Abstract
Earthquake disasters usually cause panic in the community affected areas, so it is necessary to be analyzed to deal with earthquake events in the future. This paper analyzes data from 9 major earthquakes in Indonesia over the past 4 years and determines 14 critical events. The analysis is based on credible association rules (CAR), data mining, and the maximum clique algorithm. To verify the accuracy of the association relationship and CAR effectiveness, it is performed using a maximum clique algorithm. Based on the results of data mining, that earthquakes have a credible association relationship and have a probability of critical events in various regions in Indonesia. Thus, these results can be used for prediction, early warning, and logistic distribution planning.
Highlights
Critical incidents of earthquake disaster are series of problems about the society and economy in the secondary disasters which are caused by the earthquake disasters, such as people’s lives being threatened, a huge loss of the economy, the destruction of regular production and living order, the turbulence and confusion of some part of society
Warning of a critical incident of earthquake disaster is on the basis of analysis of the historical data, using data mining algorithm, to find useful information from huge data, and in order to provide scientific proofs and effective solutions to promptly handle coordinate critical incidents in the future
Based on the order of credibility, we can find from the statistics of the research, all the obtained results of 2-item credible set are different in the critical incidents of earthquake disasters in different areas, they have some kind of tendency, some critical incidents with high credibility in common, such as price inflation, supplies scarcity, land traffic jams, shortage of water and power supply and plague epidemic etc
Summary
Critical incidents of earthquake disaster are series of problems about the society and economy in the secondary disasters which are caused by the earthquake disasters, such as people’s lives being threatened, a huge loss of the economy, the destruction of regular production and living order, the turbulence and confusion of some part of society. Warning of a critical incident of earthquake disaster is on the basis of analysis of the historical data, using data mining algorithm, to find useful information from huge data, and in order to provide scientific proofs and effective solutions to promptly handle coordinate critical incidents in the future. Early warning of a critical incident of earthquake disaster is still in the first stage. This paper is based on credible association rules and its mining algorithm based on maximum clique (Xiao et al, 2008) to analyze 9 influential crises of earthquake disasters in recent 4 years in the world, according to mine the credible association. 7-16, 2021 relationships and probabilities of these crises to forecast the occurring probability of related critical incidents and to achieve the purpose of forecasting and early warning Suyudi et al / International Journal of Global Operations Research, Vol 2, No 1, pp. 7-16, 2021 relationships and probabilities of these crises to forecast the occurring probability of related critical incidents and to achieve the purpose of forecasting and early warning
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