An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting

International tourism is one indicator of measuring tourism development. Tourism development is important for the national economy since tourism could boost foreign exchange, create business opportunities, and provide employment opportunities. The prediction of foreign tourist numbers in the future...

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Autor principal:	Muhammad Fajar
Formato:	article
Lenguaje:	EN
Publicado:	Department of Mathematics, UIN Sunan Ampel Surabaya 2019
Materias:	foreign tourist, singular spectrum analysis, extreme learning machine Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/ba298ec9006c447c8e15d6f088f2c36c
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spelling	oai:doaj.org-article:ba298ec9006c447c8e15d6f088f2c36c2021-12-02T14:27:48ZAn Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting2527-31592527-316710.15642/mantik.2019.5.2.60-68https://doaj.org/article/ba298ec9006c447c8e15d6f088f2c36c2019-10-01T00:00:00Zhttp://jurnalsaintek.uinsby.ac.id/index.php/mantik/article/view/496https://doaj.org/toc/2527-3159https://doaj.org/toc/2527-3167International tourism is one indicator of measuring tourism development. Tourism development is important for the national economy since tourism could boost foreign exchange, create business opportunities, and provide employment opportunities. The prediction of foreign tourist numbers in the future obtained from forecasting is used as an input parameter for strategy and tourism programs planning. In this paper, the Hybrid Singular Spectrum Analysis – Extreme Learning Machine (SSA-ELM) is used to forecast the number of foreign tourists. Data used is the number of foreign tourists January 1980 - December 2017 taken from Badan Pusat Statistik (Statistics Indonesia). The result of this research concludes that Hybrid SSA-ELM performance is very good at forecasting the number of foreign tourists. It is shown by the MAPE value of 4.91 percent with eight observations out a sample.Muhammad FajarDepartment of Mathematics, UIN Sunan Ampel Surabayaarticleforeign tourist, singular spectrum analysis, extreme learning machineMathematicsQA1-939ENMantik: Jurnal Matematika, Vol 5, Iss 2, Pp 60-68 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	foreign tourist, singular spectrum analysis, extreme learning machine Mathematics QA1-939
spellingShingle	foreign tourist, singular spectrum analysis, extreme learning machine Mathematics QA1-939 Muhammad Fajar An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
description	International tourism is one indicator of measuring tourism development. Tourism development is important for the national economy since tourism could boost foreign exchange, create business opportunities, and provide employment opportunities. The prediction of foreign tourist numbers in the future obtained from forecasting is used as an input parameter for strategy and tourism programs planning. In this paper, the Hybrid Singular Spectrum Analysis – Extreme Learning Machine (SSA-ELM) is used to forecast the number of foreign tourists. Data used is the number of foreign tourists January 1980 - December 2017 taken from Badan Pusat Statistik (Statistics Indonesia). The result of this research concludes that Hybrid SSA-ELM performance is very good at forecasting the number of foreign tourists. It is shown by the MAPE value of 4.91 percent with eight observations out a sample.
format	article
author	Muhammad Fajar
author_facet	Muhammad Fajar
author_sort	Muhammad Fajar
title	An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
title_short	An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
title_full	An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
title_fullStr	An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
title_full_unstemmed	An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
title_sort	application of hybrid forecasting singular spectrum analysis – extreme learning machine method in foreign tourists forecasting
publisher	Department of Mathematics, UIN Sunan Ampel Surabaya
publishDate	2019
url	https://doaj.org/article/ba298ec9006c447c8e15d6f088f2c36c
work_keys_str_mv	AT muhammadfajar anapplicationofhybridforecastingsingularspectrumanalysisextremelearningmachinemethodinforeigntouristsforecasting AT muhammadfajar applicationofhybridforecastingsingularspectrumanalysisextremelearningmachinemethodinforeigntouristsforecasting
_version_	1718391275979276288

An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting

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