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MODELING AND FORECASTING THE TOTAL VOLUME OF GOODS TRANSPORTED BY RAIL IN INDONESIA USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA)

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 2 (2025) · hlm. 829–842

DOI
10.30598/barekengvol19iss2pp829-842
ISSN
2615-3017, 1978-7227
Terbit
2025-04-01
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Transportation has an important role in supporting the mobility of people in Indonesia. Trains are included in the most widely used transportation category because they are effective and efficient, not only transporting passengers, trains also have a role in the distribution of goods. This study aims to model and forecast total volume of goods transported through rail transportation in Indonesia using the Seasonal Autoregressive Integrated Moving Average (SARIMA) Method because the data has seasonal trend. The data used comes from the Central Statistics Agency (BPS) from January 2013 to April 2024. The results were obtained that the SARIMA (0,1,1)(0,1,1)12 model is the best model with a MAPE value of 0.96% which is included in the category of accurate model. In addition to being an additional insight, this research can also be a reference in the management of railway transportation considering the number of uses both passengers, the distribution of goods that continue to increase, and can be recommendation for other research that same topic with it.

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  • Universitas Airlangga
  • Institut Teknologi Sepuluh Nopember
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  • Organisasi sama
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Rekan penulisOrganisasiArtikel bersama
Toha SaifudinUniversitas Airlangga3
Dita AmeliaUniversitas Airlangga3
Elly AnaUniversitas Airlangga2
Mega Kurnia DyaksaUniversitas Airlangga2
Anggi Triya VionitaUniversitas Airlangga2
Anisah Nabilah GhasaniUniversitas Airlangga2
Suliyanto SuliyantoUniversitas Airlangga2
Ardi KurniawanUniversitas Airlangga2
Heri KuswantoInstitut Teknologi Sepuluh Nopember1
Idrus SyahzaqiInstitut Teknologi Sepuluh Nopember1
Magdalena EffendiInstitut Teknologi Sepuluh Nopember1
Hasri RahmawatiInstitut Teknologi Sepuluh Nopember1
Nabila NurdinUniversitas Airlangga1
Bryan Given Christiano GinzelUniversitas Airlangga1
Jovansha AriyawanUniversitas Airlangga1
Mohammad Noufal UbadahUniversitas Airlangga1
Maria Setya DewantiUniversitas Airlangga1
Aurelia Islami AzisUniversitas Airlangga1
Muhammad Rosyid Ridho Az ZuhroUniversitas Airlangga1
Tentri Ryan RahmanitaUniversitas Airlangga1
Nuzulia AnidaUniversitas Airlangga1
Nabila Angel NafishaUniversitas Airlangga1
Ameliatul 'IffahUniversitas Airlangga1

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://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">MODELING AND FORECASTING THE TOTAL VOLUME OF GOODS TRANSPORTED BY RAIL IN INDONESIA USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA)</dc:title>
	<dc:creator>Syahzaqi, Idrus</dc:creator>
	<dc:creator>Sediono, Sediono</dc:creator>
	<dc:creator>Anggakusuma, Aurellia Calista</dc:creator>
	<dc:creator>Wieldyanisa, Ezha Easyfa</dc:creator>
	<dc:creator>Oktavia, Sabrina Salsa</dc:creator>
	<dc:description xml:lang="en-US">Transportation has an important role in supporting the mobility of people in Indonesia. Trains are included in the most widely used transportation category because they are effective and efficient, not only transporting passengers, trains also have a role in the distribution of goods. This study aims to model and forecast total volume of goods transported through rail transportation in Indonesia using the Seasonal Autoregressive Integrated Moving Average (SARIMA) Method because the data has seasonal trend. The data used comes from the Central Statistics Agency (BPS) from January 2013 to April 2024. The results were obtained that the SARIMA (0,1,1)(0,1,1)12 &amp;nbsp;model is the best model with a MAPE value of 0.96% which is included in the category of accurate model. In addition to being an additional insight, this research can also be a reference in the management of railway transportation considering the number of uses both passengers, the distribution of goods that continue to increase, and can be recommendation for other research that same topic with it.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-04-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14369</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss2pp829-842</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application; 829-842</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss2year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14369/9877</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Idrus Syahzaqi, Sediono Sediono, Aurellia Calista Anggakusuma, Ezha Easyfa Wieldyanisa, Sabrina Salsa Oktavia</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>