Jurnal Teknik Komputer
Vol 2, No 2 (2016): Jurnal Teknik Komputer AMIK BSI

ANALISA KOMPARASI NEURAL NETWORK BACKPROPAGATION DAN MULTIPLE LINEAR REGRESSION UNTUK PERAMALAN TINGKAT INFLASI

Amrin, Amrin (Unknown)



Article Info

Publish Date
17 Mar 2016

Abstract

The inflation rate can not be underestimated in a countrys economic system and businesses in general. If inflation can be predicted with high accuracy, of course, can be used as the basis of government policy making in anticipation of future economic activity. In this study will be used back propagation neural network method and multiple linear regression method to predict the monthly inflation rate in Indonesia, then compare which method is the better. The data used comes from the central statistical agency in 2006-2015, which is 80% as training data and 20% as testing data. In the results of the data analysis is concluded that the performance of multiple linear regression is better than back propagatin neural network, with a mean absolute deviation (MAD) is 0.0380, a mean square error (MSE) is 0.0023, and a  Root Mean Square Error (RMSE) is 0.0481. Keywords: Inflation, neural network backpropagation, multiple linear regression, mean square error.

Copyrights © 2016






Journal Info

Abbrev

jtk

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknik Komputer merupakan jurnal ilmiah yang diterbitkan oleh LPPM Universitas Bina Sarana Informatika. Jurnal ini berisi tentang karya ilmiah hasil penelitian yang bertemakan: Networking, Embedded System, Aplikasi Sains, Animasi Interaktif, Pengolahan Citra, Sistem Pakar, Sistem ...