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PUBLIC PERCEPTION OF AMIL ZAKAT INSTITUTIONS IN INDONESIA: INSIGHT DISCOVERY FROM MACHINE LEARNING

JEBIS (Jurnal Ekonomi dan Bisnis Islam) · Vol. 9 No. 2 (2023) · pp. 373–400

DOI
10.20473/jebis.v9i2.45416
ISSN
2527-3027, 2442-6563
Published
2023-12-01
Publisher
Universitas Airlangga
Language
eng
License
creativecommons.org/licenses/by-nc-sa/4.0

Abstract

This study aims to identify the most popular topics and words in conversations on Twitter with the topic of Amil Zakat in Indonesia. This research also aims to identify the sentiments and emotions of netizens about the Amil Zakat in Indonesia. This study uses a qualitative method with a sentiment analysis approach with the help of Orange Data Mining. The data used are tweets from Twitter taken from 16 to 23 April 2023. Researchers used the keywords "Amil Zakat" "Lembaga Zakat" and "Lembaga Amil Zakat" to get a total of 1,000 tweets. The results of the study show that the words "Zakat" "Badan" and "Nasional" are the three words that appear most often in discussions of Amil Zakat institutions on Twitter. These three words refer to the BAZNAS, where based on the metadata processed in this study, many people, individuals, and institutions distribute their zakat through BAZNAS. Overall, Twitter is dominated by tweets with neutral sentiments, shown by happy emotions, as much as 93.51% of the total tweets. Amil Zakat can increase the intensity of communication through social media especially regarding solicitations for the community, as well as achieving the collection and distribution of zakat funds as a form of information disclosure to the public

Keywords

Collaboration network of the authors

40 authors · 86 co-authorship links · 15 across different organisations · showing the 40 most connected

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

  • Universitas Airlangga
  • Universitas Negeri Surabaya
  • Universiti Sains Malaysia
  • Yarmouk University
  • Universiti Teknologi MARA
  • Bandung Institute of Technology
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Dyah Permata SariUniversitas Negeri Surabaya3
Muhammad RifqiYarmouk University3
Clarashinta CanggihUniversitas Airlangga2
Ahmad Ajib RidlwanAffiliation unknown2
Shafinar IsmailAffiliation unknown2
Hariyanto HariyantoAffiliation unknown2
Sulistya RusgiantoAffiliation unknown2
Nailul AuthorAffiliation unknown2
Siti ZulaikhaAffiliation unknown2
Mohamed BattourAffiliation unknown2
Imron MawardiUniversitas Airlangga1
Zaimy Johana JohanUniversiti Teknologi MARA1
Rosa Prafitri JuniartiAffiliation unknown1
Erika TakidahAffiliation unknown1
Muhammad Nafik Hadi RyandonoAffiliation unknown1
Azreen Hamiza Abdul AzizAffiliation unknown1
Khusnul FikriyahAffiliation unknown1
Syazwani Abd RahimAffiliation unknown1
Hasan AedyAffiliation unknown1
La Ode AlimusaAffiliation unknown1
Adinda Septiani MAffiliation unknown1
Azhar AlamAffiliation unknown1
Danang Dwi NurrochmanAffiliation unknown1
Estina RahmawatiAffiliation unknown1
Rifki Fajar SubekhiAffiliation unknown1
Sri HerianingrumAffiliation unknown1
Angga Khoerul UmamAffiliation unknown1
Fadillah Nur SyafiraAffiliation unknown1
Yusuf KurniawanBandung Institute of Technology1
Hindah MustikaAffiliation unknown1
Lintang Titian PurbasariAffiliation unknown1
Donna Vanny AramintaAffiliation unknown1
Qudziyah QudziyahAffiliation unknown1
Lina Nugraha RaniAffiliation unknown1
Noraini Bt Mohd AriffinAffiliation unknown1
Melananda Risky AuliaAffiliation 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://e-journal.unair.ac.id/JEBIS/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">PUBLIC PERCEPTION OF AMIL ZAKAT INSTITUTIONS IN INDONESIA: INSIGHT DISCOVERY FROM MACHINE LEARNING</dc:title>
	<dc:creator>Timur, Yan Putra</dc:creator>
	<dc:creator>Ratnasari, Ririn Tri</dc:creator>
	<dc:creator>Pitchay, Anwar Allah</dc:creator>
	<dc:creator>Jamilu, Usman </dc:creator>
	<dc:subject xml:lang="en-US">Amil Zakat Institutions</dc:subject>
	<dc:subject xml:lang="en-US">Sentiment Analysis</dc:subject>
	<dc:subject xml:lang="en-US">Twitter</dc:subject>
	<dc:subject xml:lang="en-US">Machine Learning</dc:subject>
	<dc:subject xml:lang="en-US">Orange Data Mining</dc:subject>
	<dc:description xml:lang="en-US">This study aims to identify the most popular topics and words in conversations on Twitter with the topic of Amil Zakat in Indonesia. This research also aims to identify the sentiments and emotions of netizens about the Amil Zakat in Indonesia. This study uses a qualitative method with a sentiment analysis approach with the help of Orange Data Mining. The data used are tweets from Twitter taken from 16 to 23 April 2023. Researchers used the keywords "Amil Zakat" "Lembaga Zakat" and "Lembaga Amil Zakat" to get a total of 1,000 tweets. The results of the study show that the words "Zakat" "Badan" and "Nasional" are the three words that appear most often in discussions of Amil Zakat institutions on Twitter. These three words refer to the BAZNAS, where based on the metadata processed in this study, many people, individuals, and institutions distribute their zakat through BAZNAS. Overall, Twitter is dominated by tweets with neutral sentiments, shown by happy emotions, as much as 93.51% of the total tweets. Amil Zakat can increase the intensity of communication through social media especially regarding solicitations for the community, as well as achieving the collection and distribution of zakat funds as a form of information disclosure to the public</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Airlangga</dc:publisher>
	<dc:date>2023-12-01</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://e-journal.unair.ac.id/JEBIS/article/view/45416</dc:identifier>
	<dc:identifier>10.20473/jebis.v9i2.45416</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ekonomi dan Bisnis Islam (Journal of Islamic Economics and Business); Vol. 9 No. 2 (2023): JULY - DECEMBER 2023; 373-400</dc:source>
	<dc:source>2527-3027</dc:source>
	<dc:source>2442-6563</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://e-journal.unair.ac.id/JEBIS/article/view/45416/27123</dc:relation>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc-sa/4.0</dc:rights>
</oai_dc:dc>