A Novel Fishing Finder Technique Based on VMS Data in Indonesia

Indonesian waters are very wide and have very high fisheries potential. This clearly benefits the Indonesian fishing industry. Tuna is a primary trading commodity in this industry, but catching this fish is not easy. In addition, the movement of tuna follows the pattern of changes in Earth's temperature, so determining its position clearly requires adequate equipment. The original purpose of Vessel Monitoring System (VMS) is for enforcement and control of vessel sailing. In this paper, we use VMS to find the position of tuna to reduce fishing costs for Indonesia tuna fishermen such as fuel and labor costs. This study does three things. Firstly, conduct tracking modeling of the movements of each type of fishing vessel in Indonesian waters, and use cross-reference with weather data and earth conditions, then filtering the data for fishing tuna vessel only. Secondly, develop visualization techniques resulting from algorithms by programming Python Dash. Finally, develop fish position prediction techniques using the Machine Learning ensemble by Support Vector Machine technology. It concludes that system can predict the location of tuna correctly 97.6%.