Arima method with the software minitab and eviews to forecast inflation in semarang Indonesia


Wardono, - Arima method with the software minitab and eviews to forecast inflation in semarang Indonesia. Journal of Theoretical and Applied Information Technology. ISSN 1992-8645

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Abstract

Inflation is one of the indicators to see the economic stability of a region. The value of inflation in Semarang district on January 2014 - April 2016 unstable. Inflation which unstable will impede the economic development in Semarang district, therefore need to be undertaken against the value of the modeling inflation in the future with a method of ARIMA. The purpose of this study is to find a model ARIMA which appropriate to forecasting inflation in Semarang district and to know the forecasting inflation in Semarang district on May 2016 - April 2017 using Minitab and Eviews software. Minitab and Eviews are two statistical packages programs that both can be used to analyze the time series data. The next, the authors wanted to know which of these programs is more accurate than the other in estimating the value of inflation. The methods used in this study is a literature method i.e. authors collect, select and analyze readings related to the issues examined and methods documentation i.e. the author collected data in inflation on January 2010 - April 2016 in Semarang district. Based on the research obtained, the model appropriate to forecasting inflation in Semarang district is a model ARMA(2,1) or ARIMA(2,0,1). The results of the forecasting inflation at Semarang district using Minitab and Eviews software on May 2016 – April 2017 is stable enough. The best model to foresee the next period is ARMA(2,1) or ARIMA(2,0,1) model with software Eviews namely with the following equation: (Formula Presented) The highest inflation occurred on September, October, and November 2016 and lowest Inflation occurred on May and June 2016. © 2005 - 2016 JATIT & LLS. All rights reserved.

Item Type: Article
Subjects: UNSPECIFIED
Fakultas: UNSPECIFIED
Depositing User: iwan kepeg unnes
Date Deposited: 27 Jun 2023 02:16
Last Modified: 28 Jun 2023 08:08
URI: http://lib.unnes.ac.id/id/eprint/59193

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