<![CDATA[Fruit is a food and a good source of vitamins for the body's metabolic processes, but fruit is quickly damaged by the effects of physics, chemistry and microbiology if not given special treatment. Fresh fruit is one of the main needs in the health of the human body because the fruit contains nutrients and vitamins. Therefore, it is proposed to design an application that can classify fresh and rotten fruit. The method that will be used in this design is Convolutional Neural Network (CNN). The architecture that will be used in this design is AlexNet. The fruits that will be classified are apple, banana, grape, guava, jujube, orange, pomegranate, strawberry, mango and tamarillo. The test results on the training data produce an accuracy of 99% and the test on the test data or validation is 98% with the use of the adam optimizer. The confusion matrix shows that the trained model has an accuracy value of 98%, precision of 98%, recall of 98%, and F1-score of 98%. The output of the application is the introduction of fruit names and classification in the form of fresh or rotten.]]>
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