Abstract
Good scriptwriting or reporting requires a high level of accuracy. The basic problem is that the level of accuracy of the authors is not the same. The low level of accuracy allows for mistyping of words in a sentence. Typing errors caused the word to become non-standard. Even worse, the word became meaningless. In this case, the recommendation application serves to provide word-writing recommendations in case of a typing error. This application can reduce the error rate of the writer when typing. One method to improve word spelling is Approximate String Matching. This method applies an approach to the string search process. The Levenshtein Distance algorithm is a part of the Approximate String-Matching method. This method, firstly, is necessary to go through the preprocessing stage to correct an incorrectly written word using the Levenshtein Distance algorithm. The application testing phase uses ten texts composed of 100 words, ten texts composed of 100 to 250 words, and ten texts composed of 250 to 500 words. The average accuracy rate of these test results was 95%, 94%, and 90%.
Highlights
Typing a report manuscript or an essay requires high accuracy
This method, firstly, is necessary to go through the preprocessing stage to correct an incorrectly written word using the Levenshtein Distance algorithm
Spelling errors and writing non-standard terms can change the true meaning of information and lead to readers' misinterpretation [1]. We can avoid these typing errors by using an Approximate String Matching method, which is a method for matching a string based on similarity in terms of writing, both the number of characters and the composition of characters in a document [2]
Summary
Typing a report manuscript or an essay requires high accuracy. The level of accuracy of a writer has different levels. The factor that causes typing errors is a habit of a writer in abbreviating a word This typing error problem often occurs when a writer writes scientific papers, proposals, or reports for school, college, or work needs. Spelling errors and writing non-standard terms can change the true meaning of information and lead to readers' misinterpretation [1] We can avoid these typing errors by using an Approximate String Matching method, which is a method for matching a string based on similarity in terms of writing, both the number of characters and the composition of characters in a document [2]. The smaller the distance between the two strings indicates that the two strings are match [3] Fixing this problem can use the Levenshtein Distance algorithm with a high level of accuracy in terms of similarity search words. This application helps minimize word writing errors, both words that are not standard or words that have no meaning
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
