Jurnal Teknologi dan Sistem Komputer
Volume 8, Issue 1, Year 2020 (January 2020)

Kombinasi SOM-RBF untuk prediksi drought code berdasarkan data curah hujan dan suhu udara

Dwi Marisa Midyanti (Department of Computer Engineering, Universitas Tanjungpura)

Article Info

Publish Date
31 Jan 2020

Abstract

This study aims to predict Drought Code (DC) in Kabupaten Kubu Raya using a combination of SOM-RBF. The final weight value of SOM was used as a center on the RBF network. The input data variables are rainfall data and air temperature data for three days with three binary outputs to predict DC values. This study also observed the effect of the number of neurons, learning rates, and the number of iterations on the results of the SOM-RBF network training. The smallest MSE of training result from the SOM-RBF network was 0.159933 using 65 neurons in the hidden layer, learning rate 0.007, and epoch 45000. The detection accuracy of SOM-RBF was 91.34 % from 245 test data.

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Journal Info
Jurnal Teknologi dan Sistem Komputer
Website

Abbrev

JTSISKOM

Publisher

Universitas Diponegoro

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Jurnal Teknologi dan Sistem Komputer (JTSiskom, e-ISSN: 2338-0403) adalah terbitan berkala online nasional yang diterbitkan oleh Departemen Teknik Sistem Komputer, Universitas Diponegoro, Indonesia. JTSiskom menyediakan media untuk mendiseminasikan hasil-hasil penelitian, pengembangan dan ...