Prototipe Portabel Berbasis pH dan Turbiditas untuk Estimasi Cepat Asam Lemak Bebas pada Minyak Sawit Mentah
Abstract
Free fatty acid is an important parameter in determining the quality of crude palm oil. High free fatty acid content can reduce oil quality and cause economic losses in palm oil processing. The conventional method commonly used to determine free fatty acid content is acid-base titration, but this method requires chemicals, laboratory equipment, and relatively long analysis time. This study aimed to design a portable device for rapid detection of free fatty acid content in crude palm oil using pH meter, turbidity meter, and artificial neural network. Oil samples were obtained from oil palm fruitlets with different physical damage levels. Free fatty acid content was measured using titration, while pH and turbidity were used as input variables in the artificial neural network model. The results showed that pH had a relationship with free fatty acid content with a coefficient of determination of 0.3516, while turbidity had a stronger relationship with a coefficient of determination of 0.7636. The best artificial neural network model was obtained using the tansig-logsig-logsig activation function, with R² of 0.9501 and RMSE of 0.6390 in calibration. In the testing stage, the model produced R² of 0.8061 and RMSE of 1.9222. The developed prototype can be used as a rapid method to estimate free fatty acid content in crude palm oil.
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