Sistem Pengenalan Aksara Sunda Menggunakan Metode Modified Direction Feature dan Learning Vector Quantization

Abstract: Sundanese script is one revised regional Indonesia which is the work of the sundanese have orthographic peculiarities in terms of how the writing system by using a non-latin character as well as in terms of the unique pronunciation, therefore his presence should be conserved. One of its preservation efforts is to build an sundanese script recognition systems, which in the process is to identify a pattern of characters can make use of a technique of feature extraction and classification of characteristics, one of which was modified direction featured (MDF) which is the hallmark of the extraction method based on the shape of the patterns on the image, whereas the methods used for the process of classification of characteristics of an image is learning vector quntization (LVQ). This system will accept input in the image of sundanese script and image patterns revised its characteristics will be taken and entered into the database that will be used as training data, then done in the result of the extraction of characteristics are grouped into classes to the nearest value identified on a class derived from the test image, its function is to support the introduction of this aksara can be combined with text to speech. Text to speech system (TTS) is a system that can turn text into speech, so that the output can be showing the introduction of aksara sunda examples of their pronunciation. The level of accuracy of the test results of the 300 samples data of aksara sunda verified correctly between the suitability of image characters with names and their pronunciation is of 78.67%.
Keywords: Pattern Recognition, Feature Extraction, Classification, Text-to-Speech
Penulis: rizki rahmat riansyah, Youllia Indrawaty Nurhasanah, Irma Amelia Dewi
Kode Jurnal: jptinformatikadd170251

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