@article {10.3844/jcssp.2025.347.362,
article_type = {journal},
title = {Big Data Analytics (BDA) in the Research Landscape: Using Python and VOSviewer for Advanced Bibliometric Analysis},
author = {Arifin, Samsul and Faisal, Muhammad and Manurung, Monica Mayeni and Siregar, Bakti and Rahadi, Andi Pujo and Eli, Abdullah and Ramadhan, Gilang and Fikriansyah, Ilham},
volume = {21},
number = {2},
year = {2025},
month = {Jan},
pages = {347-362},
doi = {10.3844/jcssp.2025.347.362},
url = {https://thescipub.com/abstract/jcssp.2025.347.362},
abstract = {Big data analytics has become a key element in research and development in various fields. With the ability to analyze large and complex amounts of data, this technology allows researchers to identify patterns, trends, and insights that were not seen before. This article explores how big data analytics is applied in various disciplines, including computer science, engineering, and mathematics. We use Python for data processing and analysis, as well as VOSviewer for in-depth bibliometric visualization. The study highlights recent developments in big data analysis methodologies, the challenges they face, and the potential for the future. Our findings suggest that the integration of advanced analytical techniques can accelerate scientific discovery and improve understanding across different research domains.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}