Smart Aquaculture under Digital Transformation: AHP Approach for Optimizing Vannamei Shrimp Farming in Central Java

Abstract

The transformation of aquaculture through digital technologies has become increasingly essential to enhance sustainability, efficiency, and competitiveness in shrimp farming. Despite its importance, the challenge of determining which regions should be prioritized for digital adoption remains unresolved, particularly in contexts with diverse production and economic conditions. This study introduces the Analytical Hierarchy Process (AHP) as a multi-criteria decision-making tool to evaluate and prioritize coastal districts in Central Java, Indonesia, for smart aquaculture development in Litopenaeus vannamei farming. AHP integrates indicators of production potential, economic feasibility, and price competitiveness into a unified ranking framework, producing clear differentiation across districts. The results highlight Cilacap, Kendal, Brebes, Purworejo, and Rembang as priority areas for early adoption of digital innovations such as IoT-based monitoring, AI-driven disease prediction, and traceability platforms. This research contributes to the operationalization of the AHP algorithm for aquaculture decision-making, contextualization of the global digital transformation framework in the Indonesian shrimp sector, and demonstrates the robustness of multi-criteria prioritization for policy planning. Although the precision of the results may be limited by the scope of the available data, the study confirms the significant role of AHP in guiding evidence-based, scalable, and adaptive strategies for advancing smart aquaculture.