TY - JOUR
T1 - Increasing disaster victim survival rate
T2 - SaveMyLife Mobile Application development
AU - Berawi, Mohammed Ali
AU - Leviäkangas, Pekka
AU - Siahaan, Sutan Akbar Onggar
AU - Hafidza, Alya
AU - Sari, Mustika
AU - Miraj, Perdana
AU - Harwahyu, Ruki
AU - Saroji, Gunawan
N1 - Funding Information:
This research is supported by the EU research grant for Building European Communities' Resilience and Social Capital (BuildERS) project.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/6/15
Y1 - 2021/6/15
N2 - Natural disasters have harmful effects on human lives and the economy, as well as physical damage to the environment. Previous research has discussed technological and social perspectives to cope with disaster events, but limited evidence was found on the communication between victims and rescuers and mobile applications' impact as the means of communication between the users. This research aims to improve search and rescue team response time and increase the victim survival rate by taking into account the victim prioritization and technology utilization through mobile disaster applications. This research considers Indonesia as the case study due to its high risk of natural disaster occurrences. A mixed-method approach using the questionnaire survey and in-depth interview was conducted. A fuzzy inference system and a supervised machine learning approach were also utilized to achieve the research objectives. The research identified four components that should be considered to improve the survival rate of victims. The proposed combination model shows that the prediction produces a significant accuracy and can be used to prioritize victims. This research's output also suggests a mobile application development that guides victims to safety points and connects them to the rescuers. The mobile application can be used from pre-disaster and emergency response phases.
AB - Natural disasters have harmful effects on human lives and the economy, as well as physical damage to the environment. Previous research has discussed technological and social perspectives to cope with disaster events, but limited evidence was found on the communication between victims and rescuers and mobile applications' impact as the means of communication between the users. This research aims to improve search and rescue team response time and increase the victim survival rate by taking into account the victim prioritization and technology utilization through mobile disaster applications. This research considers Indonesia as the case study due to its high risk of natural disaster occurrences. A mixed-method approach using the questionnaire survey and in-depth interview was conducted. A fuzzy inference system and a supervised machine learning approach were also utilized to achieve the research objectives. The research identified four components that should be considered to improve the survival rate of victims. The proposed combination model shows that the prediction produces a significant accuracy and can be used to prioritize victims. This research's output also suggests a mobile application development that guides victims to safety points and connects them to the rescuers. The mobile application can be used from pre-disaster and emergency response phases.
KW - Communication
KW - Decision tree
KW - Disaster management
KW - Disaster risk reduction
KW - Fuzzy inference system
UR - http://www.scopus.com/inward/record.url?scp=85105508495&partnerID=8YFLogxK
U2 - 10.1016/j.ijdrr.2021.102290
DO - 10.1016/j.ijdrr.2021.102290
M3 - Article
AN - SCOPUS:85105508495
SN - 2212-4209
VL - 60
JO - International Journal of Disaster Risk Reduction
JF - International Journal of Disaster Risk Reduction
M1 - 102290
ER -