This research was intended to create Spelling Correction Application to help teachers examine que... more This research was intended to create Spelling Correction Application to help teachers examine questions scripts with the capability to found typographical error and give suggestion for non-real word error. This application is built with simple Damerau-Levenshtein Distance method to detect errors and give word suggestions from the typo word. This application can be used by the teacher to examine documents in the form of short answer, essay and multiple choices then save them back in the form of original documents. This application is built using a dictionary lookup consist of 41 312 words in Indonesian. The first test result is the application can detect non-real word errors from 50 sentences that have non-real word error in each sentence and produce an accuracy of 88 %. The second test is try to detect typographical error in exam test script that consist of 15 sample questions, consisting of five essay questions, five short answer, and five multiple choices.
Computatio : Journal of Computer Science and Information Systems
This research was intended to create Indonesian Text Spelling Correction system with the capabili... more This research was intended to create Indonesian Text Spelling Correction system with the capability to handle and make correction to both kind of spelling errors, non-word and real-word errors. Existing spelling correction system was analyzed and made some adjustment and modifications to boost its accuracy. The proposed spelling correction system is built with Damerau-Levenshtein Distance that used in existing spelling correction system along with the adjustment and modifications. The result that achieved by the system that uses by existing spelling correction with the word level accuracy of 40.6% and an average processing speed of 18.4 ms per sentence while the result that achieved by the system that uses Damerau-Levenshtein Distance and Recurrent Neural Network with the word level accuracy of 21.3% and an average processing speed of 29.21 ms per sentence. The result of retest text that achieved by the system that uses Damerau-Levenshtein Distance and Recurrent Neural Network with ...
This research was intended to create Spelling Correction Application to help teachers examine que... more This research was intended to create Spelling Correction Application to help teachers examine questions scripts with the capability to found typographical error and give suggestion for non-real word error. This application is built with simple Damerau-Levenshtein Distance method to detect errors and give word suggestions from the typo word. This application can be used by the teacher to examine documents in the form of short answer, essay and multiple choices then save them back in the form of original documents. This application is built using a dictionary lookup consist of 41 312 words in Indonesian. The first test result is the application can detect non-real word errors from 50 sentences that have non-real word error in each sentence and produce an accuracy of 88 %. The second test is try to detect typographical error in exam test script that consist of 15 sample questions, consisting of five essay questions, five short answer, and five multiple choices.
Computatio : Journal of Computer Science and Information Systems
This research was intended to create Indonesian Text Spelling Correction system with the capabili... more This research was intended to create Indonesian Text Spelling Correction system with the capability to handle and make correction to both kind of spelling errors, non-word and real-word errors. Existing spelling correction system was analyzed and made some adjustment and modifications to boost its accuracy. The proposed spelling correction system is built with Damerau-Levenshtein Distance that used in existing spelling correction system along with the adjustment and modifications. The result that achieved by the system that uses by existing spelling correction with the word level accuracy of 40.6% and an average processing speed of 18.4 ms per sentence while the result that achieved by the system that uses Damerau-Levenshtein Distance and Recurrent Neural Network with the word level accuracy of 21.3% and an average processing speed of 29.21 ms per sentence. The result of retest text that achieved by the system that uses Damerau-Levenshtein Distance and Recurrent Neural Network with ...
Uploads
Papers by Fendy August