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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%.

The alternative to learning Japanese is to use mobile learning. Based on comparisons made on the 7 popular Japanese language learning applications in the PlayStore, there is no Japanese language learning application that has a speech recognition feature for Japanese sentence pronunciation. In this study Japanese hiragana learning application was designed for sentences using speech recognition. This application uses google cloud speech-to-text for speech recognition features. The algorithm that is applied in this application is the levenshtein distance to compare the user's voice input with the text in the database. Android based application for users and the web for admin. Based on the results of testing the accuracy and success of detection, the ideal distance of the application receiving the user's voice input is 50 cm in a noise-free environment with a successful detection of 100%. In testing before and after using the application there was an increase in vocabulary knowledge of 44.48% after users used the application. Based on usability testing using SUS, the result is 73.01 which indicates that the application falls into the acceptable category.

The library of Faculty of Medicine of University of Palangka Raya is one of the libraries that regulates its management conventionally, and has not utilized computer technology optimally. So that, the library needs to improve its performance over the time, perticularly in delivering information on books or in terms of circulation services of book borrowing and returning transactions. The methodology used in making this information system is method of modified Waterfall software. This method consists of four stages; (1) Analysis; (2) Design; (3) Implementation; (4) Testing. Errors in typing the words searched for by the users could cause the searching for information cannot be found. Thus, levenshtein distance algorithm would be able to display autocorrect or provide the word suggestions to improve the title of the book that had the closest distance value to the word typed. Based on the results of the levenshtein distance algorithm calculation for the single target book title search, it has an accuracy of 75%; for the multi target book title with 2 words, it has an accuracy of 64.29%; for the multi target book title with 3 words, it has an accuracy of 66.75%, and; for the multi target book title with 4 words has an accuracy of 70.83%.

ujuan dari penelitian ini adalah menerapkan algoritma Levenshtein distance pada aplikasi komputer yang dapat menghitung persentase kemiripan isi teks dokumen tugas siswa/mahasiswa sehingga dapat membantu guru/dosen dalam melakukan pendeteksian dugaan awal plagiarisme. Penelitian dilakukan di laboraturium Multimedia Jurusan Teknik Elektro Fakultas Teknik Universitas Negeri Jakarta dari bulan Agustus 2013 hingga April 2014. Metode yang digunakan adalah salah satu metode pengembangan perangkat lunak, yaitu metode Waterfall. Hasil uji coba menunjukkan bahwa setelah melalui tahapan-tahapan preprocessing, algoritma Levenshtein distance dapat diimplementasi pada aplikasi dan cocok untuk mendeteksi dugaan awal plagiarisme kata demi kata.