<![CDATA[Massive technological developments continue to occur and penetrate into all sectors of the world's people's lives. In Indonesia in particular, various studies need to be carried out to develop various 4.0 technologies in agriculture and apply them to improve the quality and quantity of production. One of the technologies in agriculture that needs to be developed is the identification of fruit maturity, where this needs to be done considering the limitations of the human senses in determining the level of maturity based on the RGB value of the fruit. In this study, an Artificial Neural Network (ANN) approach with the Backpropagation algorithm was used. The dataset used consists of 90 photos of dragon fruit for training data and 15 photos of dragon fruit for data testing. The results obtained are that the ANN model built is able to identify the level of fruit maturity with 100% accuracy based on the dataset used]]>
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