Analisis Bibliometrik untuk Memetakan Tren Penelitian Covid-19 dalam Topik Ilmu Komputer

Covid-19 berdampak pada seluruh penduduk di dunia, pandemi ini tidak hanya mempengaruhi sektor kesehatan, namun juga ekonomi, pendidikan, transportasi, industri, dan pemerintahan. Covid-19 hadir sebagai topik menarik bagi para peneliti, hal tersebut nampak pada data yang diperoleh dari Scopus, Crossref, IEEEXplore, dan Google Scholar yang di dalamnya memuat penelitian di bidang ilmu komputer yang membahas covid-19, dengan berbagai tujuan penelitian untuk memperoleh inovasi maupun solusi dari permasalahan yang timbul akibat pandemi. Penelitian ini dilakukan untuk memperoleh topik apa saja yang paling diminati oleh para peneliti terkait dengan covid 19, dan menganalisis serta membandingkan relasi antara topik Artificial Intelligence, Data Mining, Deep Learning, Machine Learning, dan Internet of Thing dari sumber google scholar, scopus, IEEEXplore, dan crossref dengan menggunakan analisis bibliometrik. Metode occurrence dan link strength digunakan untuk memvisualisasikan jejaring berdasarkan kata kunci dari ke lima topik bidang ilmu komputer serta hubungan antara lima topik tersebut dengan topik riset lainnya. Hasil analisis bibliometric menunjukkan peringkat dari ke empat penyedia sumber data artikel di lihat dari persentase setiap topik penelitian adalah sebagai berikut : Scopus, Crossref, IEEEXplore, dan Google Scholar. Analisis link strength dan occurence  terhadap kelima topik penelitian menunjukkan peringkat yang dapat dilihat dari banyaknya link strength dan occurrence di setiap penyedia sumber artikel, dengan hasil peringkat sebagai berikut : Deep Learning, Artificial Intelligence, Internet of Things, Machine Learning, dan Data Mining. Kata kunci: Bibliometrik, Covid-19, Occurrence,  Link Strength, Ilmu Kompute

The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

Comparative Analysis of Web of Science and Scopus on the Energy Efficiency and Climate Impact of Buildings

Although the body of scientific publications on energy efficiency and climate mitigation from buildings has been growing quickly in recent years, very few previous bibliometric analysis studies exist that analyze the literature in terms of specific content (trends or options for zero‐energy buildings) or coverage of different scientific databases. We evaluate the scientific literature published since January 2013 concerning alternative methods for improving the energy efficiency and mitigating climate impacts from buildings. We quantify and describe the literature through a bibliometric approach, comparing the databases Web of Science (WoS) and Scopus. A total of 19,416 (Scopus) and 17,468 (WoS) publications are analyzed, with only 11% common documents. The literature has grown steadily during this time period, with a peak in the year 2017. Most of the publications are in English, in the area of Engineering and Energy Fuels, and from institutions from China and the USA. Strong links are observed between the most published authors and institutions worldwide. An analysis of keywords reveals that most of research focuses on technologies for heating, ventilation, and air‐conditioning, phase change materials, as well as information and communication technologies. A significantly smaller segment of the literature takes a broader perspective (greenhouse gas emissions, life cycle, and sustainable development), investigating implementation issues (policies and costs) or renewable energy (solar). Knowledge gaps are detected in the areas of behavioral changes, the circular economy, and some renewable energy sources (geothermal, biomass, small wind). We conclude that i) the contents of WoS and Scopus are radically different in the studied fields; ii) research seems to focus on technological aspects; and iii) there are weak links between research on energy and on climate mitigation and sustainability, the latter themes being misrepresented in the literature. These conclusions should be validated with further analyses of the documents identified in this study. We recommend that future research focuses on filling the above identified gaps, assessing the contents of several scientific databases, and extending energy analyses to their effects in terms of mitigation potentials.This work was funded by the Ministerio de Ciencia, Innovación y Universidades de España (RTI2018‐ 093849‐B‐C31), by ICREA under the ICREA Academia programme, and by the foundation SIVL

TINJAUAN PUSTAKA SISTEMATIS PADA BASIS DATA PUSTAKA DIGITAL: TREN RISET, METODOLOGI, DAN COVERAGE FIELDS

The characterization of digital databases is needed to make it easier for academics to identify scientific literature properly and efficiently. This literature review intends to provide characterizations and descriptions related to research trends, methods and coverage fields studied in research related to the scientific database of scientific literature from around 2007 to the present (January 2019). By applying the specified inclusion and exclusion criteria, 54 relevant studies were chosen to be studied further. The systematic literature review method was applied in this study to analyze and identify previous studies related to this topic. Based on the selected primary literature there is an increasing trend of studies related to the scientific database of scientific literature. In addition, we can see that there are four of the most influential and influential publication journals related to this topic, namely the Journal of Informetrics, Journal of Cleaner Production, Asian Social Science and Journal of Academic Librarianship which are characterized by high levels of productivity issues related to the topics studied and SJR values rank is in the range Q1. Most of the studies were conducted on Scopus digital database (41%), Web of Sciences (WoS) 38% and Google Scholar (GS) 13% and the rest spread in other publication journals. The results of this study also identified that Scopus is a scientific database which has the most varied coverage fields compared to other digital database scientific literature. WoS is a digital database of scientific literature that has proven to have a paper with a higher impact factor than others. GS has the predicate digital database with the largest collection level

Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review.

In the past five years, the textile industry has undergone significant transformations in response to evolving fashion trends and increased consumer garment turnover. To address the environmental impacts of fast fashion, the industry is embracing artificial intelligence (AI) and immersive technologies, particularly leveraging conversational agents as personalised guides for sustainable fashion practices. In this research paper, we conduct a systematic literature review to categorise techniques, platforms, and applications of conversational agents in promoting sustainability within the fashion industry. Additionally, the review aims to scrutinise the solutions offered, identify gaps in the existing literature, and provide insights into the effectiveness and limitations of these conversational agents. Utilising a predefined search strategy on IEEE Xplore, Google Scholar, SCOPUS, and Web of Science, 15 relevant articles were selected through a step-by-step procedure based on the guidelines of the PRISMA framework. The findings reveal a notable global interest in AI-powered conversational agents, with Italy emerging as a significant centre for research in this domain. The studies predominantly focus on consumer perceptions and intentions regarding the adoption of AI technologies, indicating a broader curiosity about how individuals incorporate such innovations into their daily lives. Moreover, a substantial proportion of the studies employs diverse methods, reflecting a comprehensive approach to understanding the functionality and performance of conversational agents in various contexts. While acknowledging the historical precedence of text-based agents, the review highlights a research gap related to embodied agents. The conclusion emphasises the need for continued exploration, particularly in understanding the broader impact of these technologies on creating sustainable and environmentally-friendly business models in the e-retail sector