Evaluasi Layanan Taksi Menggunakan Agen Based Modeling (ABM)

Silvi Istiqomah(1*), Y Yuniaristanto(2), I Wayan Suletra(3),

(2) Sebelas Maret University
(*) Corresponding Author
DOI: https://doi.org/10.23917/jiti.v18i1.7227


Taxi services involve the number of taxi and demand. A balance is needed for operated taxi and demand, so that the number of canceled order decreases. This system involves taxi and consumers as agents with various behaviors from their agents, then solved using modeling methods. Agent-based modeling is a feasible method used in this study because it can accommodate the properties and attributes of each agent. From the scenario that has been done, the average number of good fleets to operate is 103 fleets, with the canceled order rate is 1.2% and this model proves that the number of operated taxi is sensitive to the number of requests that exist.


taksi; demand ; agen based modeling

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Agahari. (2017). Peluang dan Tantangan Ekonomi Digital di Indonesia. Center of Innovation Policy and Governance.

Barrios, J.A., Doig, J.C., 2014. Fleet sizing for flexible carsharing systems: a simulation-based approach. In: Proc. Transportation Research Board 93rd Annual Meeting.

Ch, J.D.C. & Briones, J. 2006, "A diagrammatic analysis of the market for cruising taxis", Transportation Research Part E: Logistics and Transportation Review, vol. 42, no. 6, pp. 498-526.

Chang, H., Tai, Y. & Hsu, J.Y. 2009, "Context-aware taxi demand hotspots prediction", International Journal of Business Intelligence and Data Mining, vol. 5, no. 1, pp. 3-18.

Cuevas, Estrada, & Salanova. (2016). Management of On-demand Transport Services in Urban Contexts. Barcelona Case Study. Transportation Research Procedia 13 ( 2016 ) 155 – 165

Dia, H. & Javanshour, F. (2017). Autonomous Shared Mobility-On-Demand: Melbourne Pilot Simulation Study, 22 (2017) 285–296.

Fagnant, Daniel J., and Kara M. Kockelman. ”Dynamic ride-sharing and optimal fleet sizing for a system of shared autonomous vehicles.” Transportation Research Board 94th Annual Meeting. No. 15-1962. 2015.

Grau & Romeu. (2015). Agent based modelling for simulating taxi services. Procedia Computer Science 52 ( 2015 ) 902 – 907

Grau, Estrada, Tzenosa, Aifandopoulou. (2018). Agent based simulation framework for the taxi sector modeling. Procedia Computer Science 130 (2018) 294–301

Li, L., 2011. Design and Analysis of a Carsharing System Offering One-way Journeys. Master Thesis. University of Wisconsin-Milwaukee.

Macal, C. dan North, M., (2010), Tutorial on agent-based modelling and simulation, Journal of Simulation, Vol. 4, 151-162.

Salanova, J. M., Estrada M., Aifadopoulou, G. and Mitsakis, E., 2011. A review of the modeling of taxi services. Procedia and Social Behavioral Sciences 20: 150-161.

Siebers, Macal, Garnett, Buxton, & Pidd. (2010) Discrete-Event Simulation is Dead, Long Live Agent-Based Simulation

Vuchic, V.R., (1981), Urban Public Transportation Systems and Technology, Prentice-Hall, Englewood Cliffs, New Jersey.

Ye, Z.Y., 2009. Management of Hong Kong Taxi Industry, Traffic & Transportation,03.

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