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Abstract

This research aims to build a geographic information system that can map the level of flood-prone areas around Sub-DAS Bengkulu. To determine the flood prone areas are used four (4) parameters i.e. riverbank, high ground class, rainfall and settlement using Simple Additive Weighting method and using Trend Non Linier forecasting method. The resulting outer area of the flood map is calculated from The Simple Additive weightingmethod. For five (5) years, from 2014 – 2018 there are 267 data entering intermediate clustering , 477 of data entering low clustering and the latter there are 35 data that enters high clustering . In addition, there is also an external result of prediction Chart of the highest Trend Non Linier in 2021 of 2.3809, in 2022 for 3.14841, in 2023 for 4.04413, in 2024 for 5.06803, and in 2025 for 6.22014.

Keywords

Floods Sub-DAS Bengkulu DownStream Simple Additive Weighting Trend Non Linier Geographic Information System

Article Details

References

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