Perancangan Deteksi Kemiripan pada Abstrak Artikel Ilmiah Informatika - Reza Pahlevi; Mira Ziveria (KALBISIANA Jurnal Sains, Bisnis dan Teknologi, 2022)
The purpose of this study is to develop a similarity detection application using cosine similiarity calculations which can be useful to find out the percentage of similarity of a text. Detection and calculation is done by cosine similiarity algorithm and framework flask with the help of the NLTK and Literature library which helps in proprocessing data to convert words that have affixes into standard words. Application development using the SDLC method. At the design stage the application detects and calculates the percentage of word-for-word similarities with cosine similiarity calculations. At the implementation stage cosine similiarity calculation will calculate the similarity of the text with the text. At the testing stage the cosine similiarity calculation will detect the similarity of words obtained from web forms built with the flask framework. The application can detect similarities in the text and display the similarity percentage.