Levenshtein Distance Algorithm in Javanese Character Translation Machine Based on Optical Character Recognition

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Observational analysis improved translation accuracy of Javanese script to Indonesian language, suggesting technological enhancement is vital.

Translation accuracy improved to 90% for words and 70% for sentences, highlighting gaps in sentence translation accuracy.
The convolutional neural network approach achieved a 95% image detection accuracy at the 21st epoch during the analysis.
Incorporating optical character recognition enhanced data capture of Javanese script, crucial for cultural preservation ambitions.
Further advancements may require transformer models or data augmentation to address limitations in training data.

Pradana et al. (2025) studied this question.

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Observational analysis improved translation accuracy of Javanese script to Indonesian language, suggesting technological enhancement is vital.