Monte Carlo Algorithm Applications in Shrimp Farming: Monitoring Systems and Feed Optimization - Kurniawan, Vincentius; Herkristito, Atanasius Raditya; Prasetiyowati, Maria Irmina (Universitas Multimedia Nusantara, 2025)
Indonesia is one of the world’s leading maritime nations, ranking second in fishery export value in 2020 [1]. Shrimp stands out as the most lucrative commodity, with an export value of USD 1,997.49 million [2]. Feeding shrimp plays a vital role in their growth and cultivation; however, overfeeding can result in feed residue that negatively impacts the quality of pond water and represents the biggest operational after capital expenditure [3]. The profitability of shrimp farming heavily depends on the feeding cost. This study using the Monte Carlo algorithm to track feed in shrimp and provides an optimal feeding plan. The algorithm can be used to provide feed recommendations for shrimp start from 33 days of cultivation (DoC), with an best range around 85kg to 92kg. The findings show the potential of the Monte Carlo algorithm in enhancing feeding plan in shrimp farming industries. Index Terms— Cultivation; Feeding; Feed Recommendations; Margin; Monte Carlo; Operational Cost; Pond Water; Shrimp Farming