Analisis Model Intervensi Fungsi Step Ganda untuk Peramalan Inflasi Indonesia

(Studi Kasus: Inflasi Indonesia Tahun 2009-2017)

  • Masrawanti Masrawanti Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Sri Wahyuningsih Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Memi Nor Hayati Laboratorium Statistika Terapan FMIPA Universitas Mulawarman

Abstract

The intervention model is one time series model that can be used to explain the impact of an intervention caused by external or internal factors that occur in a time series data. This model can also be generally used to explain structural changes in a time series data. The purposes of this study are to determine the intervention model of double step function on the increase of the price of fuel oil to the Indonesia’s inflation (yoy), and forecasting Indonesia's inflation (yoy) period 2018. The government's policy to increase of the price of fuel oil in June 2013 and November 2014 is a step intervention because impact of the intervention is permanent. The procedure of forming an intervention model is a double step function that is determining the intervention function that occurs during the research period, dividing the data based on the time of the intervention, modelling, estimating parameters, testing diagnostics, and selecting the best model. Next stage is forming the first and second intervention models. The best model for predicting Indonesia's inflation (yoy) isSARIMA (0,1,1) (1,0,0)12 as the model before the intervention with the order of the first intervention responseand the second intervention response order . The results of forecasting Indonesia's inflation (yoy) in the period 2018 will placed around the average inflation amount 3%.

Published
2020-02-01
How to Cite
MASRAWANTI, Masrawanti; WAHYUNINGSIH, Sri; HAYATI, Memi Nor. Analisis Model Intervensi Fungsi Step Ganda untuk Peramalan Inflasi Indonesia. JURNAL EKSPONENSIAL, [S.l.], v. 10, n. 2, p. 119-126, feb. 2020. ISSN 2085-7829. Available at: <http://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/569>. Date accessed: 26 feb. 2020.