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PEMILIHAN MODEL ARFIMA-GPH DAN INTERVENSI MULTI INPUT PADA INDEKS HARGA PERDAGANGAN BESAR INDONESIA

Vivi Dina Melani  -  Universitas Syiah Kuala, Indonesia
*Miftahuddin Miftahuddin orcid scopus  -  Universitas Syiah Kuala (USK), Indonesia
Muhammad Subianto  -  Universitas Syiah Kuala, Indonesia
Open Access Copyright 2022 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

IHPBI is an early indicator in consumer price analysis. When the IHPBI increases, it results in inflation. When inflation occurs, Indonesia's economic stability begins to be disturbed, so in order to suppress inflation, the government raises interest rates and when the circulation of money begins to decrease, the prices of goods and services will return to normal. This research to see IHPBI in the next 3 years through the ARFIMA method and multi-input intervention with the condition that the data must contain long memory and have an intervention pattern. This is done to determine the selected model, namely ARFIMA (1,d,0) with a d value of 0.1579, intervention in January 2009 with ARIMA (1,1,1) of order (b=0, s=1, r=1) and November 2013 intervention with ARIMA (1,1,2) order(b=1, s=1, r=0).

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Keywords: IHPBI, ARFIMA, intervention, forecasting

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