Implementation of Extreme Learning Machine for Water Quality Control in Vannamei Shrimp Ponds

Abstract

The application of science and technology knowledge is crucial in supporting the Indonesian Government's program to increase the production of Litopenaesus Vannamei shrimp. This research collaborates with shrimp pond farmers to develop technology that supports the cultivation of vaname shrimp. The water quality affect the harvest results, and the water parameters such as pH, dissolved oxygen (DO), alkalinity, salinity, and temperature should be monitored and adjusted if the parameters exceed the predetermined limits. We have developed an Extreme Learning Machine-based water quality management system tailored to the geographic conditions of Indonesia. This tool uses sensors to read data from the pond water, which is then processed by a microcontroller and displayed in a web-based information system. This tool helps farmers determine the water conditions and condition it accordingly. Based on experimental result error dari data training adalah 0.0001 dan error pada data testing yaitu sebesar 0.1851, it can be seen the Extreme Learning Machine has good performance for this research.