Melola Discovery

← Melola Discovery

Open access Jurnal

The Forecasting Result Study of the Poverty Line and Number of Poor Population in DIY using DES and ARIMA

Jurnal Matematika, Statistika dan Komputasi · Vol. 21 No. 2 (2025) · pp. 397–407

DOI
10.20956/j.v21i2.36734
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

The poverty rate in DIY, based on BPS data, stands at 11.04%, which remains above the national average of 9.36%. This study aims to predict poverty patterns in the Special Region of Yogyakarta (DIY) using DES and ARIMA methods. The data utilized in this research is sourced from BPS, focusing on poverty line data and the number of impoverished individuals. The DES model is employed to estimate the increase in the poverty line, demonstrating good accuracy with a MAPE value of 2.968%. Meanwhile, the ARIMA(0,2,1) model is applied to forecast a reduction in the number of impoverished individuals, yielding a MAPE of 3.543% through 2028. The findings of this study indicate that government policies have had a positive impact on reducing poverty, although challenges remain. The results of this analysis are expected to guide policymakers in crafting more effective and targeted poverty alleviation strategies in the DIY region. These findings suggest that government policies have had a positive impact on reducing poverty, despite ongoing challenges.

Bahasa Indonesia

Penelitian ini bertujuan untuk memprediksi pola kemiskinan di Daerah Istimewa Yogyakarta (DIY) dengan menggunakan metode Pemulusan Eksponensial Ganda (Double Exponential Smoothing/DES) dan ARIMA (Auto-Regressive Integrated Moving Average). Data yang digunakan dalam penelitian ini bersumber dari Badan Pusat Statistik (BPS), yaitu data garis kemiskinan dan jumlah penduduk miskin. Model DES digunakan untuk memperkirakan kenaikan garis kemiskinan, yang menunjukkan tingkat akurasi yang baik dengan nilai MAPE sebesar 2,968%. Sementara itu, model ARIMA(0,2,1) diterapkan untuk meramalkan penurunan jumlah penduduk miskin dengan MAPE sebesar 3,543% hingga tahun 2028. Temuan penelitian ini menunjukkan adanya dampak positif dari kebijakan pemerintah dalam mengurangi angka kemiskinan, meskipun tantangan masih ada. Hasil analisis ini diharapkan dapat memberikan panduan bagi pembuat kebijakan dalam merancang strategi pengentasan kemiskinan yang lebih efektif dan tepat sasaran di wilayah DIY.

Keywords

Collaboration network of the authors

22 authors · 35 co-authorship links

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

  • Islamic University of Indonesia
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nahdah Ghina HandayaniIslamic University of Indonesia1
Rinaldi SjahrilAffiliation unknown1
A. Sri Sartika Sufiina AhmadAffiliation unknown1
Herlinda YanasariAffiliation unknown1
Muh. Yunus SuriaAffiliation unknown1
Nur Qadri FebriantiAffiliation unknown1
Nur FaizinAffiliation unknown1
Arum Handini PrimandariAffiliation unknown1
Muhammad BariklanaAffiliation unknown1
Octavia RahmawatiAffiliation unknown1
Nanda Lailatul HumairahAffiliation unknown1
Ashabul Akbar MaulanaAffiliation unknown1
Alfa YulianaAffiliation unknown1
Fitri AmaliaAffiliation unknown1
Nabila Dwi FaziraAffiliation unknown1
IKA MEIZA MAHARANIAffiliation unknown1
Mega Luna SuliztiaAffiliation unknown1
Malecita Nur Atala SinggihAffiliation 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) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">The Forecasting Result Study of the Poverty Line and Number of Poor Population in DIY using DES and ARIMA</dc:title>
	<dc:creator xml:lang="en">Azzahra, Shazia Ayesha</dc:creator>
	<dc:creator xml:lang="en">Andini, Wiranti Nugrah</dc:creator>
	<dc:creator xml:lang="en">Fauzan, Achmad</dc:creator>
	<dc:creator xml:lang="en">Sutisna, Irwan</dc:creator>
	<dc:subject xml:lang="en">ARIMA</dc:subject>
	<dc:subject xml:lang="en">Poverty Line</dc:subject>
	<dc:subject xml:lang="en">Double Exponential Smoothing</dc:subject>
	<dc:description xml:lang="en">The poverty rate in DIY, based on BPS data, stands at 11.04%, which remains above the national average of 9.36%. This study aims to predict poverty patterns in the Special Region of Yogyakarta (DIY) using DES and ARIMA methods. The data utilized in this research is sourced from BPS, focusing on poverty line data and the number of impoverished individuals. The DES model is employed to estimate the increase in the poverty line, demonstrating good accuracy with a MAPE value of 2.968%. Meanwhile, the ARIMA(0,2,1) model is applied to forecast a reduction in the number of impoverished individuals, yielding a MAPE of 3.543% through 2028. The findings of this study indicate that government policies have had a positive impact on reducing poverty, although challenges remain. The results of this analysis are expected to guide policymakers in crafting more effective and targeted poverty alleviation strategies in the DIY region. These findings suggest that government policies have had a positive impact on reducing poverty, despite ongoing challenges.</dc:description>
	<dc:description xml:lang="id">Penelitian ini bertujuan untuk memprediksi pola kemiskinan di Daerah Istimewa Yogyakarta (DIY) dengan menggunakan metode Pemulusan Eksponensial Ganda (Double Exponential Smoothing/DES) dan ARIMA (Auto-Regressive Integrated Moving Average). Data yang digunakan dalam penelitian ini bersumber dari Badan Pusat Statistik (BPS), yaitu data garis kemiskinan dan jumlah penduduk miskin. Model DES digunakan untuk memperkirakan kenaikan garis kemiskinan, yang menunjukkan tingkat akurasi yang baik dengan nilai MAPE sebesar 2,968%. Sementara itu, model ARIMA(0,2,1) diterapkan untuk meramalkan penurunan jumlah penduduk miskin dengan MAPE sebesar 3,543% hingga tahun 2028. Temuan penelitian ini menunjukkan adanya dampak positif dari kebijakan pemerintah dalam mengurangi angka kemiskinan, meskipun tantangan masih ada. Hasil analisis ini diharapkan dapat memberikan panduan bagi pembuat kebijakan dalam merancang strategi pengentasan kemiskinan yang lebih efektif dan tepat sasaran di wilayah DIY.</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:type xml:lang="id">text</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/36734</dc:identifier>
	<dc:identifier>10.20956/j.v21i2.36734</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 21 No. 2 (2025): JANUARY 2025; 397-407</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/36734/12436</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>
</oai_dc:dc>