PENERAPAN TEKNOLOGI WEB UNTUK SMART TRANSPORTATION DAN MANAJEMEN ARMADA DI ERA IOT SYSTEMATIC LITERATURE REVIEW 2020–2025

Penulis

  • Aril Yusuf Universitas Muhammadiyah Kolaka Utara, Lasusua, Indonesia
  • Muh. Afriansa Universitas Muhammadiyah Kolaka Utara, Lasusua, Indonesia
  • Annisa Annisa Universitas Muhammadiyah Kolaka Utara, Lasusua, Indonesia
  • Serli Serli Universitas Muhammadiyah Kolaka Utara, Lasusua, Indonesia
  • Wahda Mutmainna Universitas Muhammadiyah Kolaka Utara, Lasusua, Indonesia
  • Dayanti Dayanti Universitas Muhammadiyah Kolaka Utara, Lasusua, Indonesia

DOI:

https://doi.org/10.64476/jtbc.v2i1.22

Kata Kunci:

smart transportation, fleet management, iot, web technology, real - time monitoring, Fleet Management System, Telematics, Cloud Computing, Predictive Maintenance, Route Optimization, Machine Learning, Big Data Analytics

Abstrak

Perkembangan Internet of Things (IoT) telah mentransformasi sistem transportasi cerdas dan manajemen armada modern, dengan teknologi web sebagai platform integrasi yang menghubungkan perangkat IoT, sistem manajemen, dan pengguna. Penelitian sistematik ini mengkaji implementasi teknologi web untuk monitoring kendaraan real-time, optimasi rute berbasis machine learning, predictive maintenance, dan dashboard analytics. Arsitektur sistem melibatkan empat layer: IoT (sensor kendaraan), komunikasi (MQTT, REST API, WebSocket), cloud computing (big data processing), dan presentasi (Progressive Web Apps, React/Vue.js). Sistem mengintegrasikan data GPS, telemetri, konsumsi bahan bakar, perilaku mengemudi, dan kondisi lalu lintas untuk optimasi operasional. Hasil kajian menunjukkan peningkatan efisiensi operasional 30-40%, pengurangan biaya maintenance 25%, penurunan konsumsi bahan bakar 15-20%, dan reduksi incident rate 35%. Tantangan meliputi keamanan data, interoperabilitas sistem, skalabilitas infrastruktur, standardisasi protokol, dan integrasi dengan legacy system. Penelitian memberikan reference architecture, framework evaluasi teknologi, best practices, dan roadmap transformasi digital untuk berbagai skala organisasi dan jenis armada.

Unduhan

Data unduhan belum tersedia.

Referensi

Oladimeji, D., Gupta, K., Kose, N. A., Gundogan, K., Ge, L., & Liang, F. (2023). Smart transportation: an overview of technologies and applications. Sensors, 23(8), 3880.

Infrastructure, S. T. (2024). Internet of Things (IoT) Solutions for smart transportation infrastructure and fleet management. Tuijin Jishu/Journal of Propulsion Technology, 45(4), 1492-1509. https://www.researchgate.net/profile/Apata-Bolanle/publication/385824116_Internet_of_Things_IoT_Solutions_for_Smart_Transportation_Infrastructure_and_Fleet_Management/links/6736c286a78ba469f0618119/Internet-of-Things-IoT-Solutions-for-Smart-Transportation-Infrastructure-and-Fleet-Management.pdf.

Sreelekha, M., & Midhunchakkaravarthy. (2025). Revolutionizing Urban Traffic Management: IoT-Driven Algorithms for Intelligent Transportation Systems. International Journal of Intelligent Transportation Systems Research, 1-28.

Ahmad Jan, M., Adil, M., Brik, B., Harous, S., & Abbas, S. (2025). Making Sense of Big Data in Intelligent Transportation Systems: Current Trends, Challenges and Future Directions. ACM Computing Surveys, 57(8), 1-43.

Musa, A. A., Malami, S. I., Alanazi, F., Ounaies, W., Alshammari, M., & Haruna, S. I. (2023). Sustainable traffic management for smart cities using internet-of-things-oriented intelligent transportation systems (ITS): challenges and recommendations. Sustainability, 15(13), 9859.

Shi, R., & Niu, L. (2023). A brief survey on learning based methods for vehicle routing problems. Procedia Computer Science, 221, 773-780.

