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Tri Gatra Bangun Bahasa, namely prioritizing Indonesian, preserving local languages and mastering foreign languages. Through this, the local language as one of the wealth of the Indonesian nation needs to be preserved. In addition, local languages also function as a supporter of the national language, namely Indonesian. The use of technology can be used as an effort to preserve local languages. This study utilizes artificial intelligence technology, namely machine translation that translates Indonesian into local languages based on text images. The local language used is the Minang language. The focus of this research is the process of translating the results of Optical Character Recognition from Indonesian text images using the edit distance algorithm, namely Hamming distance, Leveinshtein distance and Jaro-Winkler. The results of this study indicate that the edit distance algorithm can improve the OCR results in translating into local languages. OCR results on text images have an initial accuracy of 50.72%. After applying the edit distance algorithm, the translation accuracy increases to 68.34% for the Hamming distance algorithm, 70.5% for the Leveinshtein distance algorithm and 70.2% for the Jaro-Winkler algorithm. Of the three algorithms, Leveinshtein distance has the highest translation accuracy performance.

Penerjemahan Bahasa Indonesia ke Bahasa Minang dari Optical Character Recognition dengan Menggunakan Algoritme Edit Distance