POTENTIAL AREA MAPPING FOR SEAWEED AQUACULTURE BASED ON INTERVAL TYPE-2 FUZZY SETS AND MULTI-LAYER PERCEPTRON ALGORITHM

This paper proposes a mapping model for seaweed aquaculture based on Interval Type-2 Fuzzy Sets (IT2FS) and Multi-Layer Perceptron (MLP) algorithm as a new framework to map potential area for seaweed cultivation to face uncertainty business environment. The main output of this research is a framework as a conceptual model for seaweed potential area mapping based on IT2FS and MLP; and visualization model from the proposed framework using google map API. We use MLP to learn historical data of variables that affect seaweed cultivation and predict future environment condition. The output of MLP used as input for IT2FS for inference process. The decision output from IT2FS is potential or not potential with specific prediction of production size for each region. We test our model for potential mapping in South Sulawesi’s seaweed aquaculture Indonesia. The test result shows our mapping model can provide potential area with total production size each area in South Sulawesi Indonesia.