TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 16, No 4: August 2018

A Novel Forecasting Based on Automatic-optimized Fuzzy Time Series

Yusuf Priyo Anggodo (Brawijaya University)
Wayan Firdaus Mahmudy (Brawijaya University)



Article Info

Publish Date
01 Aug 2018

Abstract

In this paper, we propose a new method for forecasting based on automatic-optimized fuzzy time series to forecast Indonesia Inflation Rate (IIR). First, we propose the forecasting model of two-factor high-order fuzzy-trend logical relationships groups (THFLGs) for predicting the IIR. Second, we propose the interval optimization using automatic clustering and particle swarm optimization (ACPSO) to optimize the interval of main factor IIR and secondary factor SF, where SF = {Customer Price Index (CPI), the Bank of Indonesia (BI) Rate, Rupiah Indonesia /US Dollar (IDR/USD) Exchange rate, Money Supply}. The proposed method gets lower root mean square error (RMSE) than previous methods.

Copyrights © 2018






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...