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ANALISIS PERBANDINGAN MENGGUNAKAN ARIMA DAN BOOTSTRAP PADA PERAMALAN NILAI EKSPOR INDONESIA

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

DOI
10.15294/ujm.v5i1.13102
ISSN
2460-5859, 2252-6943
Terbit
2017-02-27
Penerbit
Universitas Negeri Semarang
Bahasa
eng

Abstrak

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.

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  • State University of Semarang
  • University of Miyazaki
  • State University of Malang
  • VIA University College
  • Dhofar University
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Rekan penulisOrganisasiArtikel bersama
Emi PujiastutiState University of Semarang8
Scolastika MarianiState University of Semarang8
Amin SuyitnoState University of Semarang6
Fathur RokhmanState University of Semarang5
Putriaji HendikawatiState University of Semarang5
Masrukan MasrukanState University of Semarang5
Iwan JunaediState University of Semarang3
Sunarmi SunarmiAfiliasi tidak diketahui3
Walid WalidAfiliasi tidak diketahui3
Iqbal KharisudinAfiliasi tidak diketahui3
Nurkaromah DwidayatiState University of Semarang3
Walid WalidState University of Semarang3
Kartono KartonoState University of Semarang2
Andi Saparuddin NurState University of Semarang2
Rochmad RochmadState University of Semarang2
Dwi ArifaState University of Semarang2
Gunawan TjokroState University of Semarang2
Heri YantoState University of Semarang2
Abdul RajagukgukAfiliasi tidak diketahui2
Kartono KartonoState University of Semarang2
Heriyanto HeriyantoAfiliasi tidak diketahui2
Arief AgoestantoAfiliasi tidak diketahui2
Aisyah Fany AchmaliaAfiliasi tidak diketahui2
Nuriana Rachmani DewiAfiliasi tidak diketahui2
Rohimatul AzizahAfiliasi tidak diketahui2
Isti HidayahState University of Semarang2
Mulyono MulyonoAfiliasi tidak diketahui2
Arif WidiyatmokoState University of Semarang1
Subhan SubhanState University of Semarang1
Daiki NakamuraUniversity of Miyazaki1
Sudarmin SudarminState University of Semarang1
Yudhi UtomoState University of Malang1
E. JuulVIA University College1
Arief RohmanState University of Semarang1
Muhammad KhafidState University of Semarang1
Souad Ahmed EzzeroualiDhofar University1
Gunawan TjokroAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/ujm/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 6 Nov 2026.
Metadata asli (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>
</oai_dc:dc>