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The Development of Javanese Language Teaching Materials Through Introduction of Java Scripts Using Artificial Neural Network

Authors: Siswo Wardoyo; Kuntari W.; Anggoro S. Pramudyo; Suhendar Suhendar; Syarif Hidayat;

The Development of Javanese Language Teaching Materials Through Introduction of Java Scripts Using Artificial Neural Network

Abstract

The Java script is a traditional Indonesian scripts known as Hanacaraka or Carakan. Java script becomes less desirable students who have not been introduced by Master to students using interesting digital media. Javanese language teachers in teaching activities do not yet have interactive learning media in making Java script. This research aims to develop digital media recognition Java script using artificial neural network back propagation method as a teaching material of Java language. The sample of research used is basic java script which consist of 20 characters. The method of extraction properties used is Fast Fourier Transform, which is sampled horizontally and vertically. The result of this research showed FFT and ANN can be made of interactive learning media. The effectiveness of system with sensitivity value of 0,046 - 0,085, specification value 0,023 - 0,052, and system reliability is 59,5%. Validation value system that has been built for pattern recognition Java script on the training process is 100%, the testing process with the data -3o rotation, -1o, +1o, +3o reaches 100%, for a rotation -5o testing data, and +5° is 80%, testing of handwritten data is 65%, the test data +10o rotation is 25%, the test with the data translation is 5%, and for testing with the data and the data of rotation +90° zoom in (view) is 0%.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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