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Hernawan
Postgraduate Program, Universitas Negeri Jakarta, Jakarta, Indonesia

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Trends in scientific publication of traditional game learning models in physical education and sports in Indonesia: A bibliometric analysis Joni Alpen; Firmansyah Dlis; Hernawan; Widiastuti; Leni Apriani; Edi Kurniawan; Davi Sofyan
Journal Sport Area Vol 7 No 2 (2022): August
Publisher : UIR Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/sportarea.2022.vol7(2).9072

Abstract

The development of scientific publications in the field of traditional game learning models requires more research in order to compete with other fields. The goal of this research is to look at the production of scientific publications based on the traditional game learning model. The Scopus database and various bibliometric indicators such as global publication trends, most active authors, number of citations, and author keywords are used to collect publications. From 1996 to 2022, a total of 473 publications on traditional game learning models are discovered. Data in Comma-separated Values (CSV) and Research Information Systems (RIS) formats are exported to Microsoft Excel, Publish or Perish (PoP), and VOSviewer software for this review. According to the research findings, 2021 has been the year with the most publications, with 139 documents. Universitas Pendidikan Indonesia is listed as the most active affiliate, with up to 80 academic scientific works published. Suherman, A., from Universitas Pendidikan Indonesia, is the most active writer, with 13 publications to his credit. With 60 documents, the Journal of Physics Conference Series is the most actively published scientific resource. Some of the research limitations in our paper include the selection of keywords that do not represent the entire search data, data filters, and data providers. It should be noted that a variety of other databases can be used to obtain data. This bibliometric study sheds light on future research directions in the field of traditional game learning models.