Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022
Dublin Core
Title
Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022
Subject
bibliometric; dimensions; journal; RESTI; research trends
Description
This study provides a comprehensive analysis of the RESTI Journal, a prominent publication in the field of systems engineering
and information technology. The analysis aims to evaluate the journal's publication output, citation impact, and overall
contribution to the field. The study uses data from the Dimensions database, focusing on articles published between 2018 and
2022, resulting in a data set of 594 articles. To analyze the data collected, the study employs bibliometric and network
visualization tools such as Bibliometrix and VOSviewer. The analysis reveals a notable increase in the number of publications
over time, indicating a growing interest and research activity in the field. Furthermore, the distribution of author productivity
deviates from Lotka's law, highlighting variations in author patterns and productivity levels. An examination of institutional
affiliations reveals Telkom University as the dominant institution, making a substantial contribution to the journal.
Visualizations based on author-provided titles, abstracts, and keywords highlight research trends in image recognition and
classification, with a particular emphasis on utilizing convolutional neural networks (CNN) and Support Vector Machines
(SVM). Overall, this study provides valuable information on the performance and trends of the RESTI Journal. The findings
contribute to a deeper understanding of the impact and its role in advancing knowledge in systems engineering and information
technology. These insights can inform researchers, practitioners, and stakeholders in the field, guide future research directions
and improve the scholarly impact of the RESTI Journal.
and information technology. The analysis aims to evaluate the journal's publication output, citation impact, and overall
contribution to the field. The study uses data from the Dimensions database, focusing on articles published between 2018 and
2022, resulting in a data set of 594 articles. To analyze the data collected, the study employs bibliometric and network
visualization tools such as Bibliometrix and VOSviewer. The analysis reveals a notable increase in the number of publications
over time, indicating a growing interest and research activity in the field. Furthermore, the distribution of author productivity
deviates from Lotka's law, highlighting variations in author patterns and productivity levels. An examination of institutional
affiliations reveals Telkom University as the dominant institution, making a substantial contribution to the journal.
Visualizations based on author-provided titles, abstracts, and keywords highlight research trends in image recognition and
classification, with a particular emphasis on utilizing convolutional neural networks (CNN) and Support Vector Machines
(SVM). Overall, this study provides valuable information on the performance and trends of the RESTI Journal. The findings
contribute to a deeper understanding of the impact and its role in advancing knowledge in systems engineering and information
technology. These insights can inform researchers, practitioners, and stakeholders in the field, guide future research directions
and improve the scholarly impact of the RESTI Journal.
Creator
Ronal Watrianthos, Yuhefizar
Source
http://jurnal.iaii.or.id
Publisher
Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association
Date
August 2023
Contributor
Sri Wahyuni
Rights
ISSN Media Electronic: 2580-0760
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Ronal Watrianthos, Yuhefizar, “Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022,” Repository Horizon University Indonesia, accessed January 11, 2026, https://repository.horizon.ac.id/items/show/10010.