Improving TDS Sensor Accuracy in an IoT-Based Fertigation Prototype Using Polynomial Regression Calibration and Interpolation

Harjanto, Arif
Nugroho, Happy
Ainurrosyidah, Aprilia Amrina
Burhandenny, Aji Ery

International Journal of Engineering, Science and Information Technology
Vol 6, No 1 (2026)

Accurate measurement of Total Dissolved Solids (TDS) is a critical requirement for hydroponic nutrient management, especially in automated fertigation systems that adjust nutrient concentrations based on plant age. However, non-industrial TDS sensors often exhibit significant fluctuations and non-linear errors, leading to unreliable nutrient dosing. This study proposes a calibration approach using second-order polynomial regression combined with interpolation to improve the accuracy of TDS measurements in an IoT-based fertigation prototype for lettuce hydroponics. The calibration was performed using reference TDS solutions and a digital TDS meter to ensure accurate measurements. The results show that the Mean Absolute Percentage Error (MAPE) decreased from 24.771% to 7.5768% during calibration, demonstrating a significant improvement in measurement accuracy. The calibrated sensor readings fall within the acceptable range for hydroponic nutrient control (±10%). This method provides a low-cost, reliable alternative for improving sensor accuracy in IoT fertigation systems.