Purse Seine Fleet Optimization with E-Logbook Data in Gorontalo Fisheries: Optimasi Armada Purse Seine Berbasis Data E-Logbook di Perikanan Gorontalo - Rahmawati, Mega Deza Tahta; Salam, Aziz; Baruadi, Alfi Sahri Remi (Universitas Muhammadiyah Sidoarjo, 2026)
General Background Fisheries operations in Indonesia rely heavily on purse seine fleets whose performance determines regional marine resource utilization and post-harvest productivity. Specific Background At the Fish Landing Base (PPI Tenda) in Gorontalo City, mandatory e-logbook reporting provides real-time operational data enabling quantitative assessment of fleet productivity, seasonal variability, and technical capacity. Knowledge Gap However, this dataset has not been systematically applied to identify target production capacity (Ymax) or determine the optimal number of operational fleets to match infrastructural and biological limits. Aims This study evaluates e-logbook data from January–August 2025 to analyze productivity, estimate Ymax through linear regression, and apply Goal Programming to determine an optimal fleet configuration based on CPUE, gross tonnage productivity, and trip frequency tolerance. Results Findings show fluctuating productivity driven by fishing season dynamics, with efficiency reflected in CPUE ranging 0.587–0.860 and GT productivity increasing during peak months. Regression produced a performance model Y = −141.438 + 2.198X (p < 0.05) and estimated Ymax at 120–130 tons per hour with operative capacity of 110–120 tons per hour. Goal Programming modeling using 54 fleets indicates an optimal operational structure of 48 fleets to maintain production within target potential while reducing deviation from effort limits. Novelty This work provides the first integrated regression-based Ymax estimation combined with Goal Programming for purse seine fleet configuration decisions using verified e-logbook records from PPI Tenda. Implications Results offer evidence-based input for sustainable fisheries management, operational scheduling, and policy formulation to balance economic productivity with technical efficiency and resource sustainability in Gorontalo’s coastal fisheries system. Highlights Data-driven regression modeling identifies Ymax at 120–130 tons per hour. Goal Programming recommends 48 fleets as an optimal operational configuration. Seasonal shifts produce measurable fluctuations in CPUE and GT productivity. KeywordsE-Logbook; Purse Seine Fleet; CPUE Productivity; Goal Programming Optimization; Gorontalo Fisheries