The Indonesian sea, as one of the main trade traffic in the world, is very vulnerable to infringing practices, including Illegal, Unreported and Unregulated (IUU) fishing and transshipment. Therefore, strong fisheries and marine regulations are imperative, with the principle of state sovereignty, ecosystem sustainability and people's welfare. One of the strategies to improve Indonesia's maritime security is through system design that identify all forms of sea infringement practices. This study designs an IUU fishing and transshipment identification system using the fuzzy type 2 (SLF type-2) method. The dynamic data input variable is obtained from AIS data by building 3 subsystems, which are the selector subsystem, the IUU transshipment decision maker and the IUU fishing decision maker. The test is carried out in 2 ways where the generation of ship motion pattern data and validation of ship data. The results displayed that the identification system constructed able to identify IUU fishing and IUU transshipment actions successfully, with maximum accuracy of 85, 0377% and a minimum accuracy of 75.5%.