Melola Discovery

← Melola Discovery

Akses terbuka Jurnal SINTA 1

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

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

DOI
10.20473/jebis.v9i2.45416
ISSN
2527-3027, 2442-6563
Terbit
2023-12-01
Penerbit
Universitas Airlangga
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc-sa/4.0

Abstrak

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

Kata kunci

Jaringan kolaborasi para penulis

40 penulis · 86 tautan kepenulisan bersama · 15 lintas organisasi · menampilkan 40 yang paling banyak terhubung

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

  • Universitas Airlangga
  • Universitas Negeri Surabaya
  • Universiti Sains Malaysia
  • Yarmouk University
  • Universiti Teknologi MARA
  • Bandung Institute of Technology
  • Afiliasi tidak diketahui
  • 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
Dyah Permata SariUniversitas Negeri Surabaya3
Muhammad RifqiYarmouk University3
Clarashinta CanggihUniversitas Airlangga2
Ahmad Ajib RidlwanAfiliasi tidak diketahui2
Shafinar IsmailAfiliasi tidak diketahui2
Hariyanto HariyantoAfiliasi tidak diketahui2
Sulistya RusgiantoAfiliasi tidak diketahui2
Nailul AuthorAfiliasi tidak diketahui2
Siti ZulaikhaAfiliasi tidak diketahui2
Mohamed BattourAfiliasi tidak diketahui2
Imron MawardiUniversitas Airlangga1
Zaimy Johana JohanUniversiti Teknologi MARA1
Rosa Prafitri JuniartiAfiliasi tidak diketahui1
Erika TakidahAfiliasi tidak diketahui1
Muhammad Nafik Hadi RyandonoAfiliasi tidak diketahui1
Azreen Hamiza Abdul AzizAfiliasi tidak diketahui1
Khusnul FikriyahAfiliasi tidak diketahui1
Syazwani Abd RahimAfiliasi tidak diketahui1
Hasan AedyAfiliasi tidak diketahui1
La Ode AlimusaAfiliasi tidak diketahui1
Adinda Septiani MAfiliasi tidak diketahui1
Azhar AlamAfiliasi tidak diketahui1
Danang Dwi NurrochmanAfiliasi tidak diketahui1
Estina RahmawatiAfiliasi tidak diketahui1
Rifki Fajar SubekhiAfiliasi tidak diketahui1
Sri HerianingrumAfiliasi tidak diketahui1
Angga Khoerul UmamAfiliasi tidak diketahui1
Fadillah Nur SyafiraAfiliasi tidak diketahui1
Yusuf KurniawanBandung Institute of Technology1
Hindah MustikaAfiliasi tidak diketahui1
Lintang Titian PurbasariAfiliasi tidak diketahui1
Donna Vanny AramintaAfiliasi tidak diketahui1
Qudziyah QudziyahAfiliasi tidak diketahui1
Lina Nugraha RaniAfiliasi tidak diketahui1
Noraini Bt Mohd AriffinAfiliasi tidak diketahui1
Melananda Risky AuliaAfiliasi tidak diketahui1

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://e-journal.unair.ac.id/JEBIS/oai, pertama di-harvest 8 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">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>