Prediction Models of Infrastructure Resilience as a Decision Support System Based on Bayesian Network

A. D. Agustin*, T. J.W. Adi

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


The impact of climate change is the implication of global warming that affects people around the world, including Indonesia, which is causing more the intensity and type of natural disaster that causes a decrease or malfunction of a city. To reduce the impact of climate change is needed for the application of the concept of resilience. Resilience is the ability to withstand disturbances caused by external factors and the ability to recover if damage occurs. One of the natural disasters is an earthquake is a natural disaster that often occurs in Indonesia and generally causes significant damage to the physical condition of buildings and infrastructure. This study aims to create a prediction model to measure the impact of a disaster as a decision support system such as a mitigation strategy and responses to identify measures that can improve performance infrastructure to meet resilience goals. One of probabilistic methods is the Bayesian Network method. It is a graphical model probabilistic that represents a set of variables and freedom probabilistic using conditional-probability-table. This research expects as a proposed method of assessing resilience infrastructure to cities in Indonesia when natural disasters occur, especially earthquakes.

Original languageEnglish
Article number012014
JournalIOP Conference Series: Earth and Environmental Science
Issue number1
Publication statusPublished - 19 Aug 2021
Event3rd International Conference on Sustainable Infrastructure, ICSI 2020 - Yogyakarta, Virtual, Indonesia
Duration: 5 Oct 20206 Oct 2020


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