Abstract
Agricultural modernization is crucial for the economic development of agriculture. Technique for order preference by similarity to an ideal solution (Topsis) and artificial neural network (ANN) were employed to evaluate and predict agricultural modernization level. A three-layer ANN models were developed to predict agricultural modernization level. The models were compared using the mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE). The 5-4-1 ANN model with standardization transformation was the best model. Topsis and ANN are useful tools to evaluate agricultural modernization level and to provide policy proposals for more efficient decision-making for the local government.
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