PEMODELAN RESPON SURFACE METHODOLOGY (RSM) UNTUK MEMPREDIKSI pH DAN ARUS LISTRIK LARUTAN SISA PENCELUPAN POLIESTER MENGGUNAKAN ELEKTROKOAGULAN - Dewi, Siska Astari; Rahma Kusuma Wardhani, Elfira; Novianti, Keke; Nabilla Putri, Salma; Eka Mulyani, Rr Wiwiek (Texere, 2025)
Treating wastewater from polyester dyeing processes using disperse dyes is essential for environmental conservation. Among various treatment methods, electrocoagulation presents a promising alternative for textile effluent remediation. This study developed predictive models using Response Surface Methodology (RSM) to optimize the electrocoagulation process by examining the effects of process duration (0-30 minutes) and applied voltage (5-9 Volts) on pH and electric current. Results demonstrated that the RSM model achieved excellent predictive accuracy for electric current (R² = 0.9786), while the pH model showed moderate correlation (R² = 0.6013). Statistical validation confirmed model reliability through adjusted R², predicted R², and adequate precision values. The research identified optimal time-voltage parameter ranges for experimental waste treatment applications. Both independent variables significantly influenced the observed responses, with voltage exerting a dominant effect on electric current generation during electrocoagulation. These findings contribute to the development of more efficient treatment processes for textile wastewater and align with previous studies highlighting electrocoagulation's effectiveness in pollutant removal from industrial effluents.