Maulana, Fairuz Iqbal, Febriantono, M. Aldiki, Hamim, Miftahul, Fajri, Bayu Ramadhani and Arifuddin, Rahman (2022) Scientometric analysis in the field of big data and artificial intelligence in industry. In: 2022 1st International Conference on Information System & Information Technology (ICISIT), Universitas Airlangga.
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Abstract
Big Data and Artificial Intelligence (BD&AI) in
Industry have grown so prevalent, and the potential they
provide is so revolutionary that they are seen as critical for
competitive growth. Because the number of organizations
BD&AI on Industry technology is increasing exponentially, so
is the need for BD&AI on Industry practitioners. Until we
conducted this research, only 1399 academic documents on
BD&AI in Industry found from 2002 to 2020 were obtained by
searching the Scopus database. BD&AI in the industrial sector is examined in-depth in this paper. This study uses bibliometric analysis and indexed digital methods to map scientific publications worldwide. This study uses the Scopus database to collect information and online analysis via the Scopus website and VOSViewer to demonstrate bibliometric network mapping. We use the article selection process, starting with the keywords to be searched for, the year limitation, then the database is exported into RIS and CSV format files. From the database, we also perform network mapping using VOSViewer. Researchers in China have the most articles published and indexed by Scopus among the most prolific authors (373), followed by the United States (239) and India with 125 academic publications. Data analysis reveals an upward trend in the number of worldwide publications in BD&AI in Industry, as measured by the Scopus index.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Nama : Rahman Arifuddin NIDN : |
| Uncontrolled Keywords: | big data, artificial intelligence, industry, bibliometric, VOSViewer |
| Divisions: | Fakultas Teknik > S1 Teknik Elektro |
| Depositing User: | Surya Dannie |
| Date Deposited: | 29 Dec 2023 06:07 |
| Last Modified: | 29 Dec 2023 06:07 |
| URI: | https://eprints.unmer.ac.id/id/eprint/3906 |
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