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Investigating Effectiveness Wayfinding on Terminal Navigation in Terminal 2 Soekarno-Hatta Airport: Bayesian Network Approach

Published: 27 September 2019 Publication History

Abstract

Effective wayfinding is the interaction that occurs between human and environmental factors which results in a person successfully moving from their current position to the desired location at the right time. This interaction needs to be modeled from the process that occurs. This paper proposes a complex modeling system approach from wayfinding using Bayesian Networks. Bayesian Network is a method that is often used to understand the relationship between variables because it studies the relationship of each dependent and independent variable. To model effective wayfinding with the Bayesian Network, the application to the process at the airport is used. The airport used is Soekarno-Hatta airport. The purpose of this study is to obtain factors that influence wayfinding activities at Soekarno-Hatta Airport. Modeling the influence of each factor in the hope that the model becomes the basic model. Provide recommendations for innovation design related to system improvements to improve the quality of wayfinding activities based on the results of the analysis carried out.

References

[1]
R. M. Downs and D. Stea. 2011. Cognitive Maps and Spatial Behaviour: Process and Products. John Wiley & Sons.
[2]
A. C. Farr, T. Kleinschmidt, S. Johnson, P. K. D. V. Yarlagadda, and K. Mengersen. 2014. Investigating Effective Wayfinding in Airports: a Bayesian Network Approach. Transport. 29, 1 (Mar. 2014), 90--99.
[3]
Badan Pusat Statistik. 2016. Jumlah Penumpang Bandara Tahun 2006-2016.
[4]
H. T. Pandve. 2017. Historical Milestones of Ergonomics: From Ancient Human to Modern Human. J. Ergon. 7, 4 (Jul. 2017), 7556.
[5]
A. Churchill, E. Dada, A. G. de Barros, and S. C. Wirasinghe. 2008. Quantifying and validating measures of airport terminal wayfinding. J. Air Transp. Manag. 14, 3 (May 2008), 151--158.
[6]
E. Herskovits and G. F. Cooper. 1992. A Bayesian method for the induction of probabilistic networks from data. Mach. Learn. 9, 4 (Oct. 1992), 309--347.
[7]
B. Reiz and L. Csató. 2014. Tree-like Bayesian Network classifiers for surgery survival chance prediction Tree-Like Bayesian Network Classifiers for Surgery Survival Chance Prediction Bayesian Networks.
[8]
J. Han, M. Kamber, and J. Pei. 2012. Data Mining: Concepts and Techniques. Elsevier Inc.

Cited By

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  • (2021)INNOVATION AT AIRPORTS: A SYSTEMATIC LITERATURE REVIEW (2000–2019)Aviation10.3846/aviation.2021.1491725:3(220-231)Online publication date: 25-Nov-2021

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  1. Investigating Effectiveness Wayfinding on Terminal Navigation in Terminal 2 Soekarno-Hatta Airport: Bayesian Network Approach

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      cover image ACM Other conferences
      ICIBE '19: Proceedings of the 5th International Conference on Industrial and Business Engineering
      September 2019
      398 pages
      ISBN:9781450376532
      DOI:10.1145/3364335
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • The Hong Kong Polytechnic: The Hong Kong Polytechnic University

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 27 September 2019

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      Author Tags

      1. Airport
      2. Bayesian Network
      3. Graphical Model
      4. Terminal Navigation
      5. Wayfinding

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      • Refereed limited

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      • Directorate of Research and Community Engagement (DRPM)

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      ICIBE 2019

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      • (2021)INNOVATION AT AIRPORTS: A SYSTEMATIC LITERATURE REVIEW (2000–2019)Aviation10.3846/aviation.2021.1491725:3(220-231)Online publication date: 25-Nov-2021

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