<![CDATA[Green synthesis of iron oxide nanoparticles (IONPs) has emerged as an eco-friendly alternative to conventional synthesis methods. This method utilizes natural ingredients, such as green tea extract, as a reducing agent that supports the green chemistry process. This research aims to analyze the effects of precursor concentration, reducing agent volume, and reaction temperature on the synthesis results using technical and pro-analytical FeCl3.6H2O precursors. A full factorial design was employed to assess the effect of synthesis conditions on the IONPs yield. The yield was statistically analyzed using analysis of variance (ANOVA). The analysis results reveal that the predicted values are within reasonable consistency based on the experimental data of both IONPs from the technical and pro-analytical precursors. The ANOVA values for both precursor sources show that the reaction temperature factor is negatively correlated, while the precursor concentration and reducing agent volume positively correlate with the IONPs yield. Regression model variance (ANOVA) can be explained 98.15% for the technical precursor model and 99.83% for the analytical precursor model from data variations. This research can determine the optimal combination of synthesis factors that provide a basis for selecting a synthesis strategy tailored to specific performance requirements. These findings can support the wider application and reproducibility of green synthesis methods in various research contexts and implications for industry.]]>
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