IMPLEMENTASI ALGORITMA POLYNOMIAL REGRESSION UNTUK PREDIKSI PERTUMBUHAN TANAMAN PAKCOY PADA SISTEM HIDROPONIK - Yurni Oktarina; Rendi Dwi Yanto; Tresna Dewi (JURNAL TELISKA, 2026)
This study aims to apply the polynomial regression algorithm to model and predict the growth of pakcoy plants in a hydroponic system. The observed growth parameters include plant height, plant width, and number of leaves, with plant age used as the independent variable. Data were collected over two planting periods, with weekly observations conducted from the seedling stage until harvest. In addition to morphological parameters, Total Dissolved Solids (TDS) and water temperature were recorded as supporting parameters to ensure stable cultivation conditions throughout the study. The non-linear relationship between growth parameters and plant age was represented using a second-order polynomial regression model. The modeling results indicate a good level of fit, with coefficients of determination (R²) of 0.989 for plant height, 0.946 for plant width, and 0.970 for number of leaves, respectively. The relatively low Root Mean Square Error (RMSE) values for each parameter indicate that the model is capable of providing predictions with low estimation error. These findings demonstrate that second-order polynomial regression is a simple and effective approach for modeling the growth dynamics of pakcoy plants in hydroponic systems with limited data availability