Computational Bibliometric Analysis on Publication of Techno- Economic Education

© 2021 Kantor Jurnal dan Publikasi UPI Article History: Received 08 Dec 2021 Revised 10 Jan 2022 Accepted 12 Jan 2022 Available online 14 Jan 2022 ____________________ Keyword: Bibliometric, Education, Evaluation, Techno-Economic, VOSviewer. Indonesian Journal of Multidisciplinary Research Journal homepage: http://ejournal.upi.edu/index.php/ IJOMR/ Indonesian Journal of Multidisciplinary Research 2(1) (2022) 213-222 Ragadhita and Nandiyanto., Computational Bibliometric Analysis on Publication ... | 214 DOI: http://dx.doi.org/10.17509/xxxx.xxx pISSN 2776-608X eISSN 2776-5970


INTRODUCTION
The development of the chemical industry is increasingly complex. And, these developments need to be compared with the state of the natural resources, environmental, and safety aspects of the chemical industry, as well as consumer needs (Surya, et al., 2021;Mahmud, et al., 2021). Given the limitations of these aspects, an economic evaluation is needed in designing the required industry or market (de Oliveira, et al., 2018). Of course, in techno-economic analysis requires good basic skills to be able to win the competition in the industrial world (Buchner, et al., 2018;Corderi, et al., 2021). Furthermore, this study discovered that examining economic potentials and profitability could provide important information for decision-making about the possibility of scaling up chemical processes and bioprocesses, based on published investigations. Economic performance is one of the most important factors to consider when designing chemical processes (Meramo-Hurtado, et al., 2020;Carvajal, et al., 2016;Panjapakkul & El-Halwagi, 2018).
In our previous study related to the analysis of techno-economic education in the field of chemistry have been carried out including on waste materials Nandiyanto, 2018), organic materials (Elia, et al., 2021), inorganic materials (Nandiyanto, 2021;Zen, et al., 2021;Ragadhita, et al., 2019;Prabowo, et al., 2018;Shalahuddin, et al., 2019), and brakepad materials . Based on this research, there have been many studies discussing techno-economic education. However, there are no studies that discuss bibliometric analysis and mapping processes using VOSviewer. Therefore, this analysis is important to determine the quantity and up-to-date of a term.
Based on our earlier bibliometric research Al Husaeni & Nandiyanto, 2022), the goal of this work is to combine mapping analysis with VOSviewer software to undertake bibliometric engineering research in techno-economic education. This study is meant to assist and serve as a reference for researchers in performing and deciding on research topics, particularly in the field of chemistry. Bibliometric analysis is thought to be useful at producing datasets that may be utilized to improve research quality . A distribution of the type of publication, the topic area investigated, the researcher's country of origin, the journal where the article was published, and the language used is displayed on the bibliometric map (Hamidah, et al., 2020). However, the bibliometric employed in this study is a distribution that includes the type of publication and the research topic area is published.

METHODS
In performing bibliometric data analysis on a particular publication data, we prepare several applications. First, a reference manager application such as Publish or Perish to prepare database sources. This reference manager application is used to collect research data that has been published related to techno-economic topics. Research data from published articles collected and filtered from 2017-2022 where each article has been indexed by Google Schoolar. The keywords used to compile articles were "education", "techno-economic", and "economic evaluation" to gained 288 articles related this topic. The Second, we need an application for data mapping analysis such as VOSviewer. The VOSviewer application is used because it is an open-source application. Then, using the VOSviewer tool, we created bibliometric maps to visualize and analyze trends. We created data mapping articles from prepared database sources. There are three forms of data mapping: network, density, and overlay visualization. The keyword frequency is set as desired when creating a bibliometric map, and irrelevant or less relevant terms are removed. Our earlier investigations Al Husaeni & Nandiyanto, 2022;Al Husaeni & Nandiyanto, 2023) provide detailed information about VOSviewer and library quest. Figure 1 shows the development of research related to techno-economic studies over a period of 6 years (from 2017 to 2022). Based on Figure 1, the total publications of studies related to techno-economy are unstable each year. The significant increases in total publications on this topic occurred in 2021. The total number of publications in 2017 was 44 articles. Then, there were an addition of 8 articles in 2018 thus the number of articles was 52 articles. In 2019 and 2020, the trend of the total number of publications of this this topic per year is not much different from the trend of 2017 and 2018. In 2019, there was a decrease in the number of articles compared to 2018. The number of articles in 2019 was 46 articles. Then there was an insignificant increase in 2020 where the number of articles became 55 articles. Furthermore, in 2021 a significant increase in the total number of publications per year reach 80 articles. However, in 2022, the articles available are very much different from the previous year, which was only 11 articles. The decrease in the number of publications in 2022 was due to data collection occurring at the beginning of the year, thus there were still few articles available. Based on Figure 1, the increase in 2021 was due to the impact of the COVID-19 pandemic. As we know that techno-economics is related to computational experiments, thus during the COVID-19 pandemic, researchers turned to computational-based research due to the COVID-19 epidemic has limited the number of experiments that may be conducted (physical distancing) (Afifah, 2021).

