Issue |
E3S Web Conf.
Volume 450, 2023
International Conference on SDGs and Bibliometric Studies (ICoSBi 2023)
|
|
---|---|---|
Article Number | 01006 | |
Number of page(s) | 10 | |
Section | Earth and Environmental Sciences | |
DOI | https://doi.org/10.1051/e3sconf/202345001006 | |
Published online | 29 November 2023 |
Trends in research publication topics related to eco enzymes with bibliometric analysis
1,4,5 State University of Surabaya, Surabaya, Indonesia
2 EDP Mathematical Sciences, University of Michigan, Michigan, United States
3 Pembangunan Nasional Veteran University, Yogyakarta, Indonesia
* Corresponding author: winarsih@unesa.ac.id
Ecoenzyme is a potential sustainable waste management solution that could make waste management more beneficial. This study seeks to analyze the evolution of ecoenzyme-related research publication topic trends over the past decade, then visualize them and identify potential ecoenzyme-related research topics for future study. Using Publish or Perish software with Google Scholar database sources and VOSviewer software, this research method employs a literature review and bibliometric analysis. The investigation and search produced a collection of published document metadata regarding ecoenzymes that included up to 666 documents from 2013 to 2023. During that time, ecoenzyme-related research publications covered a variety of topics, including composition, training, and product development. N. Ginting and T. Wikaningrum are the authors who have contributed the most to the publication of the ecoenzyme topic, with a total of 12 publication documents. Further research can be conducted on the development of ecoenzymes, such as the investigation of the efficacy and effectiveness of using ecoenzymes and the investigation of other ecoenzyme research involving various other scientific disciplines. This study has limitations due to its reliance on data obtained through Google Scholar and its lack of a rigorous screening process. Therefore, it is recommended that future research take additional measures to filter more collected data.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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