The application of Rabin-Karp algorithm and stemming to detect similarity of electronic documents Available to Purchase

Submission of information has been supported by the presence of electronic documents in recent years. Checking the similarity of the contents of the electronic documents continues to be carried out to improve the quality of information and overcome plagiarism. The problem with checking the similarity of document contents at the Faculty of Engineering and Information Systems, Yapis University Papua, is that the process and results of checking the similarity of document contents that have been carried out so far have not been optimal. The research aimed at increasing the effectiveness and efficiency of the document content similarity checking process by presenting a document similarity detection system and applying the Rabin Karp algorithm along with stemming to determine the percentage similarity of electronic document contents. It also applied the waterfall development model, fishbone analysis model, and UML. The preprocessing stages on the Rabin Karp algorithm are case folding, tokenizing, filtering, and stemming. The research results are a website-based system that can check the documents being tested, namely ten Information System Student Journals at Yapis Papua University, with a total time of 33.896 seconds and produce optimal percentages in journals with text content lengths of less than 14,500 mixed characters without spaces.