Issue |
E3S Web Conf.
Volume 331, 2021
International Conference on Disaster Mitigation and Management (ICDMM 2021)
|
|
---|---|---|
Article Number | 04011 | |
Number of page(s) | 6 | |
Section | Lesson Learnt in Disaster Management | |
DOI | https://doi.org/10.1051/e3sconf/202133104011 | |
Published online | 13 December 2021 |
A literature review: model of disaster risk reduction for decision support system
Program of Civil Engineering, Jember University, 68121 Jl Kalimantan 37 Jember, Indonesia
* Corresponding author: jojok.teknik@unej.ac.id
Disaster is a threat to human life. Many losses are caused by disasters, namely loss of life, injured people, loss of homes, and others. In addition, the frequency and intensity of disasters are also increasing every year. Therefore, research on Disaster Risk Reduction (DRR) is needed both to reduce disaster risk and to manage the disaster. The purpose of this research is to develop an appropriate DRR model in an area to assist decision-making in making policy. This research was compiled based on literature studies from various reputable journals to be used as a reference in the preparation of the right model. Then proceed with the development of a framework to model an efficient and effective DRR. The steps for making a holistic DRR model have been identified and the test design for the model has been determined, namely simulation, validation, and scenario. The recommendation given from this study is the preparation of a DSS (Decision Support System) as a tool for decision-makers to make policies regarding DRR-based regional development. This discussion will be continued in the next research by including case studies in certain urban areas.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.