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ANALISIS PERBANDINGAN MENGGUNAKAN ARIMA DAN BOOTSTRAP PADA PERAMALAN NILAI EKSPOR INDONESIA

Unnes Journal of Mathematics · Vol. 5 No. 1 (2017) · pp. 31–38

DOI
10.15294/ujm.v5i1.13102
ISSN
2460-5859, 2252-6943
Published
2017-02-27
Publisher
Universitas Negeri Semarang
Language
eng

Abstract

In this research used the data export value of Indonesia as a case study. Indonesia's export would be predicted using ARIMA and bootstrap methods with the help of the program R 2.11.1. Bootstrap method used is bootstrap the ARIMA process. ARIMA method is one of the most common methods used in modeling of time series. However on certain data time series models can not guarantee the fulfillment of the assumptions in the classical statistical analysis. Bootstrap methods can be used in situations where standard assumptions are not met. The main objective of this study is to compare the methods ARIMA and bootstrap the Indonesian export data so as to obtain the best forecasting method that will be used to forecast the data export value of Indonesia for the next period. Based on the results of the two models forecasting, it would have been the result of forecasting that has the smallest value of standard error and approach the original data. Results forecasting export value of Indonesia on ARIMA (1,1,2) has the smallest value and the standard error tends to approach the original data when compared to bootstrap the process models ARIMA (1,1,2). Then ARIMA method is the best forecasting method. Next will be forecasting for the months of April to December 2015 using ARIMA method as the best method.

Collaboration network of the authors

40 authors · 182 co-authorship links · 12 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • State University of Semarang
  • Universitas Airlangga
  • Universitas Halu Oleo
  • University of Miyazaki
  • State University of Malang
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Emi PujiastutiState University of Semarang9
Scolastika MarianiState University of Semarang8
Amin SuyitnoAffiliation unknown6
Putriaji HendikawatiAffiliation unknown6
Walid WalidState University of Semarang6
Fathur RokhmanState University of Semarang5
Masrukan MasrukanState University of Semarang5
Mulyono MulyonoAffiliation unknown4
Heri YantoAffiliation unknown3
Gunawan TjokroAffiliation unknown3
Abdul RajagukgukAffiliation unknown3
Kartono KartonoUniversitas Airlangga3
Iwan JunaediState University of Semarang3
Sunarmi SunarmiAffiliation unknown3
Arief AgoestantoAffiliation unknown3
Iqbal KharisudinAffiliation unknown3
Nurkaromah DwidayatiAffiliation unknown3
Rochmad RochmadAffiliation unknown3
Isti HidayahAffiliation unknown3
Subhan SubhanUniversitas Halu Oleo2
Dwi ArifaAffiliation unknown2
Heriyanto HeriyantoAffiliation unknown2
Aisyah Fany AchmaliaAffiliation unknown2
Nuriana Rachmani DewiAffiliation unknown2
Rohimatul AzizahAffiliation unknown2
Wardono WardonoAffiliation unknown2
Mohammad AsikinAffiliation unknown2
YL SukestiyarnoAffiliation unknown2
Dwijanto DwijantoAffiliation unknown2
Hardi SuyitnoAffiliation unknown2
Kartono KartonoState University of Semarang1
Andi Saparuddin NurState University of Semarang1
Rochmad RochmadState University of Semarang1
Arif WidiyatmokoState University of Semarang1
Daiki NakamuraUniversity of Miyazaki1
Sudarmin SudarminState University of Semarang1
Yudhi UtomoState University of Malang1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/ujm/oai, first harvested 6 Nov 2026, last seen 6 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">ANALISIS PERBANDINGAN MENGGUNAKAN ARIMA DAN BOOTSTRAP PADA PERAMALAN NILAI EKSPOR INDONESIA</dc:title>
	<dc:creator>Cynthia, Ari</dc:creator>
	<dc:creator>Sugiman, Sugiman</dc:creator>
	<dc:creator>Zaenuri, Zaenuri</dc:creator>
	<dc:description xml:lang="en-US">In this research used the data export value of Indonesia as a case study. Indonesia's export would be predicted using ARIMA and bootstrap methods with the help of the program R 2.11.1. Bootstrap method used is bootstrap the ARIMA process. ARIMA method is one of the most common methods used in modeling of time series. However on certain data time series models can not guarantee the fulfillment of the assumptions in the classical statistical analysis. Bootstrap methods can be used in situations where standard assumptions are not met. The main objective of this study is to compare the methods ARIMA and bootstrap the Indonesian export data so as to obtain the best forecasting method that will be used to forecast the data export value of Indonesia for the next period. Based on the results of the two models forecasting, it would have been the result of forecasting that has the smallest value of standard error and approach the original data. Results forecasting export value of Indonesia on ARIMA (1,1,2) has the smallest value and the standard error tends to approach the original data when compared to bootstrap the process models ARIMA (1,1,2). Then ARIMA method is the best forecasting method. Next will be forecasting for the months of April to December 2015 using ARIMA method as the best method.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2017-02-27</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/sju/ujm/article/view/13102</dc:identifier>
	<dc:identifier>10.15294/ujm.v5i1.13102</dc:identifier>
	<dc:source xml:lang="en-US">Unnes Journal of Mathematics; Vol 5 No 1 (2016); 31-38</dc:source>
	<dc:source>2460-5859</dc:source>
	<dc:source>2252-6943</dc:source>
	<dc:source>10.15294/ujm.v5i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/ujm/article/view/13102/7183</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2017 Unnes Journal of Mathematics</dc:rights>
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