Jurnal Ilmu Komputer dan Informasi
Vol 9, No 1 (2016): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)

Performance Comparison Between Support Vector Regression and Artificial Neural Network for Prediction of Oil Palm Production

Mustakim Mustakim (Unknown)
Agus Buono (Unknown)
Irman Hermadi (Unknown)



Article Info

Publish Date
15 Feb 2016

Abstract

The largest region that produces oil palm in Indonesia has an important role in improving the welfare of society and economy. Oil palm has increased significantly in Riau Province in every period, to determine the production development for the next few years with the functions and benefits of oil palm carried prediction production results that were seen from time series data last 8 years (2005-2013). In its prediction implementation, it was done by comparing the performance of Support Vector Regression (SVR) method and Artificial Neural Network (ANN). From the experiment, SVR produced the best model compared with ANN. It is indicated by the correlation coefficient of 95% and 6% for MSE in the kernel Radial Basis Function (RBF), whereas ANN produced only 74% for R2 and 9% for MSE on the 8th experiment with hiden neuron 20 and learning rate 0,1. SVR model generates predictions for next 3 years which increased between 3% - 6% from actual data and RBF model predictions.

Copyrights © 2016






Journal Info

Abbrev

JIKI

Publisher

Subject

Computer Science & IT

Description

Jurnal Ilmu Komputer dan Informasi is a scientific journal in computer science and information containing the scientific literature on studies of pure and applied research in computer science and information and public review of the development of theory, method and applied sciences related to the ...