Open AccessGIS-based ranking and categorization of potential impact on drought as disaster mitigation effort in Bandung Barat Regency (KBB) using Simple Additive Weighting (SAW)
Author(s) -
Yulison Herry Chrisnanto,
Faiza Renaldi,
N Z Afsyari,
Asep Id Hadiana
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1098/3/032043
Subject(s) - weighting , categorization , ranking (information retrieval) , geography , settlement (finance) , environmental resource management , environmental planning , computer science , environmental science , artificial intelligence , medicine , radiology , world wide web , payment
Drought is a disaster that has a significant impact on agriculture, economics, health and the environment, and many other aspects of life all including Kabupaten Bandung Barat (KBB), Indonesia. The Regional Disaster Management Agency (BPBD) of KBB shows that in 2018, over 92,780 houses in 47 villages were affected by drought. This study aims to predict which area in KBB will be impacted by drought using Geographical Information System (GIS). Previous studies have shown much evidence that GIS will work, but none were done in Indonesia. We use the Simple Additive Weighting (SAW) method to create the ranking, categorization, and information on potential droughts. The method analyses historical drought impact, rainfall densities, water resources, rivers, and lakes availability, and settlement area. At the end of this study, we successfully categorize 162 villages into 4 categories. Accuracy on the result is also tested using real data from 2018, which resulted in 70.21% accuracy out compared to all 47 villages that were affected in 2018. An increase in accuracy of 72.50% also highlighted when comparing the result of very high potential and high potential area affected by drought with the 2018 data. Furthermore, a convincing 100% accuracy was obtained when comparing the top-10 data of very high potential in droughts and 2018 data. As our future recommendation, We suggest more parameters to be included in the calculations and also to use a 3-dimensional GIS approach as a tool to visualize the information.