International Journal of New Media Technology
Vol 9 No 1 (2022): IJNMT (International Journal of New Media Technology)

Bibliographic Computer Science Indexing Review with Disease Covid 19

Andrianingsih Andrianingsih (Universitas Nasional)
Tri Wahyu Widyaningsih (Tanri Abeng University)
Meta Amalya Dewi (Bina Nusantara University)



Article Info

Publish Date
05 Jul 2022

Abstract

Abstract - Researchers in conducting their research use the search using the homepage of the publication, according to expertise, collaboration in research, and research interests. And at this time the Covid 19 pandemic, became a trending topic for researchers, in various scientific fields. This study classifies based on publications located on the homepage source namely Scopus and Google Scholar, by analyzing the following topics, namely Natural Language Processing, Text Mining, Remote Sensing, and Sentiment Analysis using Name Entity Recognition to detect and classify named entities in text and using occurrence and link strength methods. The results showed science index literature about diseases Covid 19, obtained that Scopus has the most equitable percentage, has a good occurrence and link strength among the five scientific fields, namely Natural Language Processing 23.81%.33%, Text Mining 19.05%%, Remote Sensing 0 %, Sentiment Analysis 57.14 % then Google Scholar Natural Language Processing 51.35%, Text Mining 0 %, Remote Sensing 48.65 %, Sentiment Analysis 0 % Index Terms : Information Extraction; Bibliographic indexing; Disease Covid 19

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Journal Info

Abbrev

IJNMT

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Description

International Journal of New Media Technology (IJNMT) is a scholarly open access, peer-reviewed, and interdisciplinary journal focusing on theories, methods, and implementations of new media technology. IJNMT is published annually by Faculty of Engineering and Informatics, Universitas Multimedia ...