<![CDATA[Apple fruit is one of the important agricultural commodities in the farming industry. The maturity level of apple fruit is a key factor that affects its quality and shelf life. Manual determination of apple fruit maturity levels is often time-consuming and subjective. Therefore, this research aims to develop an automation system that can classify the maturity levels of apple fruit using the Convolutional Neural Network (CNN) method on the Android platform.Image data of apple fruit at various maturity levels were collected and processed in this study. A CNN model was designed, trained, and optimized using this data to identify the maturity levels of apple fruit from images. The final outcome of this research is a user-friendly Android application that can assist apple farmers in quickly and accurately classifying the maturity levels of apple fruit.The research results indicate that the CNN model can recognize the maturity levels of apple fruit with high accuracy, and the generated Android application provides easy access for users to support apple farming by enhancing efficiency in harvest management and apple processing]]>
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