Open AccessPrototype Decision Support System To Detect Disaster Prone Areas With Saw Method (Tanggamus District Case Study)
Author(s) -
Tri Susilowati,
. Nurzaman,
Andino Maseleno,
Wahyu Dwi Saputra
Publication year - 2022
Publication title -
international journal of agriculture and animal production
Language(s) - English
Resource type - Journals
ISSN - 2799-0907
DOI - 10.55529/ijaap.21.1.11
Subject(s) - landslide , disaster area , flood myth , emergency management , process (computing) , geography , computer science , risk analysis (engineering) , environmental planning , business , political science , geology , seismology , meteorology , archaeology , law , operating system
Most of Tanggamus regency is a disaster-prone area, such as floods, landslides, earthquakes, and so on. To determine the area that is really potentially catastrophic is something complicated and the determination process there are many errors, because the determination process is based on subjectivity. In this case it is most likely that the area that is really potential for disaster does not enter into the territory prioritized by the government to be given socialization of insights about disasters or reduce the risk of disasters. This paper discusses the Simple Additive Weighting (SAW) method that can be used in determining disaster-prone areas in Tanggamus Regency. The area to be designated as a disaster-prone area has criteria that have been set. Criteria needed include: Flood disaster data, landslide disaster data, earthquake disaster data, tsunami disaster data, and fire disaster data. The result of this system is a list of disaster-prone areas that comply with the criteria specified as areas of special attention from local governments.