Big Data Analytics and Data Science
Vol. 1 No. 2 (2026): June: Big Data Analytics and Data Science

Transforming the Global Aquaculture Supply Chain through the Integration of Artificial Intelligence and Big Data for Overcome Asymmetry Information

Hernalom Sitorus (Universitas Komputer Indonesia)
Zaenal Arifin Hasibuan (Universitas Komputer Indonesia)
Bobi Kurniawan (Universitas Komputer Indonesia)
Sri Supatmi (Universitas Komputer Indonesia)



Article Info

Publish Date
17 Jun 2026

Abstract

The global aquaculture sector faces structural challenges in the form of information asymmetry that causes a misalignment between production and market demand. The still-dominant production-driven paradigm leads to supply chain inefficiencies, low transparency, and limited traceability. This research aims to develop an information system integration model based on Artificial Intelligence (AI) and Big Data to transform the supply chain into a market-driven one. The research uses the Design Science Research (DSR) method, which includes needs analysis, data integration architecture design, development of Machine Learning and Deep Learning-based predictive models, and evaluation through prototype implementation. Expected outcomes include a data integration architecture, a supply-demand prediction model, and an AI-based traceability framework. This research contributes to improving the efficiency, transparency, and global competitiveness of the aquaculture sector.

Copyrights © 2026






Journal Info

Abbrev

BDAS

Publisher

Subject

Description

Aims This journal aims to publish cutting-edge research in big data analytics and data science, emphasizing data-driven methods and intelligent analytics for decision support and innovation. Scope Big data architectures and platforms Data mining and predictive analytics Machine learning for data ...