A Study on Reducing Measurement Fluctuations in Iron-Electrode Salinity Sensor Using Moving Average and Kalman Filters

Indonesia is recognized as one of the leading shrimp-producing countries globally, with most farms operating on a small scale using traditional methods. This creates a strong demand for low-cost technologies to support aquaculture. One critical component in shrimp farming is water quality monitoring, where salinity is a key parameter affecting shrimp health and growth. Affordable salinity sensors using iron electrodes are increasingly considered. However, they often produce unstable and fluctuating readings, compromising monitoring reliability. This study addresses the issue by applying digital filters to enhance the stability of salinity sensor data. Two filtering methods, Moving Average and Kalman filters were evaluated using salinity ADC data from previous research. The analysis focused on comparing their effectiveness in stabilizing measurements. Results show that the Moving Average filter outperformed the Kalman filter, providing lower standard deviation values (87,09, 65,69, 63,67) and variance values (7,5807E+03, 4,3150E+03, 4,0542E+03), confirming its suitability for improving low-cost salinity sensor performance.