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Firda Dinny Islami
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PEMODELAN FUNGSI TRANSFER DENGAN DETEKSI OUTLIER UNTUK MEMPREDIKSI NILAI INFLASI BERDASARKAN BI RATE (Studi Kasus BI Rate dan Inflasi Periode Januari 2006 sampai Juli 2016) Firda Dinny Islami; Abdul Hoyyi; Dwi Ispriyanti
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (484.317 KB) | DOI: 10.14710/j.gauss.v6i3.19305

Abstract

Inflation control is one of the important things in managing a country besides economic growth. Inflation received special attention in the economy of Indonesia. Every time there is a distortion in the society, politic or economic development, people always relate it to inflation. Low and stable inflation is a stimulator of economic growth. Inflation is also the final target in the monetary policy framework so the need for a central bank role to determine the policy direction. The BI Rate is one of the variables capable of controlling inflation. This study aims to forecast inflation based on the BI Rate using the transfer function model with outlier detection. The transfer function model depends on the parameters b, r, and s. The result of the analysis has been obtained the transfer function model with the value of b = 1, r = 0, s = 1 and the noise series ARMA (2,0). The addition of 16 outliers on the model yielded the best model with the AIC value is -868,56. The forecasting results show that the value of inflation has fluctuated, where in September 2016 it has decreased and then increased until December 2016.Keywords : Inflation, BI Rate, transfer function, outlier detection, AIC
Co-Authors Abdul Hoyyi Dwi Ispriyanti