Analysis of fuzzy logic systems types 1 and 2 in identifying of IUU fishing and transshipment: A case study in Indonesia's vulnerable waters

The identification system for illegal, unreported, and unregulated (IUU) fishing and transshipment of incidents is one effort as early warning and it can be adopted by the Indonesian ministry of fisheries and marine affairs. The system has been developed using several methods. One of them is the artificial neural networks (ANN) have been used, but it is several weaknesses when AIS data is lost. The system able to identify in missing data in a short duration of time only. The development of a system for IUU identification proposed using a fuzzy logic system (FLS). The IUU identification system consists of subsystems: (i) missing data prediction, (ii) anomaly trajectory decision, (iii) IUU selection, and (iv) IUU decision. The performance of FLS is compared between fuzzy type 1 and type 2. The system tested using data of IUU occurrences waters in high frequency. Both SLF type 1 and type 2 are able to give result in very good accuracy for IUU fishing and transshipment identification.