Adsorption is the process of interaction between a liquid and a solid surface. It happens because of physical forces or chemical bonds, which moves substance molecules dissolved in a liquid to the solid surface. As a result, the concentration of the substance in the solution drops. In this study, an artificial neural network (ANN) was applied to model the adsorption of Amorphophallus oncophyllus Prain and xanthan gum on sand grains with sizes of 40 mesh and 60 mesh. Two ANN models were developed. The first ANN model was used to predict the final concentration of the polymer solution after the adsorption process. This model had a correlation coefficient for the training, validation, and testing phases of 0.9968, 0.9982, and 0.9990, respectively. Meanwhile the second ANN model was used to predict the adsorbed polymer. This model had a correlation coefficient for the training, validation, and testing phases of 0.9984, 0.9996, and 0.9985, respectively. These models were capable of accurately predicting the final concentration and adsorbed polymer when compared to laboratory data.
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