BIBLIOMETRIC ANALYSIS OF MACHINE LEARNING ON DEVELOPMENT RESEARCH FOR EDUCATION IN INDONESIA

Artificial Intelligence – Machine Learning has great potential to help the development of education in Indonesia. So, it is important to map the research that has been done, whereas it can be a strategy to explore the use of Machine Learning for efficient the development of education. This research...

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Bibliographic Details
Published inJP (Jurnal Pendidikan) Vol. 8; no. 1; pp. 29 - 36
Main Author Wigati, Wigati
Format Journal Article
LanguageEnglish
Indonesian
Published Universitas Negeri Surabaya 19.05.2023
Subjects
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ISSN2527-6891
2527-6891
DOI10.26740/jp.v8n1.p29-36

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Summary:Artificial Intelligence – Machine Learning has great potential to help the development of education in Indonesia. So, it is important to map the research that has been done, whereas it can be a strategy to explore the use of Machine Learning for efficient the development of education. This research was conducted to determine the development of publications through article content, authorship patterns, and author productivity. The method used is descriptive bibliometric analysis, data source from the Scopus indexer, while data collection is carried out with Publish or Perish software and Vos Viewer as bibliometric analysis media. The following research findings: (i) Articles about Machine Learning in Indonesia are spread in various journals. And showing significant improvements with various new themes, the fields that most often appear are those related to computer science or Machine Learning development processes. (ii) In general, in 2009-2021 as many as 446 researchers produced 533 articles. The most research publications in 2020, namely 161 articles (30.1%). And related to the field of education there are only 14 articles (2.6%). (iii) The Keywords related to popular fields/subjects are Indonesian, development, prediction, approach, international conference. While keywords related to education produce higher education, education technology, smart educational robots and engineering education.
ISSN:2527-6891
2527-6891
DOI:10.26740/jp.v8n1.p29-36