ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER

The inflation data is one of the financial time series data which often has high volatility. It is caused by the presence of outliers in the data. Therefore, it is necessary to analyze forecasting that can make all the assumptions are fulled without having to ignore the presence of outliers. The aim...

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Main Authors: Suparti Suparti, Alfi Faridatus Sa'adah
Format: Article
Language:English
Published: Universitas Diponegoro 2015-06-01
Series:Media Statistika
Online Access:https://ejournal.undip.ac.id/index.php/media_statistika/article/view/9198
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author Suparti Suparti
Alfi Faridatus Sa'adah
author_facet Suparti Suparti
Alfi Faridatus Sa'adah
author_sort Suparti Suparti
collection DOAJ
description The inflation data is one of the financial time series data which often has high volatility. It is caused by the presence of outliers in the data. Therefore, it is necessary to analyze forecasting that can make all the assumptions are fulled without having to ignore the presence of outliers. The aim of this study is analyzing the inflation data in Indonesia using ARIMA model with the outlier detection. By modeling annual inflation data in December 2006 to December 2013 there are two types of outlier that are additive outlier (AO) and level shift (LS) outlier. The results show that The ARIMA model with the addition of outlier are better than the ARIMA model without outlier. The ARIMA ([1.12], 1.0) model with the addition of 19 outliers meet to the all assumptions that are the significance parameters, normality, homoscedasticity, and independence of residuals as well as the smallest MSE value.   Keywords: Inflation, ARIMA, Outlier, MSE
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spelling doaj.art-3672896bb12c429e9df2690b49bdf9e12022-12-22T01:33:02ZengUniversitas DiponegoroMedia Statistika1979-36932477-06472015-06-018111110.14710/medstat.8.1.1-117695ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIERSuparti Suparti0Alfi Faridatus Sa'adah1Departemen Statistika, Fakultas Sains dan Matematika, Universitas DiponegoroDepartemen Statistika, Fakultas Sains dan Matematika, Universitas DiponegoroThe inflation data is one of the financial time series data which often has high volatility. It is caused by the presence of outliers in the data. Therefore, it is necessary to analyze forecasting that can make all the assumptions are fulled without having to ignore the presence of outliers. The aim of this study is analyzing the inflation data in Indonesia using ARIMA model with the outlier detection. By modeling annual inflation data in December 2006 to December 2013 there are two types of outlier that are additive outlier (AO) and level shift (LS) outlier. The results show that The ARIMA model with the addition of outlier are better than the ARIMA model without outlier. The ARIMA ([1.12], 1.0) model with the addition of 19 outliers meet to the all assumptions that are the significance parameters, normality, homoscedasticity, and independence of residuals as well as the smallest MSE value.   Keywords: Inflation, ARIMA, Outlier, MSEhttps://ejournal.undip.ac.id/index.php/media_statistika/article/view/9198
spellingShingle Suparti Suparti
Alfi Faridatus Sa'adah
ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER
Media Statistika
title ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER
title_full ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER
title_fullStr ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER
title_full_unstemmed ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER
title_short ANALISIS DATA INFLASI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DENGAN PENAMBAHAN OUTLIER
title_sort analisis data inflasi indonesia menggunakan model autoregressive integrated moving average arima dengan penambahan outlier
url https://ejournal.undip.ac.id/index.php/media_statistika/article/view/9198
work_keys_str_mv AT supartisuparti analisisdatainflasiindonesiamenggunakanmodelautoregressiveintegratedmovingaveragearimadenganpenambahanoutlier
AT alfifaridatussaadah analisisdatainflasiindonesiamenggunakanmodelautoregressiveintegratedmovingaveragearimadenganpenambahanoutlier