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Distribution Based Fuzzy Time Series Markov Chain Models for forecasting Inflation in Bandung

KUBIK: Jurnal Publikasi Ilmiah Matematika · Vol. 7 No. 1 (2022) · hlm. 11–18

DOI
10.15575/kubik.v7i1.18156
ISSN
2686-0341, 2338-0896
Terbit
2022-09-30
Penerbit
Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung
Bahasa
eng

Abstrak

This study discusses the application of the Fuzzy Time Series Markov Chain method which was developed by determining the length of the interval using the distribution method. In the fuzzy forecasting method, the determination of the length of the interval is an important thing that will affect the accuracy of the forecasting results. The development of this forecasting model aims to get better forecasting accuracy results. In this study, general inflation data for the city of Bandung is used for the period January 2016 – June 2021. The data is divided into two groups, namely in sample data and out sample data with a ratio of 90: 10. In the data processing process, the Python programming language is used. Based on the accuracy test using the MAPE method, it can be concluded that this method provides better forecasting results with a MAPE value of 1.16%.

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.uinsgd.ac.id/index.php/kubik/oai, pertama di-harvest 7 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Distribution Based Fuzzy Time Series Markov Chain Models for forecasting Inflation in Bandung</dc:title>
	<dc:creator>Pratiwi, Salsabila Ayu</dc:creator>
	<dc:creator>Rachmatin, Dewi</dc:creator>
	<dc:creator>Marwati, Rini</dc:creator>
	<dc:subject xml:lang="en-US">Fuzzy Time Series Markov Chain</dc:subject>
	<dc:subject xml:lang="en-US">Distribution Based Interval</dc:subject>
	<dc:subject xml:lang="en-US">MAPE</dc:subject>
	<dc:subject xml:lang="en-US">Inflation</dc:subject>
	<dc:subject xml:lang="en-US">Python.</dc:subject>
	<dc:description xml:lang="en-US">This study discusses the application of the Fuzzy Time Series Markov Chain method which was developed by determining the length of the interval using the distribution method. In the fuzzy forecasting method, the determination of the length of the interval is an important thing that will affect the accuracy of the forecasting results. The development of this forecasting model aims to get better forecasting accuracy results. In this study, general inflation data for the city of Bandung is used for the period January 2016 – June 2021. The data is divided into two groups, namely in sample data and out sample data with a ratio of 90: 10. In the data processing process, the Python programming language is used. Based on the accuracy test using the MAPE method, it can be concluded that this method provides better forecasting results with a MAPE value of 1.16%.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung</dc:publisher>
	<dc:date>2022-09-30</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.uinsgd.ac.id/index.php/kubik/article/view/18156</dc:identifier>
	<dc:identifier>10.15575/kubik.v7i1.18156</dc:identifier>
	<dc:source xml:lang="en-US">KUBIK: Jurnal Publikasi Ilmiah Matematika; Vol. 7 No. 1 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika; 11-18</dc:source>
	<dc:source xml:lang="id-ID">KUBIK; Vol 7 No 1 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika; 11-18</dc:source>
	<dc:source>2686-0341</dc:source>
	<dc:source>2338-0896</dc:source>
	<dc:source>10.15575/kubik.v7i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.uinsgd.ac.id/index.php/kubik/article/view/18156/7713</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Salsabila Ayu Pratiwi, Dewi Rachmatin, Rini Marwati</dc:rights>
</oai_dc:dc>