RESI, VINSENSIUS RINDA (2014) ANALISIS PERBANDINGAN METODE BACKPROPAGATION DAN RADIAL BASIS FUNCTION UNTUK MEMPREDIKSI CURAH HUJAN DENGAN JARINGAN SYARAF TIRUAN. Skripsi, Fakultas Ilmu Komputer.
![[img]](http://eprints.dinus.ac.id/style/images/fileicons/application_pdf.png)
| PDF - Published Version Download (3533b) | Preview |
Abstract
Indonesia is a tropical country with very high rainfall. Rainfall prediction models are used for various purposes and accuracy becomes important especially in specialized areas such as flood prevention. This analysis is based on two methods: the method of Radial Basis Function and backpropagation method of training with multiple functions. The results obtained from the method of Radial Basis Function found that accuracy in predicting precipitation is 81.37% while for Backpropagation method with some training obtained better results is 99%. So that the prediction of rainfall is more advisable to use the method of artificial neural network with backpropagation training functions in order to get better accuracy rate.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > Teknik Informatika > RPL Rekayasa Perangkat Lunak dan Data Universitas Dian Nuswantoro > Fakultas Ilmu Komputer > Teknik Informatika > RPL Rekayasa Perangkat Lunak dan Data |
| Divisions: | Library of Congress Subject Areas > T Technology > Teknik Informatika > RPL Rekayasa Perangkat Lunak dan Data Fakultas Ilmu Komputer > Teknik Informatika > RPL Rekayasa Perangkat Lunak dan Data |
| Depositing User: | Psi Udinus |
| Date Deposited: | 08 Sep 2014 13:34 |
| Last Modified: | 22 Nov 2014 07:05 |
| URI: | http://eprints.dinus.ac.id/id/eprint/5341 |
Actions (login required)
| View Item |
