Indonesian Spelling Error Detection and Type Identification using Bigram Vector and Minimum Edit Distance Based Probabilities

dc.contributor.authorErwina, Emmy
dc.date.accessioned2021-11-27
dc.date.available2021-11-27
dc.date.issued2021
dc.identifier.uri https://jurnal.polgan.ac.id/index.php/sinkron/article/view/11224/652
dc.description.abstract Spelling error has become an error that is often found in this era which can be seen from the use of words that tend to follow trends or culture, especially in the younger generation. This study aims to develop and test a detection and identification modelusing a combination of Bigram Vector and Minimum Edit Distance Based Probabilities. Correct words from error words are obtained using candidates search and probability calculations that adopt the concept of minimum edit distance. The detection results then identified the error type into three types of errors, namely vowels, consonants and diphthongs from the error side on the tendency of the characters used as a result of phonemic rendering at the time of writing. The results of error detection and identification of error types obtained are quite good where most of the error test data can be detected and identified according to the type of error, although there are several detection errors by obtaining more than one correct word as a result of the same probability value of these words.en_US
dc.language.isoenen_US
dc.publisherUniversitas Harapan Medanen_US
dc.subjectbigram; minimum edit distance; probabilities; spelling; vectoren_US
dc.titleIndonesian Spelling Error Detection and Type Identification using Bigram Vector and Minimum Edit Distance Based Probabilitiesen_US
dc.typeKarya Ilmiahen_US


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