Prototype of TDS, EC, Temperature Monitoring System with NodeMCU ESP8266 in Water Quality Prediction Against Variations in Catfish Density BUDIKDAMBER - Riswanto Riswanto; Putut Marwoto; Sunyoto Eko Nugroho (Prodi Pendidikan Fisika Universitas Sarjanawiyata Tamansiswa, 2026)
This study aims to develop and validate an Arduino-based system for monitoring water quality using NodeMCU ESP8266 to measure Total Dissolved Solids (TDS), Electrical Conductivity (EC), and water temperature in fish farming in buckets (Budikdamber). Budikdamber monitoring has never been done in real-time with TDS–EC–temperature at the same time, as well as analyzing the influence of fish density variations on water quality dynamics. ADDIE's development model is used through the stages of analysis, design, development, implementation, and evaluation. The prototype was validated and calibrated with standard instruments, and its accuracy was tested using Pearson, MAE, RMSE, and MAPE correlation. The results showed a high measurement agreement between the prototype and the standard tool, with Pearson correlation values of 0.907 (TDS), 0.973 (EC), and 0.936 (temperature), respectively, signifying the high validity and precision of the measurements. Regression equations result in an effective calibration model to correct measurement bias. water- quality dynamics & density effect to Observations of various fish densities indicate that an increase in the number of fish increases TDS, EC, and pH fluctuations and also affects the thermal characteristics of the water. Regression analysis showed that fish density was a strong predictor of increased TDS (R² = 0.9098) and EC (R² = 0.8988). The study concluded that the prototype is feasible to be used for real-time monitoring and that the ideal density of Budikdamber ranges from 55 to 70 heads per 80-liter bucket to maintain water quality stability. Water management: the safest and optimal time to change pool water is in the afternoon, around 5:30–7:00 PM, with a waiting period of 4-5 days, offering a scalable physics-based monitoring framework for micro-aquaponics systems