Evaluasi Biaya Pemeliharaan Proyek Jalan di Kota Bogor - Jawa Barat
DOI:
https://doi.org/10.51903/kompak.v18i2.2959Keywords:
pemeliharaan jalan , APBD, Proyek Daerah, infrastruktur daerah, proyek pemerintahAbstract
Pemerintah daerah memiliki kewenangan pengelolaan Anggaran Pendapatan dan Belanja Daerah (APBD) untuk menyediakan dan melakukan pemeliharaan infrastruktur fisik yang digunakan oleh Masyarakat, sehingga diperlukan perencanaan yang komprehensif untuk Pembangunan dan pemeliharaan infrastruktur fisik agar tepat sasaran dan memiliki kemaslahatan bagi Masyarakat. Pembangunan infrastruktur yang berhasil akan berdampak pada masyarakat untuk memiliki akses dalam melaksanakan berbagai kegiatan yang berhubungan dengan peningkatan taraf hidup. Penelitian ini bertujuan untuk mengevaluasi biaya pemeliharaan infrastruktur jalan di Kota bogor berbasis faktor yang dianggap signifikan mempengaruhi sekaligus memberikan rekomendasi biaya pemeliharaan yang optimal untuk jalan raya di Kota Bogor, Jawa Barat. Penelitian ini dilakukan melalui metode kuantitatif dan kualitatif (mix method), metode kuantitatif dilakukan dengan menganalisa 30 ruas jalan yang telah dilaksanakan untuk menentukan faktor yang dianggap mempengaruhi dan dominan dalam pemeliharaan jalan. Penelitian kualitatif akan dilakukan melalui interview mendalam (in-depth interview) kepada pakar untuk memvalidasi hasil penelitian kuantitatif yang dihasilkan sehingga dapat menjadi rekomendasi pemeliharaan jalan raya di Kota Bogor, Jawa Barat. Hasil dari penelitian ini adalah hasil evaluasi pemeliharaan jalan beserta faktor yang dianggap mempengaruhi dalam pemeliharaan jalan. Penelitian ini akan memberikan manfaat baru dalam mengembangkan knowledge bidang pemeliharaan infrastruktur jalan raya bagi pemerintah daerah, akademisi, kontraktor dan Masyarakat dalam pemeliharaan infrastruktur jalan raya di Kota Bogor, Jawa Barat dan daerah lain untuk dievaluasi dan dikembangkan faktornya agar pekerjaan pemeliharaan jalan di daerah menjadi optimal di masa yang akan datang.
References
[1] M. Loy, “Landscapes of (dis)connection: Modelling connectivity in west Samos with least cost path analysis,” J Archaeol Sci Rep, vol. 64, Jun. 2025, doi: 10.1016/j.jasrep.2025.105144.
[2] J. Jang, “Predicting nighttime black ice using atmospheric data for efficient winter road maintenance patrols,” Transp Res Interdiscip Perspect, vol. 29, Jan. 2025, doi: 10.1016/j.trip.2024.101299.
[3] M. F. Sheikh, D. R. Padmanabhan, D. M. Hadid, and D. L. Kerbache, “Towards Additive Manufacturing Enabled Sustainable Spare Parts Supply Chain: A Multi-Objective MILP Model for Cost and Carbon Emissions Minimization,” in Procedia Computer Science, Elsevier B.V., 2025, pp. 952–963. doi: 10.1016/j.procs.2025.01.157.
[4] S. Shaffiee Haghshenas, G. Guido, S. Shaffiee Haghshenas, and V. Astarita, “Predicting the level of road crash severity: A comparative analysis of logit model and machine learning models,” Transportation Engineering, vol. 20, Jun. 2025, doi: 10.1016/j.treng.2025.100323.
[5] A. Soltani, S. Afshari, and M. A. Amiri, “Human cost, machine insight: A data-driven analysis of Australian road crashes,” Case Stud Transp Policy, vol. 20, Jun. 2025, doi: 10.1016/j.cstp.2025.101440.
[6] A. Benardos and D. Skenderas, “Exploring the true cost of infrastructure transit projects: Road vs Tunnel alternatives,” Tunnelling and Underground Space Technology, vol. 162, Aug. 2025, doi: 10.1016/j.tust.2025.106624.
[7] N. Mohammadi and A. Klein-Paste, “Simulating winter maintenance efforts: A multiscale geographically weighted regression model,” Cold Reg Sci Technol, vol. 236, Aug. 2025, doi: 10.1016/j.coldregions.2025.104512.
[8] M. Yin et al., “Exploring the value of digital twins for information management in highway asset maintenance,” Developments in the Built Environment, vol. 21, Mar. 2025, doi: 10.1016/j.dibe.2025.100614.
[9] R. Viri and H. Tiikkaja, “The costs of mobility: a data-based method for estimating cost and emissions per kilometre in Finland,” in Transportation Research Procedia, Elsevier B.V., 2025, pp. 1974–1993. doi: 10.1016/j.trpro.2024.12.167.
