Sign language is the language used by people with limited speech or hearing. However, not everyone knows how to translate sign language in letters. Therefore, this research is motivated because there are many people who are normal or who do not have disabilities in speaking or listening who do not know how to communicate with people who have these limitations. So from this i raised a topic for the final project, "Application of Indonesian Sign Language Into Alphabet Letters. By using the Convolutional Neural Network classification method using the MobilenetV2 model architecture. The results of the classification will be exported into a model which will then be processed using Tensorflow Lite Android Studio. Based on the results of model testing, the resulting accuracy level reaches 0.9995 with a loss value of 0.6982. So that the performance of the application detection is not optimal. In addition, this application also displays animated letters of the Indonesian sign language alphabet so that people can also learn Indonesian sign language in visual form.
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