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Menampilkan 1–2 dari 2 artikel
Transforming the Global Aquaculture Supply Chain through the Integration of Artificial Intelligence and Big Data for Overcome Asymmetry Information
Hernalom Sitorus
; Zaenal Arifin Hasibuan
; Bobi Kurniawan
; Sri Supatmi
Big Data Analytics and Data Science
Vol 1
, No 2
(2026)
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 Scienc...
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Predicting Multi-Morbidity Progression and Identifying Key Determinants in Chronic Disease Patients Using a Longitudinal Data-Driven Information Systems Approach: A Research Protocol for a Cohort Study in Bandung Regency, Indonesia
Lusianto Lusianto
; Zaenal Arifin Hasibuan
; Sri Supatmi
; Adnan Shahid Khan
Indonesian Journal of Infomatics
Vol 1
, No 2
(2026)
Multimorbidity represents a critical challenge for primary healthcare systems in low- and middle-income countries (LMICs). In Indonesia, fragmented electronic health record (EHR) infrastructure limits effective chronic disease management. This research protocol presents an end-to-end information systems approach to: (1) design a validated ETL framework for heterogeneous health data; (2) develop and compare machine learning models (Random Forest, XGBoost, LSTM) for predicting multimorbidity risk;...
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