[10] L. Lu, A. M. d’Avigneau, Y. Pan, Z. Sun, P. Luo, and I. Brilakis, “Modeling heterogeneous spatiotemporal pavement data for condition prediction and preventive maintenance in digital twin-enabled highway management,” Autom Constr, vol. 174, Jun. 2025, doi: 10.1016/j.autcon.2025.106134.
[11] X. Ji, X. Huang, S. Zhong, and J. Zhou, “Advancing toward a low-carbon infrastructure: Emission reduction potential of geopolymer road maintenance,” Materials Today Sustainability, vol. 30, Jun. 2025, doi: 10.1016/j.mtsust.2025.101121.
[12] M. Sundararaman and B. Sambasivam, “The Road to Net Zero in a Renewable Energy-Dominated Electricity System: Impact of EV Charging and Social Cost of Emission on the Optimal Economic Dispatch,” Green Energy and Intelligent Transportation, p. 100280, Feb. 2025, doi: 10.1016/j.geits.2025.100280.
[13] C. Peco-Costas, C. Acuña-Alonso, M. García-Ontiyuelo, and X. Álvarez, “Assessing ecological connectivity in the Serra do Cando and Serra do Candán area of Galicia: A multitemporal classification and least-cost path modelling approach,” Ecol Inform, vol. 86, May 2025, doi: 10.1016/j.ecoinf.2025.103049.
[14] A. Faisal and S. Gargoum, “Cost-effective LiDAR for pothole detection and quantification using a low-point-density approach,” Autom Constr, vol. 172, Apr. 2025, doi: 10.1016/j.autcon.2025.106006.
[15] Q. V. Dinh, V. N. Dinh, and P. G. Leahy, “A differential evolution model for optimising the size and cost of electrolysers coupled with offshore wind farms,” Int J Hydrogen Energy, vol. 124, pp. 318–330, May 2025, doi: 10.1016/j.ijhydene.2025.03.440.
[16] B. Faria, J. P. Nunes, J. E. M. Baartman, L. Dias, J. Wu, and S. A. Prats, “Assessing cost-effectiveness of land management measures to restore forest ecosystem services after fire using hydrological modelling and multi-criteria decision analysis,” Catena (Amst), vol. 251, Apr. 2025, doi: 10.1016/j.catena.2025.108808.
[17] A. Maffei, C. Spironelli, and A. Angrilli, “Affective and cortical EEG gamma responses to emotional movies in women with high vs low traits of empathy,” Neuropsychologia, vol. 133, Oct. 2019, doi: 10.1016/j.neuropsychologia.2019.107175.
[18] L. Edler et al., “Mathematical modelling and quantitative methods,” 2002. [Online]. Available: www.elsevier.com/locate/foodchemtox
[19] D. Briskorn and M. Dienstknecht, “Survey of quantitative methods in construction,” Apr. 01, 2018, Elsevier Ltd. doi: 10.1016/j.cor.2017.11.012.
[20] E. W. L. Cheng and H. Li, “Exploring quantitative methods for project location selection,” Build Environ, vol. 39, no. 12, pp. 1467–1476, Dec. 2004, doi: 10.1016/j.buildenv.2004.03.015.
[21] S. Guercini, “New qualitative research methodologies in management,” Management Decision, vol. 52, no. 4, pp. 662–674, 2014, doi: 10.1108/md-11-2013-0592.
[22] C. R. Boddy, “Sample size for qualitative research,” Qualitative Market Research, vol. 19, no. 4, pp. 426–432, 2016, doi: 10.1108/qmr-06-2016-0053.
[23] A. Saihi, M. Ben-Daya, and R. As’ad, “An Investigation of Sustainable Maintenance Performance Indicators: Identification, Expert Validation and Portfolio of Future Research,” IEEE Access, vol. 10, pp. 124259–124276, 2022, doi: 10.1109/access.2022.3224450.
[24] E. Hayat and D. Amaratunga, “The Role of Local Government in Post-Disaster Road Reconstruction: Assessment of Factors Affecting Local Government Road Maintenance Capacity,” 2017, pp. 255–279. doi: 10.1007/978-3-319-54466-3_10.
[25] M. B. Bouraima, Y. Qiu, C. Kiprotich Kiptum, and K. Maraka Ndiema, “Evaluation of Factors Affecting Road Maintenance in Kenyan Counties Using the Ordinal Priority Approach,” Journal of Computational and Cognitive Engineering, vol. 2, no. 3, pp. 260–265, Aug. 2023, doi: 10.47852/bonviewjcce2202272.
[26] M. T. Wangare, “Factors Influencing Maintenance Of Roads In Kenya: A Case Of The Nairobi Thika Highway Improvement Project,” University of Nairobi, 2019. [Online]. Available: https://erepository.uonbi.ac.ke/handle/11295/109484
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