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Sukuk Rating Prediction using Voting Ensemble Strategy

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 1 (2018)

DOI
10.11591/ijece.v8i1.pp299-303
ISSN
2088-8708, 2088-8708
Published
2018-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Islamic finance development has grown into a focal point in many countries accros the globe. Sukuk, in particular, an Islamic investment product that has received growing attention from sovereigns, multinational and national organizations from both developed and emerging economies. Its uses has been aimed to finance investments in a varieties of economic activities and development projects. Despite the promising look of Sukuk, currently there is lack of studies had been to examine and predict the rating of the Sukuk. As a result, many practitioners adopted the conventional bond hence ignore the fact that these two instruments are different in nature. In order to fill the gap in the literature, it is the aim of this research to develop an ensemble model that can be used to predict Sukuk rating. The effectiveness of the proposed models were evaluated using dataset on Sukuk issuance for domestic from 2006 to 2016. The results indicate that the overall performance of the ensemble model is fall short behind the i duction decision tree (IDT) model. However, the class precision of the ensemble model improved, particularly in predicting the lowest rating of Sukuk.

Collaboration network of the authors

27 authors · 61 co-authorship links · 23 across different organisations

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  • International Islamic University Malaysia
  • Syarif Hidayatullah State Islamic University Jakarta
  • Yogyakarta State University
  • University of Indonesia
  • International Centre for Education in Islamic Finance
  • University of Kuala Lumpur
  • Politeknik Negeri Cilacap
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Hasmah MansorInternational Islamic University Malaysia4
Rashidah Funke OlanrewajuInternational Islamic University Malaysia2
Amart SulongInternational Islamic University Malaysia2
Othman Omran KhalifaInternational Islamic University Malaysia2
Hassan DaoUniversity of Kuala Lumpur2
Abdul MutholibInternational Islamic University Malaysia2
Intan Rahmithul Husna YaldiInternational Islamic University Malaysia2
Yasmin Mahira Saiful MunirInternational Islamic University Malaysia2
Nur Atikah Muhamat SalehInternational Islamic University Malaysia2
Noreha Abdul MalikInternational Islamic University Malaysia1
W. IdrisInternational Islamic University Malaysia1
Siti Noorjannah IbrahimInternational Islamic University Malaysia1
Abd Rahman AhlanAffiliation unknown1
A’ang SubiyaktoSyarif Hidayatullah State Islamic University Jakarta1
Husni Teja SukmanaSyarif Hidayatullah State Islamic University Jakarta1
Mir Suhail AlamInternational Islamic University Malaysia1
Malik Arman MorshidiInternational Islamic University Malaysia1
Fatchul ArifinYogyakarta State University1
Didik HariyantoYogyakarta State University1
Arif Ainur RafiqPoliteknik Negeri Cilacap1
Nguyen Vu QuynhLac Hong University1
M. Shabri Abd. MajidInternational Islamic University Malaysia1
Ronald RulindoInternational Islamic University Malaysia1

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.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Sukuk Rating Prediction using Voting Ensemble Strategy</dc:title><dc:creator>Kartiwi, Mira</dc:creator><dc:creator>Gunawan, Teddy Surya</dc:creator><dc:creator>Arundina, Tika</dc:creator><dc:creator>Omar, Mohd Azmi</dc:creator><dc:description>&lt;jats:p&gt;Islamic finance development has grown into a focal point in many countries accros the globe. Sukuk, in particular, an Islamic investment product that has received growing attention from sovereigns, multinational and national organizations from both developed and emerging economies. Its uses has been aimed to finance investments in a varieties of economic activities and development projects. Despite the promising look of Sukuk, currently there is lack of studies had been to examine and predict the rating of the Sukuk. As a result, many practitioners adopted the conventional bond hence ignore the fact that these two instruments are different in nature. In order to fill the gap in the literature, it is the aim of this research to develop an ensemble model that can be used to predict Sukuk rating. The effectiveness of the proposed models were evaluated using dataset on Sukuk issuance for domestic from 2006 to 2016. The results indicate that the overall performance of the ensemble model is fall short behind the i duction decision tree (IDT) model. However, the class precision of the ensemble model improved, particularly in predicting the lowest rating of Sukuk.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2018-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v8i1.pp299-303</dc:identifier><dc:identifier>10.11591/ijece.v8i1.pp299-303</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 1 (2018); 299</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/9721/8769</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>