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Recently, the mud-crab farming can help the rural population economically. However, the existing parasite in the mud-crabs could interfere the long live of the mud-crabs. Unfortunately, the parasite has been identified to live in hundreds of mud-crabs, particularly it happened in Terengganu Coastal Water, Malaysia. This study investigates the initial identification of the parasite features based on their classes by using machine learning techniques. In this case, we employed five classifiers i.e logistic regression (LR), k-nearest neighbors (kNN), Gaussian Naive Bayes (GNB), support vector machine (SVM), and linear discriminant analysis (LDA). We compared these five classfiers to best performance of classification of the parasites. The classification process involving three stages. First, classify the parasites into two classes (normal and abnormal) regardless of their ventral types. Second, classified sexuality (female or male) and maturity (mature or immature). Finally, we compared the five classifiers to identify the species of the parasite. The experimental results showed that GNB and LDA are the most effective classifiers for carrying out the initial classification of the rhizocephalan parasite within the mud crab genus Scylla.

In this paper, a system dynamics approach is used instead of the traditional approaches to stimulate, forecast and analyze the economic effects of an existing policy practice in Setiu Wetland. As a part of Setiu district that uphold tradition in fishery and maritime based industry, Setiu Wetland area seems to be left behind in terms of economic and livelihood. Generally, Setiu development policy consists of five subsystem including population growth, economic, residential, transportation and suburban sprawl. Due to their widespread population distribution, Setiu Wetland receives low urban-related progress. Hence, a forecast of 30 years from 2016 to 2046 providing a necessary insight for potential development of the Setiu Wetland region, to simulate its environment, identify gaps, propose suitable land model towards Setiu Minapolitan area (Peri-urban area) and suggest directions for future studies particularly in economic and livelihood for local authorities to develop with.

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