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All Journal TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan
Sidharta, Josie
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Computer Science & IT Control & Systems Engineering

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Jaringan Saraf Tiruan Menggunakan Metode Backpropagation untuk Prediksi Curah Hujan Tamaji, Tamaji; Utama, Yoga Alif Kurnia; Sidharta, Josie
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol. 10 No. 1 (2022): TELEKONTRAN vol 10 no 1 April 2022
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/telekontran.v10i1.7409

Abstract

Rain is very difficult to predict. This is because there ar eso many factors that can affect rain starting from temperature, humidity, rainfall and intensity of sunlight. Moreover, coupled with weather anomalies such as la nina and el nino which cause a longer rainy period than usual. Whereas high rainfall causes disasters such as floods and so on. Therefore, it is important in predicting the rain that will occur in a place As it is likely possible anticipate flood disaster that will occur. This study uses a backpropagation type of artificial neural network in predicting rainfall. Input data that used to train this artificial neural network is data from BKMG about monthly rainfall during 2015-2019. Based About the result of the conducted test data, the MSE at output of the artificial neural network is 0.089161. From these effects it could be assume that the synthetic neural network with method backpropagation works well to predict the rainfall that will occur. Keyword ­: Backpropagation, Rainfall, Prediction, Artificial Neural Network.
Co-Authors Tamaji, Tamaji Yoga Alif Kurnia Utama, Yoga Alif Kurnia