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Application of Autoregressive Integrated Moving Average (ARIMA) for Forecasting Inflation Rate in Indonesia

Jurnal Matematika, Statistika dan Komputasi · Vol. 21 No. 2 (2025) · pp. 382–396

DOI
10.20956/j.v21i2.36609
ISSN
2614-8811, 1858-1382
Published
2025-01-12
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

Inflation is one of the indicators to maintain economic stability. Controlling inflation reflects the success of economic growth, while very high or volatile inflation can lead to economic instability. The purpose of this research is to forecast the time series data of inflation rate in Indonesia until the end of 2024 using ARIMA method. The data used in this study are secondary data of monthly inflation rates in Indonesia from January 2003 to May 2024 obtained from the Bank Indonesia website. Based on the research results, the optimal model for forecasting the inflation rate in Indonesia until the end of 2024 is ARIMA (1,0,1) with a MAPE of 6.91%. The forecasting results show a stable and not too significant increase and are still within the target range set by Bank Indonesia and the Government, which is between 1,5% and 3,5% for 2024.

Indonesian

Inflasi merupakan salah satu indikator untuk menjaga kestabilan ekonomi. Pengendalian inflasi mencerminkan keberhasilan pertumbuhan ekonomi, sementara inflasi yang sangat tinggi atau fluktuatif dapat mengakibatkan ketidakstabilan ekonomi. Tujuan dari penelitian ini adalah untuk melakukan peramalan terhadap data deret waktu laju inflasi di Indonesia hingga akhir tahun 2024 dengan menggunakan metode ARIMA. Berdasarkan hasil penelitian, diperoleh model optimal untuk meramalkan laju inflasi di Indonesia hingga akhir tahun 2024 adalah ARIMA(1,0,1) dengan MAPE sebesar 6,91%. Hasil peramalan menunjukkan peningkatan stabil dan tidak terlalu signifikan serta masih berada dalam kisaran target yang ditetapkan oleh Bank Indonesia dan Pemerintah, yaitu antara 1,5% dan 3,5% untuk tahun 2024.

Keywords

Collaboration network of the authors

10 authors · 16 co-authorship links

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Co-authorOrganisationJoint articles
Ainol YaqinAffiliation unknown2
Kurnia Novita SariAffiliation unknown1
Sapto Wahyu IndratnoAffiliation unknown1
Andi FitriawatiAffiliation unknown1
Lutfi MardiantoAffiliation unknown1
Muhammad Naif AbdallahAffiliation unknown1
Faculty of Science, Institut Teknologi Sumatera, South Lampung, Indonesia Department of MathematicsAffiliation unknown1
Faculty of Science, Institut Teknologi dan Sains NU Lampung, Indonesia Department of PhysicsAffiliation unknown1

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.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Application of Autoregressive Integrated Moving Average (ARIMA) for Forecasting Inflation Rate in Indonesia</dc:title>
	<dc:creator xml:lang="en">Saputra, Jova Edri</dc:creator>
	<dc:creator xml:lang="en">Febrianti, Werry</dc:creator>
	<dc:subject xml:lang="en">Inflation</dc:subject>
	<dc:subject xml:lang="en">Time Series Data</dc:subject>
	<dc:subject xml:lang="en">ARIMA</dc:subject>
	<dc:subject xml:lang="en">Economic Stability</dc:subject>
	<dc:description xml:lang="en">Inflation is one of the indicators to maintain economic stability. Controlling inflation reflects the success of economic growth, while very high or volatile inflation can lead to economic instability. The purpose of this research is to forecast the time series data of inflation rate in Indonesia until the end of 2024 using ARIMA method. The data used in this study are secondary data of monthly inflation rates in Indonesia from January 2003 to May 2024 obtained from the Bank Indonesia website. Based on the research results, the optimal model for forecasting the inflation rate in Indonesia until the end of 2024 is ARIMA (1,0,1) with a MAPE of 6.91%. The forecasting results show a stable and not too significant increase and are still within the target range set by Bank Indonesia and the Government, which is between 1,5% and 3,5% for 2024.
 </dc:description>
	<dc:description xml:lang="id">Inflasi merupakan salah satu indikator untuk menjaga kestabilan ekonomi. Pengendalian inflasi mencerminkan keberhasilan pertumbuhan ekonomi, sementara inflasi yang sangat tinggi atau fluktuatif dapat mengakibatkan ketidakstabilan ekonomi. Tujuan dari penelitian ini adalah untuk melakukan peramalan terhadap data deret waktu laju inflasi di Indonesia hingga akhir tahun 2024 dengan menggunakan metode ARIMA. Berdasarkan hasil penelitian, diperoleh model optimal untuk meramalkan laju inflasi di Indonesia hingga akhir tahun 2024 adalah ARIMA(1,0,1) dengan MAPE sebesar 6,91%. Hasil peramalan menunjukkan peningkatan stabil dan tidak terlalu signifikan serta masih berada dalam kisaran target yang ditetapkan oleh Bank Indonesia dan Pemerintah, yaitu antara 1,5% dan 3,5% untuk tahun 2024.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2025-01-12</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://journal.unhas.ac.id/index.php/jmsk/article/view/36609</dc:identifier>
	<dc:identifier>10.20956/j.v21i2.36609</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 21 No. 2 (2025): JANUARY 2025; 382-396</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/36609/12435</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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