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Advanced digital competency assessment of vocational teachers': A new approach based on fuzzy-analytical hierarcy process

IAES International Journal of Artificial Intelligence · Vol. 13 No. 3 (2024) · hlm. 2781–2795

DOI
10.11591/ijai.v13.i3.pp2781-2795
ISSN
2252-8938, 2089-4872
Terbit
2024-09-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Teachers need digital competence to adapt easily to the current digital era. This study tries to discover the perceptions of vocational high school (VHS) teachers in Indonesia related to advanced digital competencies, which include information, communication, content creation, digital security, and problem-solving competencies. The multi-criteria Analytical Hierarchy Process (AHP) problem-solving method is used to rank the priority digital competencies that are most mastered by the respondents, and then their performance is validated by the fuzzy AHP artificial intelligence-based method. A poll was conducted with 392 respondents, with the research instrument adopting the digital competency measurement platform from DigComp. The study's results show that the fuzzy AHP method has proven that the classical AHP method is a very good way to prioritize VHS teachers' digital skills based on several factors. The two methods gave almost identical results in determining the priority order of VHS teacher digital competencies. The survey results reveal that VHS teachers in Indonesia must immediately develop their skills in terms of digital content creation and digital security. Teachers, teacher professional organizations, and decision-makers are expected to use the findings of this study as a reference in implementing VHS teacher digital competency improvement trainings.

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  • Indonesia University of Education
  • Jenderal Soedirman University
  • Universitas Syiah Kuala
  • State University of Jakarta
  • National Research and Innovation Agency
  • Universitas Nurtanio
  • Mercu Buana University
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Rekan penulisOrganisasiArtikel bersama
Zulkarnain JalilUniversitas Syiah Kuala2
Wahyu WidanartoJenderal Soedirman University2
Mukhtar EffendiJenderal Soedirman University2
Sib Krishna GhoshalUniversity of Technology Malaysia2
Candra KurniawanNational Research and Innovation Agency2
Johanes Adi PrihantonoUniversitas Nurtanio2
Ike Yuni WulandariIndonesia University of Education2
Agus SetiawanIndonesia University of Education2
Heni PuspitaIndonesia University of Education2
Erlian SupriyantoUniversitas Nurtanio2
Muhammad Nur HudhaSebelas Maret University1
Anna PermanasariIndonesia University of Education1
Ida HamidahIndonesia University of Education1
Hasbullah HasbullahUniversitas Islam Negeri Sultan Syarif Kasim Riau1
Mindit EriyadiPoliteknik Enjinering Indorama1
Sandy Bhawana MuliaPoliteknik Manufaktur Bandung1
Eva Novita SariUniversitas Syiah Kuala1
A B IsmailUniversitas Syiah Kuala1
Bambang SoegijonoUniversity of Indonesia1
Aditia PradiptaState University of Jakarta1
Supriyanto SupriyantoState University of Semarang1
Sulaeman Deni RamdaniSultan Ageng Tirtayasa University1
Quienera JoshuaUniversiti Malaysia Sarawak1
Emmanuel Obobi TettehfioHo Technical University1
Mudrik AlaydrusMercu Buana University1
Wahyu Tri CahyantoJenderal Soedirman University1
Retno SupriyantiJenderal Soedirman University1
Lazuardi Umar ARiau University1
Dina RahmawatiJenderal Soedirman University1
Tomy TamtowiJenderal Soedirman University1
Jumaeda JatmikaNational Research and Innovation Agency1
Mudrik AlaydrusMercu Buana University1

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Advanced digital competency assessment of vocational teachers': A new approach based on fuzzy-analytical hierarcy process</dc:title>
	<dc:creator>Ramadhan Islami, Aditya</dc:creator>
	<dc:creator>Abdullah, Ade Gafar</dc:creator>
	<dc:creator>Widiaty, Isma</dc:creator>
	<dc:creator>Yulia, Cica</dc:creator>
	<dc:creator>Lukman Hakim, Dadang</dc:creator>
	<dc:creator>Handoko, Erfan</dc:creator>
	<dc:creator>Subekti, Eri</dc:creator>
	<dc:creator>Rahmawati, Sherly</dc:creator>
	<dc:subject xml:lang="en-US">Fuzzy Logic; Multi-Criteria Decision Making; Analytical Hierarchy Process</dc:subject>
	<dc:subject xml:lang="en-US">Advanced digital competences; DigComp platform; Fuzzy-analytical hierarchy process; Multi-criteria decision making; Vocational teachers’</dc:subject>
	<dc:description xml:lang="en-US">Teachers need digital competence to adapt easily to the current digital era. This study tries to discover the perceptions of vocational high school (VHS) teachers in Indonesia related to advanced digital competencies, which include information, communication, content creation, digital security, and problem-solving competencies. The multi-criteria Analytical Hierarchy Process (AHP) problem-solving method is used to rank the priority digital competencies that are most mastered by the respondents, and then their performance is validated by the fuzzy AHP artificial intelligence-based method. A poll was conducted with 392 respondents, with the research instrument adopting the digital competency measurement platform from DigComp. The study's results show that the fuzzy AHP method has proven that the classical AHP method is a very good way to prioritize VHS teachers' digital skills based on several factors. The two methods gave almost identical results in determining the priority order of VHS teacher digital competencies. The survey results reveal that VHS teachers in Indonesia must immediately develop their skills in terms of digital content creation and digital security. Teachers, teacher professional organizations, and decision-makers are expected to use the findings of this study as a reference in implementing VHS teacher digital competency improvement trainings.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US">Universitas Pendidikan Indonesia</dc:contributor>
	<dc:date>2024-09-01</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"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/24662</dc:identifier>
	<dc:identifier>10.11591/ijai.v13.i3.pp2781-2795</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 13, No 3: September 2024; 2781-2795</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v13.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/24662/14087</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>