Assessing Bali sardine stock status using real-time electronic catch landing data recorder and time series catch database

Digitalization of capture fisheries data becomes inevitable in the present and future time. The use of Information and Communication Technology (ICT) in the fisheries sector is widely applied, creating a bigger and better database. Development of the database offers the utilization of Big Data and Decision Support System (DSS) to provide robust analysis, simulate better scenarios, formulate recommendations, and propose management measures to support successful fisheries management in achieving sustainability and profitability objectives. Bali Strait sardine stock estimation has been conducted several times through several approaches and techniques. This study will combine the available times series catch and effort data from published statistic landing data and publications with real-time data from electronic catch monitoring in Muncar and Pengambengan fishing port. The sardine stock and fishery status estimation were analyzed using a stock-production model incorporating covariates (ASPIC), a Nonequilibrium surplus-production model to data on fish catch and relative abundance. Another purpose of this study is to increase stakeholder participation through a smart dashboard system that enables automatic data analysis, faster recommendations socialization, and engagement. Increased stakeholder participation in fisheries management will be a crucial factor in achieving operational and successful fisheries management.