RABIN-CARP IMPLEMENTATION IN MEASURING SIMALIRITY OF RESEARCH PROPOSAL OF STUDENTS

Abstract

Plagiarism is the use of data, language and writing without including the original author or source. The place where palgiate practice occurs most often is the academic environment. In the academic world, the most frequently plagiarized thing is scientific work, for example thesis. To minimize the practice of plagiarism, it is not enough to just remind students. Therefore we need a system or application that can help in measuring the level of similarity of student thesis proposals in order to minimize plagiarism practice. In computer science, the Rabin-Karp algorithm can be used in measuring the level of similarity of texts. The Rabin-Karp algorithm is a string matching algorithm that uses a hash function as a comparison between the search string (m) and substrings in text (n). The Rabin-Karp algorithm is a string search algorithm that can work for large data sizes. The test results show that the use of values on k-gram has an effect on the results of the measurement of similarity levels. In addition, it was also found that the use of the value 5 on k-gram was faster in executing than the values 4 and 6.