Bibliometric Analysis using Vos Viewer with Publish or Perish of Intelligent Tutoring System in Private Universities

The objective of this study is to analyze the development of intelligent tutoring systems in private universities. We conducted the analysis using bibliometric methods, utilizing the Publish or Perish and VOSviewer applications. Data was obtained by using the publish or perish application with the keyword "intelligent tutoring system in private university" from the Google Scholar database from 2019 to 2024. According to search results, the number of research papers has decreased from 117 to 23 from 2020 to 2024. Mapping using VOSviewer application produces three types of visualization, namely network, overlay


INTRODUCTION
In private universities, the Intelligent Tutor System (ITS) has become an indispensable component of the learning environment.
An ITS-customized platform enhances students' education more efficiently.By utilizing data analysis and artificial intelligence technology, Intelligent Tutor System (ITS) is able to tailor educational materials to the individual requirements and abilities of each student.For example, Intelligent Tutor System (ITS) can provide additional practice for students who struggle to comprehend specific material or further difficulty for students who have already achieved a high level of proficiency.The implementation of Intelligent Tutor System (ITS) in private universities has resulted in significant improvements in students' academic achievement and retention rates.
Intelligent Tutoring Systems (ITS) have attracted great attention in private universities environments due to their ability to provide individualized instruction and improve learning outcomes (Ma et al., 2014).Research has shown that Intelligent Tutor System (ITS) can be as effective as human tutoring and other tutoring systems, and in some cases, even more effective in raising test scores and improving student performance (Kulik & Fletcher, 2016).Additionally, Intelligent Tutor System (ITS) has been recognized for its ability to provide personalized instruction tailored to each student, thereby revolutionizing online education (Mitrovic et al., 2007).The integration of Intelligent Tutor System (ITS) in university collaboration information systems has been proven feasible and effective (Laaziri et al., 2018).
Additionally, Intelligent Tutor System (ITS) has been shown to be effective in improving students' reading comprehension and providing consistent and measurable instruction (Xu et al., 2019).
The explanation above leaves room for further research on intelligent tutoring systems in private universities.Several previous studies have focused on intelligent tutoring systems in private universities, but none have analyzed research trends using a bibliometric analysis approach and mapping visualization.Presently, bibliometric analysis is often used to ascertain research trends (Nandiyanto et al., 2023;Niknejad et al., 2021;Kim et al., 2021;Ragadhita & Nandiyanto, 2022;Suprapto et al., 2021).Table 1 displays a collection of prior studies that used bibliometric analytic techniques to examine the progression or pattern of a study subject in more depth.This study aims to investigate the development of intelligent tutoring systems in private universities using bibliometric analysis methods supported by mapping analysis.To analyze this research, we used the Publish or Perish and VOSviewer applications.In addition, this study examines the advancements in research and the growth in citations in the field of intelligent tutoring systems in private universities.
We utilize mapping visualizations produced by the VOSviewer application to identify keywords that frequently appear in research on intelligent tutoring systems in private universities.Data was obtained using the publish or perish application using the keyword "intelligent tutoring system in private universities" from the Google Scholar database from 2019 to 2024.

METHOD
This research includes bibliometric analysis.The process consists of many steps, starting with collecting article data related to the topic "Intelligent Tutoring System in Private Universities".The data searched covered the time period from 2019 to 2024 and were collected from Google Scholar using Publish or Perish software, resulting in a total of 499 papers for analysis.Data is saved in CSV and RIS format for analysis using Microsoft Excel and VOSviewer applications.After collecting the data, the articles were screened to verify that the data were comprehensive, including examining components such as year of publication.We subsequently visualized the article data using VOSviewer and analyzed it in Microsoft Excel.Further elaboration on the procedural aspects of the analysis can be found in our previous research (Al Husaeni & Nandiyanto, 2022).

