About the Journal

Journal of Computing and Data Analytics (JCDA) is a leading international, peer-reviewed, open-access journal dedicated to advancing research in computing, data science, artificial intelligence, and data analytics. Published in one volume per year comprising three issues by Vertex Academic Publishing, JCDA employs a rigorous double-blind peer-review process to ensure the highest standards of scholarly excellence, originality, and scientific integrity. The journal publishes cutting-edge methodological, theoretical, and application-oriented research in computing and data-driven technologies, covering a broad range of topics including artificial intelligence, machine learning, deep learning, big data analytics, statistical computing, computational intelligence, cloud and edge computing, computer vision, optimization, cybersecurity, the Internet of Things, software engineering, and intelligent systems. By fostering the dissemination of high-quality interdisciplinary research, JCDA serves as a global platform for researchers, academics, engineers, and practitioners, promoting innovation, collaboration, and the development of next-generation computing and data analytics technologies.

Publisher: Vertex Academic Publishing

ISSN (Online): 2979-5389

Current Issue

Vol. 1 No. 1 (2026)
View Vol. 1 No. 1 (2026)
Published: 2026-07-15

Articles

  • A comparison of predictions for cardiovascular disease using a variety of machine learning techniques

    Khamis K. Al-karawi, Abdullah K. Al-karawi (Author)
    1-13
    DOI: https://doi.org/10.68264/jcda.2026.011

  • Cloud computing and big data service: Challenges and barriers

    Abdulrahman S. Alenizi, Idress Mohammed Husien (Author)
    14-21
    DOI: https://doi.org/10.68264/jcda.2026.012

  • Adoption of Voice Biometrics in the Kuwaiti Public Sector: A Study of User Perceptions and Acceptance Factors

    Abdulrahman S. Alenizi, Abdullah K. Al-karawi (Author)
    22-29
    DOI: https://doi.org/10.68264/jcda.2026.013

  • Enhancing speaker verification performance in noisy environments via parallel model combination

    Duraid Y. Mohammed, Ahmed Aljuboori (Author)
    30-41
    DOI: https://doi.org/10.68264/jcda.2026.014

  • Central Composite Designs for Reduced Models: I_V-Optimality, Heredity Rules, and High-Dimensional Heuristics

    Okechukwu J. Obulezi, L. O. Ngonadi, Clinton Chikezie Ugorji, Ehab M. Almetwally (Author)
    42-51
    DOI: https://doi.org/10.68264/jcda.2026.015
View All Issues
Journal Cover

About the Journal

Journal of Computing and Data Analytics (JCDA) is a leading international, peer-reviewed, open-access journal dedicated to advancing research in computing, data science, artificial intelligence, and data analytics. Published in one volume per year comprising three issues by Vertex Academic Publishing, JCDA employs a rigorous double-blind peer-review process to ensure the highest standards of scholarly excellence, originality, and scientific integrity. The journal publishes cutting-edge methodological, theoretical, and application-oriented research in computing and data-driven technologies, covering a broad range of topics including artificial intelligence, machine learning, deep learning, big data analytics, statistical computing, computational intelligence, cloud and edge computing, computer vision, optimization, cybersecurity, the Internet of Things, software engineering, and intelligent systems. By fostering the dissemination of high-quality interdisciplinary research, JCDA serves as a global platform for researchers, academics, engineers, and practitioners, promoting innovation, collaboration, and the development of next-generation computing and data analytics technologies.

Publisher: Vertex Academic Publishing

ISSN (Online): 2979-5389