About the Journal

JOURNAL OF INDUSTRIAL COMPUTATIONAL STATISTICS

Journal of Industrial Computational Statistics (JICS) is a peer-reviewed scientific journal dedicated to advancing the development and application of statistical methodologies, computational techniques, data analytics, artificial intelligence, machine learning, optimization, and industrial data science. The journal serves as an interdisciplinary platform connecting statistical theory, computational innovation, and industrial applications to address complex real-world problems in manufacturing, engineering, healthcare, finance, environmental systems, energy, logistics, and public policy.

JICS aims to publish high-quality original research articles, review papers, case studies, methodological developments, and industrial applications that contribute to the advancement of computational statistics and data-driven decision-making.

The journal welcomes contributions from researchers, academicians, industry practitioners, government institutions, and interdisciplinary scholars who utilize statistical and computational approaches to solve industrial and societal challenges.
Journal of Industrial Computational Statistics (JICS) is published twice a year, in June and December. Each issue publishes a minimum of five (5) peer-reviewed articles that have undergone a rigorous editorial and double-blind peer-review process.
Journal title Journal of Industrial Computational Statistics
Abbrevation -
Initial JICS
Frequency 2 (two) issues per year
ISSN (Print) -
ISSN (Online) -
Digital Object Identifier (DOI) 10-32734
Editor-in-Chief -
Publisher TALENTA Publisher, Universitas Sumatera Utara
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