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A Bibliometric Study: Recommendation based on Artificial Intelligence for iLearning Education

Aptisi Transactions on Technopreneurship (ATT) · Vol. 5 No. 2 (2022) · hlm. 109–117

DOI
10.34306/att.v5i2.279
ISSN
2656-8888, 2655-8807
Terbit
2022-11-30
Penerbit
Pandawan
Bahasa
en
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

Since most students begin their studies online, the LMS platform is frequently used. Universities and colleges play a crucial role in adopting many of its LMS platforms. A web-based application software package called Bibliometrics is used to design, test, and evaluate specific learning processes. LMS will be the dominant artificial intelligence-based solution for managing eLearning starting in early 2021. The principal objective of this project is to develop an artificial intelligence-powered LMS portal that enables students to continue studying and receive the most recent lessons from their teachers. Using the Communicate cloud software and Dialog Flow, a chatbot plugin system connected to the Google platform, and based on current needs, research bibliometrics was developed as an LMS project system. Students can interact with the chatbot anytime to satisfy their learning needs as long as they have an internet connection and a student ID card to access the dashboard. The LMS Platform, which was developed utilizing Bibliometrics and Artificial Intelligence approaches to help students access resources and complete teacher tasks, is a novelty in this work, according to earlier publications that have been evaluated.

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40 penulis · 163 tautan kepenulisan bersama · 50 lintas organisasi · menampilkan 40 yang paling banyak terhubung

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  • Universitas Raharja
  • Satya Wacana Christian University
  • Universitas Catur Insan Cendekia Cirebon
  • Universitas Banten Jaya
  • Universitas Buddhi Dharma
  • Universitas Komputer Indonesia
  • Politeknik Keselamatan Transportasi Jalan
  • Organisasi lain
  • 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
Danny ManonggaSatya Wacana Christian University18
Irwan SembiringSatya Wacana Christian University17
Nuke Puji Lestari SantosoUniversitas Raharja16
Alfiah KhoirunisaUniversitas Raharja10
Po Abas SunaryaUniversitas Raharja9
Hindriyanto Dwi PurnomoSatya Wacana Christian University9
Fitra Putri OgandaUniversitas Raharja6
Dwi ApriliasariUniversitas Raharja6
Eka Purnama HarahapUniversitas Raharja6
Shofiyul MillahUniversitas Raharja6
Agung RizkyUniversitas Raharja5
Natasya Aprila YusufUniversitas Raharja5
Indri HandayaniUniversitas Raharja4
Sudaryono SudaryonoUniversitas Banten Jaya3
Nesti Anggraini SantosoUniversitas Raharja3
Ihsan Nuril HikamUniversitas Raharja3
Aditya MardiansyahUniversitas Raharja3
Adam FaturahmanUniversitas Raharja3
Dwi ApriliasariAfiliasi tidak diketahui3
Alwiyah AlwiyahUniversitas Wiraraja3
Eko SediyonoSatya Wacana Christian University3
Marviola Grace HardiniUniversitas Raharja3
Dwi JulianingsihUniversitas Raharja3
Ahmad RamadanAfiliasi tidak diketahui3
Chandra LukitaUniversitas Catur Insan Cendekia Cirebon2
Desy AprianiUniversitas Raharja2
Nur AzizahUniversitas Raharja2
Mohamad RakhmansyahUniversitas Raharja2
Umi NarimawatiUniversitas Komputer Indonesia2
Joko SiswantoPoliteknik Keselamatan Transportasi Jalan2
Agung RizkyUniversitas Raharja2
Tarisya RamadhanUniversitas Raharja2
Farida AgustinAfiliasi tidak diketahui2
Benny DaniawanUniversitas Buddhi Dharma1

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://att.aptisi.or.id/index.php/att/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">A Bibliometric Study : Recommendation based on Artificial Intelligence for iLearning Education</dc:title>
	<dc:creator xml:lang="en">Lutfiani, Ninda</dc:creator>
	<dc:creator xml:lang="en">Wijono, Sutarto</dc:creator>
	<dc:creator xml:lang="en">Rahardja, Untung</dc:creator>
	<dc:creator xml:lang="en">Iriani, Ade</dc:creator>
	<dc:creator xml:lang="en">Aini, Qurotul</dc:creator>
	<dc:creator xml:lang="en">Septian, Rafly Ananda Dwi</dc:creator>
	<dc:subject xml:lang="en">Bibliometrics</dc:subject>
	<dc:subject xml:lang="en">LMS</dc:subject>
	<dc:subject xml:lang="en">eLearning</dc:subject>
	<dc:subject xml:lang="en">Artificial Intelligent</dc:subject>
	<dc:subject xml:lang="en">Chatbot</dc:subject>
	<dc:description xml:lang="en">Since most students begin their studies online, the LMS platform is frequently used. Universities and colleges play a crucial role in adopting many of its LMS platforms. A web-based application software package called Bibliometrics is used to design, test, and evaluate specific learning processes. LMS will be the dominant artificial intelligence-based solution for managing eLearning starting in early 2021. The principal objective of this project is to develop an artificial intelligence-powered LMS portal that enables students to continue studying and receive the most recent lessons from their teachers. Using the Communicate cloud software and Dialog Flow, a chatbot plugin system connected to the Google platform, and based on current needs, research bibliometrics was developed as an LMS project system. Students can interact with the chatbot anytime to satisfy their learning needs as long as they have an internet connection and a student ID card to access the dashboard. The LMS Platform, which was developed utilizing Bibliometrics and Artificial Intelligence approaches to help students access resources and complete teacher tasks, is a novelty in this work, according to earlier publications that have been evaluated.</dc:description>
	<dc:publisher xml:lang="en">Pandawan</dc:publisher>
	<dc:date>2022-11-30</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">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://att.aptisi.or.id/index.php/att/article/view/279</dc:identifier>
	<dc:identifier>10.34306/att.v5i2.279</dc:identifier>
	<dc:source xml:lang="en">Aptisi Transactions on Technopreneurship (ATT); Vol. 5 No. 2 (2023):  July; 109-117</dc:source>
	<dc:source xml:lang="id">Aptisi Transactions On Technopreneurship (ATT); Vol 5 No 2 (2023):  July; 109-117</dc:source>
	<dc:source>2656-8888</dc:source>
	<dc:source>2655-8807</dc:source>
	<dc:source>10.34306/att.v5i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://att.aptisi.or.id/index.php/att/article/view/279/190</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2022 Ninda Lutfiani, Sutarto Wijono, Untung Rahardja, Ade Iriani, Qurotul Aini, Rafly Ananda Dwi Septian</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>