Intelligent Tutoring System Development in Private University Publications from 2019 to 2024
Table 2 shows the results of research published between 2019 and 2024 on the topic "Intelligent Tutoring System in Private Universities" Both national and international journals have published these articles.According to statistical data, the cumulative count of research unearthed over the last five years amounts to 499 documents.The quantity of research on "Intelligent Tutoring System in Private Universities" fluctuates annually.The quantity of research articles on "Intelligent Tutoring System in Private Universities" is as stated: In 2019, there were 72 papers, accounting for 14.43% of the total.In 2020, there were 117 documents, representing 23.45% of the total.In 2021, there were 113 documents, making up 22.65% of the total.In 2022, there were 96 documents, accounting for 19.24% of the total.In 2023, there were 78 documents, representing 15.63% of the total.Finally, in 2024, there will be 24 documents, making up 4.61% of the total.
According to the annual research document count, there has been a decrease in publications focused on "Intelligent Tutoring Systems in Private Universities" from 2020 to 2024.Fig 1 presents a graph that clearly shows the decrease in the number of articles on "Intelligent Tutoring Systems in Private Universities".Between 2019 and 2024, 2020 had the most research studies conducted on this subject, with a total of 117 documents.On the other hand, the year with the fewest number of studies was 2024, with just 23 documents.There is a regular annual drop in the quantity of papers, while there was a specific rise of around 45 documents from 2019 to 2020.
Intelligent tutoring systems (ITS) are essential in higher education since they enhance the quality of teaching and improve student learning experiences.
This system provides a personalized and adaptive learning approach that caters to the unique needs and understanding of each student.By utilizing advanced technology such as artificial intelligence and data analysis, intelligent tutoring systems (ITS) can provide direct and measurable feedback to students and data analysis, helping them understand the material more efficiently.In addition, Intelligent Tutoring System (ITS) allows educational institutions to enhance their use of human resources by offering organized and effective learning methods.Furthermore, Intelligent Tutor System (ITS) helps to improve student retention rates by providing individualized and targeted educational services.Therefore, Intelligent Tutoring System (ITS) play a crucial role in enhancing the educational standards of private universities and facilitating the attainment of superior educational objectives for both students and educational institutions.Hence, the objective of this study is to provide a literature evaluation pertaining to intelligent tutoring systems in private universities.This study comprises 15 publications focused on intelligent tutoring systems in private universities with the most significant amount of citations.Table 3 displays the information of the articles that have received the most citations.Table 3 reveals that the work titled "Systematic review of research on artificial intelligence applications in higher education-where are the educators?"was authored by Zawacki-Richter et al.The most frequently referenced article in 2019 was a literature review on the use of artificial intelligence applications in higher education.It received a total of 1763 citations, with an average of 352.6 citations each year.The study by Deng et al. (2020) is one of the most frequently cited articles.In their study, Deng et al. (2020) explore the concept of Edge intelligence, which aims to address critical issues in edge computing by using widely-used and efficient AI technologies.The paper authored by Deng et al. (2020) has received a total of 782 citations since 2020, with an annual average of 195.5 citations.Table 3   As an illustration, the phrase "intelligent tutoring system" is the most frequently used term in 2021, as indicated by the green overlay visualization.On the other hand, the purple color indicates a higher usage of the term "university" in 2020.
Additionally, the yellow color indicates the widespread use of the phrase "artificial intelligence" in 2021.Figure 4 shows density visualization, in contrast to network and overlay views, uses color to represent the frequency of phrases.The brightness of a term's color corresponds to its frequency of use.

CONCLUSION
The objective of this study is to examine the progress of intelligent tutoring systems at private universities.Analysis was carried out using bibliometric methods using the Publish Or Perish and VOSviewer applications.There have been a total of 499 publications on the topic of "Intelligent tutoring systems in private universities" from 2019 to 2024.The study on "Intelligent tutoring systems in private universities" has seen a decline from 2020.In 2020, there were a record-breaking 117 articles published.The number steadily declines until 2024, with corresponding figures of 113 articles (23,45%) in 2020, 113 articles (22,65%) in 2021, 96 articles (19,24%) in 2022, 78 articles (15,63%) in 2023, and 23 articles (4,61%) in 2024.According to the bibliometric and VOSviewer analyses, it is evident that the advancement of intelligent tutoring system technology at private universities is decreasing from 2020 to 2024.However, there is still a high probability of developing mapping and visual representations of relevant topics using VOS Viewer in clusters 4, 5, and 6.This development aims to enhance the Learning Management System (LMS) by incorporating an intelligent learning system to assess individual students' abilities, a feature currently lacking.