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All Journal Portal: Jurnal Teknik Sipil IJOT Jurnal Sipil Sains Terapan
Syarwan, Syarwan
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Evaluasi Jenis Kerusakan Jalan dan Estimasi Biaya Perbaikan (Studi Kasus Jalan Banda Aceh – Medan KM 205+000 – 210+000) Maulana, Rio; Syarwan, Syarwan; Iskandar, Iskandar
Jurnal Sipil Sains Terapan Vol 3, No 01 (2020): JURNAL SIPIL SAINS TERAPAN
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P2M)

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Abstract

Jalan merupakan prasarana transportasi yang sangat berperan penting dalam mengalirkan arus lalu lintas. Jalan Banda Aceh – Medan KM 205+000 sampai dengan KM 210+000 merupakan jalan arteri atau jalan nasional yang sering dilalui oleh kendaraan berat. Ruas jalan yang ditinjau sepanjang 5 kilometer dimana kendaraan berat sering melewati jalan tersebut dan mengakibatkan kerusakan pada permukan   jalan. Penilaian kondisi permukaan jalan merupakan salah satu tahapan untuk menentukan jenis program evaluasi yang perlu dilakukan. Penelitian ini bertujuan untuk menentukan nilai kondisi perkerasan lentur jalan, jenis kerusakan dan volume kerusakan. Dua metode yang digunakan dalam melakukan penilaian kondisi jalan adalah metode Pavment Condition Index (PCI) dan metode Bina Marga. Jenis kerusakan yang terdapat pada Jalan Banda Aceh - Medan KM 205+000  – 210+000 antara lain retak halus, retak memanjang, retak blok, retak kulit buaya, pelepasan butiran, amblas, lubang, dan tambalan. Hasil evaluasi kondisi ruas jalan dengan metode PCI dan Bina Marga menghasilkan penilaian yang relatif sama, yaitu kondisi ruas jalan yang perlu dilakukan rekonstruksi adalah pada KM 205+000 – KM 208+000, sedangkan untuk KM 209+000 – KM210+000  masih dalam kondisi wajar namun memerlukan pemeliharaan rutin. Berdasarkan nilaikondisi perkerasan jalan tersebut maka di dapatkan biaya perbaikan sebesar Rp.10.995.423.000.00,- (Sepuluh Milyar Sembilan Ratus Sembilan Puluh Lima Juta Empat Ratus Dua Puluh Tiga Ribu Rupiah). Kata Kunci : Pavement Condition Index (PCI), Bina Marga, kerusakan jalan 
Adaptive Traffic Signal Control Based on Deep Reinforcement Learning with Edge Computing Scheme to Overcome The Surge in Vehicle Volume Post-Pandemic: A Critical Review of The Model and Implementation Challenges Zulfadhli , Zulfadhli; Syarwan, Syarwan; Basrin, Defry
International Journal on Orange Technologies Vol. 8 No. 1 (2026): International Journal on Orange Technologies (IJOT)
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v8i1.5670

Abstract

Fundamental changes in urban mobility patterns have led to an unpredictable and non-stationary surge in vehicle volume, driven by Work From Anywhere policies and a significant increase in private vehicle usage and ride-hailing services. Consequently, a new paradigm integrating artificial intelligence with advanced computing infrastructure is required. This study constitutes a literature review aimed at providing a comprehensive critical analysis of Deep Reinforcement Learning models and Edge Computing schemes within the context of Adaptive Traffic Signal Control, with particular focus on implementation challenges in the new normal mobility era. The findings reveal four primary insights. First, Multi-Agent Deep Reinforcement Learning architectures incorporating communication mechanisms based on Graph Neural Networks demonstrate superior performance in multi-intersection scenarios, yet remain vulnerable to distributional shift phenomena caused by non-stationary travel pattern changes. Second, Edge Computing theoretically reduces latency and enhances system resilience to network failures, although its deployment is constrained by computational resource limitations and energy consumption issues on edge devices operating in extreme intersection environments. Third, an overreliance on simulation data from SUMO or VISSIM introduces significant validity gaps when models are applied to real-world mobility dynamics influenced by heterogeneous data sources such as probe vehicles and loop detector sensors. Fourth, implementation barriers are multidimensional, encompassing computational complexity, susceptibility to adversarial attacks on DRL policies, and regulatory and interoperability gaps with legacy infrastructure. The practical implications of this research emphasize the development of compact DRL models leveraging knowledge distillation for low-power edge devices, alongside technical interoperability guidelines to facilitate gradual transition from conventional systems.
Co-Authors A, Bakhtiar Albar, M Fathul Ambia, Irsandi Al AR, Sulaiman Defry Basrin Fahira, Elsa Fathahillah, Muhammad Gusrizal Gusrizal Haris, Raihan Iskandar Iskandar Majuar, Edi Maulana, Rio Mirza Fahmi Muhammad Reza Muyassar, Ahmad Rizqi Prastica, Angela Ridha, Rahmatur Riyadhsyah, Teuku Rosalina Rosalina Sanjaya, Yudi Ari Supardin Yusniyanti, Erna Zulfadhli , Zulfadhli