Research Developments in The Field of Techno-Economic Education
Based on a total of 288 articles on techno-economics, there are 20 articles with the highest number of citations based on search results through the Google Scholar database. Table 1 shows the order details of the articles with the most citations.   Based on the Table 1, the three articles with the highest number of citations were successively published in the journals Applied Energy, Energy, and the Journal of Cleaner Production.

VOSviewer Visualization on Techno-Economic Education Topic
The minimum number of relationships between terms in the VOSviewer is restricted by two terms, according to Al Husaeni and Nandiyanto, 2022. Based on the mapping analysis, studies related to technical-economic education are divided into 13 clusters as follows: (i) Cluster 1 contains 10 items including capital cost, cost, economic benefit, economic indicator, economic model, sensitivity, strategy, techno economic model, techno economic performance, and techno economic viability. (ii) Cluster 2 contains 9 items consisting of assessment, economic assessment, economic characteristic, economic optimization, economic viability, life cycle analysis, techno economic assessment framework, techno economic case study, and technology. (iii) Cluster 3 contains 9 items comprising cost estimation, economic analysis, economic information, energy consumption, estimation, framework, rural area, techno economic framework, and techno economic potential. (iv) Cluster 4 contains 7 items belonging capital, conceptual design, internal rate return, life cycle assessment, net present value, production, and sensitivity analysis. (v) Cluster 5 has 7 items including application, economic perspective, education, evaluation, feasibility, techno economic approach, techno economic feasibility evaluation. (vi) Cluster 6 has 6 items, which consist of Indonesia, techno economic aspect, techno economic feasibility, techno economic optimization, techno economic study, and techno economic analysis. (vii) Cluster 7 has 5 items, namely current study, economic feasibility, economic potential, education building case study, and techno economic assessment (viii) Cluster 8 has 5 items, the 5 items are economic analysis model, economic factor, technical analysis, techno economic analysis, and techno economic feasibility. (ix) Cluster 9 has 4 items, namely environmental impact assessment, investigation, techno, and techno economic evaluation. (x) Cluster 10 has 4 items consisting economic simulation, energy, techno economic comparison, and techno economic modelling. (xi) Cluster 11 has 4 items, which consist of case study, economic impact, environmental aspect, and renewable energy source. (xii) Cluster 12 has 3 items, the 3 items are comprehensive techno economic evaluation, economic, and educational institute. (xiii) Cluster 13 contains 3 items including economic evaluation, techno economic modelling, and techno economic perspective. Cluster 1 is red, cluster 2 is marked in green, cluster 3 is marked in dark blue, cluster 4 is yellow, cluster 5 is marked in purple, cluster 6 is light blue, cluster 7 is marked in orange, cluster 8 is marked with brown, cluster 9 is dark yellow, cluster 10 is light red, cluster 11 is marked with light green, cluster 12 is marked in slight blue, and cluster 13 is light purple.

Network Visualization on Techno-Economic Education Topic
The network between the depicted terms displayed via the visualization network. The link between terms is depicted in Figure 2. Relationships in network visualization are depicted by lines connecting one term to another. Figure 2 shows the clusters in each of the researched topic areas. Based on Figure 2, techno-economy eduaction has connections with 13 clusters. Table 2 summarizes the total strength and occurrence based on techno-economic terms in each cluster.   Figure 3 shows the density visualization of research developments on techno-economic topics. Density visualization shows item dots that have a colour that depends on the density of an item (Mulyawati & Ramadhan, 2021). In short, the colour of the dots in the mapping depends on the number of items associated with other items that indicate the most used keywords in the publication. Based on the visualization image (see Figure 3), the yellower the colour on the density map, it indicates the closer the relationship. However, the greener the colour is on the density map, it shows a sparse relationship.