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In this paper researcher is trying to make an android-based application that can identify fish with formalin with previous version with adding some more data training. The method used in researcher methods naïve Bayes classifier as a detector (detector) with the object input in the form of fish eye image. The steps in the study include the training and testing process. In the training process used to build the model naïve classifier and estimation parameters. While testing process, implement the results of the model and parameter estimation have been built to detect fish formalin or not formalin. The trial results demonstrate the ability-based applications using the naïve Bayes 98.3% for object dimensions 10x10 image
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