Melola Discovery

← Melola Discovery

Akses terbuka Jurnal SINTA 3

HYBRID MODEL OF SINGULAR SPECTRUM ANALYSIS WITH AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND FUZZY TIME SERIES FOR INDONESIAN CRUDE PRICE FORECASTING

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 3 (2024) · hlm. 1519–1526

DOI
10.30598/barekengvol18iss3pp1519-1526
ISSN
2615-3017, 1978-7227
Terbit
2024-07-31
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

This study discusses a hybrid model of Singular Spectrum Analysis (SSA) with Autoregressive Integrated Moving Average (ARIMA) and Fuzzy Time Series (FTS) for forecasting the Indonesian Crude Price (ICP). SSA is considered to capture the deterministic component of the data while the ARIMA and FTS are to represent the stochastics one. The data that used in this study are ICP per month from January 2017 to May 2023. The data from January 2017 to December 2022 are used as insample data, while the data from January to May 2023 are used as outsample data. The insample data is firstly modeled by SSA and the residuals are then modeled by ARIMA, referred to as the hybrid SSA-ARIMA. By the same procedure, the hybrid SSA-FTS model is also constructed to the insample data. Based on the experiment, the hybrid SSA-ARIMA produces Mean Absolute Percentage Error values 8.08% for an insample and 7.10% for an outsample data. These values are less than those obtained by hybrid SSA-FTS. Therefore, the hybrid SSA-ARIMA is recommended for forecasting the monthly ICP.

Jaringan kolaborasi para penulis

20 penulis · 49 tautan kepenulisan bersama · 6 lintas organisasi

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • Sebelas Maret University
  • State University of Semarang
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Irwan SusantoSebelas Maret University3
Yuliana SusantiSebelas Maret University2
Titis Jati NugrahaSebelas Maret University2
İsnandar SlametSebelas Maret University2
Sri SubantiSebelas Maret University2
Sugianto SugiantoState University of Semarang2
Christy Sheldy SuciptoSebelas Maret University1
Hasih PratiwiSebelas Maret University1
Fauzi Nafi'udinSebelas Maret University1
Faradilla ArdiyaniSebelas Maret University1
Alfien Diva KayyisaSebelas Maret University1
Isnandar SlametSebelas Maret University1
Mutiara QalbuSebelas Maret University1
Muhammad Bayu NirwanaSebelas Maret University1
Sugiyanto SugiyantoSebelas Maret University1
Isnandar SlametSebelas Maret University1
Syifa’ Salsabila Gita ParahitaSebelas Maret University1

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) 
<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-US">HYBRID MODEL OF SINGULAR SPECTRUM ANALYSIS WITH AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND FUZZY TIME SERIES FOR INDONESIAN CRUDE PRICE FORECASTING</dc:title>
	<dc:creator>Zukhronah, Etik</dc:creator>
	<dc:creator>Sulandari, Winita</dc:creator>
	<dc:creator>Ilahi, Esa Permata Sari Putri</dc:creator>
	<dc:description xml:lang="en-US">This study discusses a hybrid model of Singular Spectrum Analysis (SSA) with Autoregressive Integrated Moving Average (ARIMA) and Fuzzy Time Series (FTS) for forecasting the Indonesian Crude Price (ICP). SSA is considered to capture the deterministic component of the data while the ARIMA and FTS are to represent the stochastics one. The data that used in this study are ICP per month from January 2017 to May 2023. The data from January 2017 to December 2022 are used as insample data, while the data from January to May 2023 are used as outsample data. The insample data is firstly modeled by SSA and the residuals are then modeled by ARIMA, referred to as the hybrid SSA-ARIMA. By the same procedure, the hybrid SSA-FTS model is also constructed to the insample data. Based on the experiment, the hybrid SSA-ARIMA produces Mean Absolute Percentage Error values 8.08% for an insample and 7.10% for an outsample data. These values are less than those obtained by hybrid SSA-FTS. Therefore, the hybrid SSA-ARIMA is recommended for forecasting the monthly ICP.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-07-31</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/11463</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss3pp1519-1526</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application; 1519-1526</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss3year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/11463/8584</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Etik Zukhronah, Winita Sulandari, Esa Permata Sari Putri Ilahi</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>