<![CDATA[The export value of Indonesian fruits in 2023 will increase compared to 2021. For this reason, a program is needed to introduce fruit maturity, in this case, citrus fruits. Currently, the fruit maturity recognition system is still done manually which takes a long time and requires a lot of human resources. Thus, the purpose of this research is to use Machine Learning and the Convolution Neural Network (CNN) model in the classification of citrus fruit maturity. The computer image recognition method used is CNN, which has advantages in computer vision applications, face recognition, object detection, image recognition, and visual recognition. Datasets in the form of orange images are collected to be applied to the Machine Learning method. The test results showed that training accuracy reached 100% and validation accuracy reached 86.59% after 40 epochs using the CNN method on local varieties of orange images. Training loss reaches 0.7 and validation loss reaches 0.69 after 40 epochs.]]>
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