Website Design for Locating Tuna Fishing Spot Using Naïve Bayes and SVM Based on VMS Data on Indonesian Sea

Abstract

Indonesia as a state maritime country has the largest ocean in the world and locates between two continents and two oceans (Figure 1). As a state maritime, Indonesia has a source power of nature which is very large both on land and at sea. Utilization of source power in waters particularly about catching fish in an area must comply with the provisions and regulations that apply, as well as follow procedures like fisheries are responsible, for it required a system that is effective and accurate. System monitoring and surveillance vessel fisheries are generally used in several countries around the world are using the instrument Vessel Monitoring System (VMS). The aim of this paper is to make a based web system that aims to determine the location of catching tuna. System has to be accurate and fast that beneficial for the fishermen who are looking for tuna in the waters of Indonesia. Two methods of machine learning are used in this research. There are Naives Bayes and Support Vector Machine. The results of this paper is a website that serves to determine the location of fishing tuna using the method of Naives Bayes and SVM -Based on Data VMS in the waters of Indonesia. The result shows that the accuracy of SVM is 97. 6 better than that of Naïve Bayes (94.2) in determining the tuna but some area Naïve Bayes is better.