T., & Savinov, V. V. (2023). Mobile application for finding the best route on campus. Ontology of Designing, 13(3), 455–464. https://doi.org/10.18287/2223-9537-2023-13-3-455-464
Hajia, M. C. (2024). Analisis Rute Terbaik Menggunakan Shortest Route Problem Untuk Meminimalisir Waktu Tempuh Transportasi. Jurnal Gradasi Teknik Sipil, 7(2), 129–134. https://doi.org/10.31961/gradasi.v7i2.1779
Halagannanavar, S. (2025). Applied Graph Theory: Techniques and Case Studies from Computational and Scientific Domains. Advanced International Journal for Research, 6(4). https://doi.org/10.63363/aijfr.2025.v06i04.1071
Kanchana, M., & Kavitha, K. (2020). A review on transportation and smart logistics using graph theoretical approach. Advances in Mathematics: Scientific Journal, 9(8), 6327–6339. https://doi.org/10.37418/amsj.9.8.100
Mansor, N. S., Awang, H., Radzali, N. F. J., Bluszcz, A., Zolkipli, A., & Yee, P. F. (2024). Optimized Campus Navigation using Mobile App: Network Analysis for Effective Route Planning. 2024 7th International Conference on Internet Applications, Protocols, and Services, NETAPPS 2024. https://doi.org/10.1109/NETAPPS63333.2024.10823503
Marian, A. R., Serdar, M. Z., & Masad, E. (2025). Developing enhanced road network vulnerability assessment using simulation-informed weighted graphs. Transportation Research Interdisciplinary Perspectives, 34. https://doi.org/10.1016/j.trip.2025.101726
Mehedi Hassan, M., Asadujjaman, M., & Golam Robbani, M. (2023). A Modified Approach of Dijkstra’s Method for Finding Shortest Path in a Weighted Directed Graph. American Journal of Science, Engineering and Technology, 8(3), 146–151. https://doi.org/10.11648/j.ajset.20230803.14
Noschese, S., & Reichel, L. (2025). Network connectivity analysis via shortest paths. Numerical Algorithms. https://doi.org/10.1007/s11075-025-02225-3
Qin, J., He, Y., & Ni, L. (2014). Quantitative efficiency evaluation method for transportation networks. Sustainability (Switzerland), 6(12), 8364–8378. https://doi.org/10.3390/su6128364
Rahmadi, D., Putri, T. N., Ilmi, D. A., Rohmah, S. M., & Safinka, D. N. (2025). Optimasi Jalur Perjalanan Antara Jakarta Dan Surabaya Menggunakan Algoritma Dijkstra. Al-Aqlu: Jurnal Matematika, Teknik Dan Sains, 3(1), 74–81. https://doi.org/10.59896/aqlu.v3i1.140
Reza, S., Ferreira, M. C., Machado, J. J. M., & Tavares, J. M. R. S. (2024). Road networks structure analysis: A preliminary network science-based approach. Annals of Mathematics and Artificial Intelligence, 92(1), 215–234. https://doi.org/10.1007/s10472-022-09818-x
Suardinata, S., Rusmi, R., & Lubis, M. A. (2022). Determining Travel Time and Fastest Route Using Dijkstra Algorithm and Google Map. Sistemasi, 11(2), 496. https://doi.org/10.32520/stmsi.v11i2.1836
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