Ahmad, K., Khujamatov, H., Lazarev, A., Usmanova, N., Alduailij, M., & Alduailij, M. (2023). Internet of things‐aided intelligent transport systems in smart cities: Challenges, opportunities, and future. Wireless communications and mobile computing, 2023(1), 7989079.

Shahbazian, R., Pugliese, L. D. P., Guerriero, F., & Macrina, G. (2024). Integrating machine learning into vehicle routing problem: Methods and applications. IEEE Access, 12, 93087-93115.

Guo, H., Huang, R., & Xu, Z. (2024). The design of intelligent highway transportation system in smart city based on the internet of things. Scientific reports, 14(1), 28122.

Ge, C., & Qin, S. (2024). Digital twin intelligent transportation system (DT‐ITS)—A systematic review. IET Intelligent Transport Systems, 18(12), 2325-2358.

Bolaños, C., Rojas, B., Salazar-Cabrera, R., Ramírez-González, G., de la Cruz, Á. P., & Molina, J. M. M. (2022). Fleet management and control system for developing countries implemented with Intelligent Transportation Systems (ITS) services. Transportation Research Interdisciplinary Perspectives, 16, 100694.

Namburi, V. L. (2024). Software-defined vehicle fleet management system with integrated cybersecurity measures. Available at SSRN 5060173. https://www.authorea.com/doi/full/10.22541/au.174172272.24930654.

Boumpa, E., Tsoukas, V., Chioktour, V., Kalafati, M., Spathoulas, G., Kakarountas, A., ... & Malindretos, G. (2022). A review of the vehicle routing problem and the current routing services in smart cities. Analytics, 2(1), 1-16.

Czuba, P., & Pierzchala, D. (2021). Machine learning methods for solving vehicle routing problems. Proceedings of the 36th International Business Information Management Association (IBIMA), Granada, Spain, 4-5. https://www.researchgate.net/profile/Przemyslaw-Czuba/publication/349058264_Machine_Learning_methods_for_solving_Vehicle_Routing_Problems/links/601d65b0299bf1cc26a6b881/Machine-Learning-methods-for-solving-Vehicle-Routing-Problems.pdf.

Potdar, P. R., & Parikh, S. M. (2025). Internet of things (IoT) and artificial intelligence (AI) enabled framework for smart fleet management. OPSEARCH, 1-33.

Xu, G., Chen, J., Wang, Z., Zhou, A., Schrader, M., Bittle, J., & Shao, Y. (2025). Enhancing Traffic Safety Analysis with Digital Twin Technology: Integrating Vehicle Dynamics and Environmental Factors into Microscopic Traffic Simulation. arXiv preprint arXiv:2502.09561. https://arxiv.org/abs/2502.09561.

Di, X., Fu, Y., Turkcan, M. K., Ghasemi, M., Mo, Z., Zang, C., ... & Zussman, G. (2024). AI-Powered Urban Transportation Digital Twin: Methods and Applications. arXiv preprint arXiv:2501.10396. https://arxiv.org/abs/2501.10396.

Shamlitsky, Y., Aleksey, O., Morozov, E., & Strekaleva, T. (2024). Using digital twins to manage traffic flows. In E3S Web of Conferences (Vol. 471, p. 04027). EDP Sciences.

Pawar, A. B., Khan, S. A., El-Ebiary, Y. A. B., Burugari, V. K., Abdufattokhov, S., Saravanan, A., & Ghodhbani, R. (2025). Digital Twin-Based Predictive Analytics for Urban Traffic Optimization and Smart Infrastructure Management. International Journal of Advanced Computer Science & Applications, 16(5).

Aliaj, A. (2023). Fleet management solutions: a census of market offerings and business expectations. https://www.politesi.polimi.it/handle/10589/234279.

Diterbitkan

2026-01-26

Cara Mengutip

Yusuf, A., Afriansa, M., Annisa, A., Serli, S., Mutmainna, W., & Dayanti, D. (2026). PENERAPAN TEKNOLOGI WEB UNTUK SMART TRANSPORTATION DAN MANAJEMEN ARMADA DI ERA IOT SYSTEMATIC LITERATURE REVIEW 2020–2025. Jurnal Teknologi Dan Bisnis Cerdas, 2(1), 27–40. https://doi.org/10.64476/jtbc.v2i1.22