Prototype Decision Support System To Detect Disaster Prone Areas With Saw Method (Tanggamus District Case Study)

Author:

Susilowati Tri1,. Nurzaman1,Maseleno Andino1,Saputra Wahyu Dwi1

Affiliation:

1. Department of Information Systems, STMIK Pringsewu, Lampung, Indonesia.

Abstract

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.

Publisher

HM Publishers

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3