Model for Predicting and Classifying Durian Fruit Based on Maturity and Ripeness Using Neural Network

Abstract This study was aimed to develop the model to predict the maturity, ripeness and defects of durian based on its physical and chemical characteristics by using the neural network. The density and acoustic characteristics measurement was fed into the model as the inputs, which provided the levels of maturity and ripeness as the output. Data training were tested to models of neural network with various nodes in the hidden layer, i.e., 4, 6, 8, and 10 nodes. The results recommended the use of 6 nodes in the hidden layer that would provide the highest accuration of 100 % in classifying the durian based on its maturity and ripeness.