Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)

Consumer Price Index (CPI) are the indicators used to measure the inflation and deflation of a group of goods and services in general. Forecasting CPI to be important as early detection in facing price hikes. This study uses the SSA and SARIMA. SARIMA a parametric model that requires various assumpt...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Deltha Airuzsh Lubis, Muhamad Budiman Johra, Gumgum Darmawan
Formato:	article
Lenguaje:	EN
Publicado:	Department of Mathematics, UIN Sunan Ampel Surabaya 2017
Materias:	ARIMA, CPI, Seasonal, Singular Spectral Analysis Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/c7746924b05242598b29d37fb3c5a49b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:c7746924b05242598b29d37fb3c5a49b
record_format	dspace
spelling	oai:doaj.org-article:c7746924b05242598b29d37fb3c5a49b2021-12-02T17:36:19ZPeramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)2527-31592527-316710.15642/mantik.2017.3.2.74-82https://doaj.org/article/c7746924b05242598b29d37fb3c5a49b2017-10-01T00:00:00Zhttp://jurnalsaintek.uinsby.ac.id/index.php/mantik/article/view/166https://doaj.org/toc/2527-3159https://doaj.org/toc/2527-3167Consumer Price Index (CPI) are the indicators used to measure the inflation and deflation of a group of goods and services in general. Forecasting CPI to be important as early detection in facing price hikes. This study uses the SSA and SARIMA. SARIMA a parametric model that requires various assumptions while SSA is a nonparametric technique that is free from a variety of assumptions, but both methods require seasonal patterns in the data. Based on the research results, methods of SSA with length window(L) of 24 and a grouping of 4 (1 group of seasonal and 3 groups of trends) and SARIMA models of order (0,1,1), (0,1,1) 6 is the most accurate and reliable models in forecasting CPI to the value Padang Sidempuan City. Forecasting CPI Padang Sidempuan City for the next 5 months with SSA method and SARIMA (0,1,1), (0,1,1) 6 shows the pattern of a trend is likely to increase but forecasting the 5th month with SSA method showed a surge in the value of CPI high or high inflation will occur.Deltha Airuzsh LubisMuhamad Budiman JohraGumgum DarmawanDepartment of Mathematics, UIN Sunan Ampel SurabayaarticleARIMA, CPI, Seasonal, Singular Spectral AnalysisMathematicsQA1-939ENMantik: Jurnal Matematika, Vol 3, Iss 2, Pp 74-82 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	ARIMA, CPI, Seasonal, Singular Spectral Analysis Mathematics QA1-939
spellingShingle	ARIMA, CPI, Seasonal, Singular Spectral Analysis Mathematics QA1-939 Deltha Airuzsh Lubis Muhamad Budiman Johra Gumgum Darmawan Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
description	Consumer Price Index (CPI) are the indicators used to measure the inflation and deflation of a group of goods and services in general. Forecasting CPI to be important as early detection in facing price hikes. This study uses the SSA and SARIMA. SARIMA a parametric model that requires various assumptions while SSA is a nonparametric technique that is free from a variety of assumptions, but both methods require seasonal patterns in the data. Based on the research results, methods of SSA with length window(L) of 24 and a grouping of 4 (1 group of seasonal and 3 groups of trends) and SARIMA models of order (0,1,1), (0,1,1) 6 is the most accurate and reliable models in forecasting CPI to the value Padang Sidempuan City. Forecasting CPI Padang Sidempuan City for the next 5 months with SSA method and SARIMA (0,1,1), (0,1,1) 6 shows the pattern of a trend is likely to increase but forecasting the 5th month with SSA method showed a surge in the value of CPI high or high inflation will occur.
format	article
author	Deltha Airuzsh Lubis Muhamad Budiman Johra Gumgum Darmawan
author_facet	Deltha Airuzsh Lubis Muhamad Budiman Johra Gumgum Darmawan
author_sort	Deltha Airuzsh Lubis
title	Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
title_short	Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
title_full	Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
title_fullStr	Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
title_full_unstemmed	Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
title_sort	peramalan indeks harga konsumen dengan metode singular spectral analysis (ssa) dan seasonal autoregressive integrated moving average (sarima)
publisher	Department of Mathematics, UIN Sunan Ampel Surabaya
publishDate	2017
url	https://doaj.org/article/c7746924b05242598b29d37fb3c5a49b
work_keys_str_mv	AT delthaairuzshlubis peramalanindekshargakonsumendenganmetodesingularspectralanalysisssadanseasonalautoregressiveintegratedmovingaveragesarima AT muhamadbudimanjohra peramalanindekshargakonsumendenganmetodesingularspectralanalysisssadanseasonalautoregressiveintegratedmovingaveragesarima AT gumgumdarmawan peramalanindekshargakonsumendenganmetodesingularspectralanalysisssadanseasonalautoregressiveintegratedmovingaveragesarima
_version_	1718379908516806656

Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)

Ejemplares similares