Simulasi Penentuan Optimasi Arah Taksi Kosong Dengan Gps Dan Metode Monte Carlo

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Sabungan Halomoan Hutapea
Rosita Sinaga

Abstract

The development of metropolitan cihJ as Jakarta for years is high, thus the demand Jo transportation
services. Tcui is one of mode transportation which is mostly used by middle to high class people. The
problem is, sometimes many people are wasting time for waiting empty taxi, mean while many
empty taxi, are searching for the passenger.
The objective of this simulation model is to direct the taxi, movement to get passenger with the help of
i~b "based software. So then, there is information to direct the taxi, mavement to choose the right Wat}
to get passenger with high possibilihJ rate of passenger.
The taxi, driver is equipped by GPS that will find out the coordinate position data of geographical. To
input the data such as position of start-finish and arrival time of passenger it can be done by cellμlar
phone then data will be transmit to ~bsite.
Using simulation approaching, a Monte Carlo simulation model can be build that will optimize taxi,
driver to find passenger. This modeling will be able to estimate the possibilihj of passenger arrival and
distribution of taxi, cars in one area. The comparison of simulation without modeling resuled int
increament of some aspects, such as increment of delivetJ services increase to 81.48%, searching time
and waiting time become 4.12% and 6.45% respectively.
Keyword: taxi, movement, waiting time, travel time, Monte-Carlo Simulation

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References

Anonim, 2004, Monte Carlo Simulation Basics. //en.wikipedia.org/w /

index.php ?title= Monte_ Carlo method&oldid=237702035

Cubilas. (2007).Urban Area. (30 Januari 2010) //en.wikipedia.org/wiki/Urban_area

Hansen, Dexter A.. (2007). Flowcharting Help Page (Tutorial). (30 Januari 2010) //

home.att.net/ ~dexter .a.hansen/ flowchart/ flowchart.htm

Jon Wittwer, Vertex42 LLC. (2004), Monte Carlo Simulation. (30 Januari 2010) //

www.vertex42.com/ExcelArticles/mc/MonteCarloSimulationhtml

Kelton W. David, Sadowski Randall P., Sturrock David T. (2007). Simulation with arena.

McGraw - Hill. United States of America.

Kakiay, Thomas J. (2004). Pengantar Sistem Simulasi.Andi. Yogyakarta.

Law, Averill M. (2007). Simulation Modelling and Analysis. McGrawHill. United State of

America.

Lllja, David J. (2000). Measuring romputer performance: a practitioner's guide .. Cambridge University

Press. Cambridge.

Pressman, Rogers. (2005). Software Engineering,APractitwner'sApproach, Sixth Edition. McgrawHill,

United States of America.

Sommerville, Ian (2001). Software Engineering Sixth Edition. Addision Wesley Publishing Limited,

Harlow.

Suryani, Erma. (2006). Pemodelan & Simulasi. Graha Ilmu. Yogyakarta.

Tsui, James Bao-Yen (2005). Fundamental of Global Positioning System Receiver. John Wiley &

Sons, Inc. Canada,

Whitten, dkk. (2004). System Analysis and Design Methods. McGraw-Hill, Singapore.

Matjik, Ahmad Ansori; I Made Sumertajaya. (2006). Perancangan Percobaan dengan Aplikasi

SAS dan MINITAB. IPB Press. Bogar.

Ziqi Song (2006). A simulation Based Di;namic Taxi Model. University Of Hong Kong