Experimental Dataset for Machine Learning Modeling of Dye Removal by Moringa Oleifera Natural Coagulant

This dataset comprises 85 experimental runs focused on the optimization of dye removal from wastewater using Moringa oleifera as a natural coagulant. The experimental design follows a Rotational Central Composite Design (RCCD) to evaluate the influence of key operational parameters on treatment efficiency.

The dataset includes:

Input Variables: Initial dye concentration (Conc), Slow Mixing Time (SMT), Fast Mixing Time (FMT), and Coagulant Dosage.

Output/Response Variables: Final Absorbance (Final ADS), Final Concentration, and Removal Efficiency (%).

This data is intended for statistical optimization and the development of predictive Machine Learning models. It integrates both previously published data (used for validation) and original experimental results.