Journal of Information Technology and Computer Science
Vol. 1 No. 2: November 2016

Rainfall Forecasting in Banyuwangi Using Adaptive Neuro Fuzzy Inference System

Gusti Ahmad Fanshuri Alfarisy (Universitas Brawijaya)
Wayan Firdaus Mahmudy (Universitas Brawijaya)

Article Info

Publish Date
08 Feb 2017

Abstract

Rainfall forcasting is a non-linear forecasting process that varies according to area and strongly influenced by climate change. It is a difficult process due to complexity of rainfall trend in the previous event and the popularity of Adaptive Neuro Fuzzy Inference System (ANFIS) with hybrid learning method give high prediction for rainfall as a forecasting model. Thus, in this study we investigate the efficient membership function of ANFIS for predicting rainfall in Banyuwangi, Indonesia. The number of different membership functions that use hybrid learning method is compared. The validation process shows that 3 or 4 membership function gives minimum RMSE results that use temperature, wind speed and relative humidity as parameters.

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Journal Info
Journal of Information Technology and Computer Science
Website

Abbrev

jitecs

Publisher

Universitas Brawijaya

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Description

The Journal of Information Technology and Computer Science (JITeCS) is a peer-reviewed open access journal published by Faculty of Computer Science, Universitas Brawijaya (UB), Indonesia. The journal is an archival journal serving the scientist and engineer involved in all aspects of information ...