Gaung Informatika
Vol 13 No 1 (2020): Jurnal Gaung Informatika Vol 13 No 1 Januari 2020

PENGUKURAN PERFORMA SUPPORT VECTOR MACHINE DAN NEURAL NETWOK DALAM MERAMALKAN TINGKAT CURAH HUJAN

Diyah Ruswanti (Unknown)

Article Info

Publish Date
06 Apr 2020

Abstract

Prediction models using Neural Network or Support Vector Machine have been developed in many areas of rainfall. In this studi we have compared the performance of NN and SVM models, in predition of monthly rainfall at R-17 station Kecepit Pemalang. The analyzed using NN and SVM in which testing with Root Mean Square Error (RMSE) for get the performance is done. The data obtained for 2009 to 2018 monthly rainfall were used as modelling and forecasting sample. The results showed that NN obtained smallest error rate compared to SVM. the recognized value of RMSE for SVM is 176,374, Neural Network is 22,289. In RMSE the smallest error rate showed the best performance of algorithm.

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Journal Info
Gaung Informatika
Website

Abbrev

GI

Publisher

Universitas Sahid Surakarta

Subject

Computer Science & IT

Description

Jurnal Gaung Informatika diterbitkan oleh Program Studi Informatika, Fakultas Sains, Teknologi, Kesehatan, Universitas Sahid Surakarta sejak 1 Januari 2009. Latar belakang awal diterbitkannya jurnal berkala ini adalah guna mempublikasikan karya ilmiah para dosen, peneliti, maupun praktisi dibidang ...