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Article . 2021 . Peer-reviewed
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License: CC BY NC ND
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Rainfall Prediction Using Fuzzy Time Series

Authors: Adhi Susano; Wulan Anggraeni;

Rainfall Prediction Using Fuzzy Time Series

Abstract

Flood is one of the problems faced by DKI Jakarta Province. To be able to reduce losses caused by flooding is to predict rainfall. The type of research is quantitative research using rainfall prediction method using Fuzzy Time Series (FTS) which was developed by Stevenson & Porter (2009). The data used is rainfall data at Kemayoran Station in the period January 2018 to December 2020. The prediction accuracy results state that the FTS method has poor accuracy so that improvements are needed in the formation of interval intervals.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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