<![CDATA[The turtle population in Indonesia continues to decline every year and is categorized as an endangered species. Lack of public knowledge about protected turtle species is one of the factors hampering conservation efforts. This study aims to design and build an Android-based application that can classify three types of turtles: the Green Turtle (Chelonia mydas), the Hawksbill Turtle (Eretmochelys imbricata), and the Olive Ridley Turtle (Lepidochelys olivacea). Software development uses the Extreme Programming (XP) method, consisting of planning, design, coding, and testing stages. The application is built with the Flutter framework and integrates a Convolutional Neural Network (CNN)-based machine learning model to classify images. Users can input images through the camera or device gallery. Blackbox testing results show that all application functionality, including navigation, image capture, and the classification process, runs as expected. This application is expected to be an educational medium to increase public awareness in turtle conservation efforts. Keywords— Classification, Turtle, Flutter, Android, Extreme Programming]]>
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