Plagiarism Detection Algorithm Using Natural Language Processing Based on Grammar Analyzing

Plagiarism has become one of the most concerned problems since there are several kinds of plagiarism that are hard to detect. Extrinsic plagiarism is now being handled well, but intrinsic plagiarism is not. Intrinsic plagiarism detection is being distracted by the mixed up structure and the using of another word which have the same meaning. Several methods have been research to handle this problem, not only using the pattern reading but also parsing the sentences, but still couldn’t give one more accurate way to detect it. In this research, we propose to use Natural Language Processing (NLP) to create the new way to detect plagiarism. Begin with using syntactic parsing method to parse the suspicious document and find the list of words which have the same meaning with it while considering the Part-Of-Speech (POS) element of that word (semantic parsing). This algorithm also includes creating the new structure of the object before comparing them. The result of this research presents the accuracy comparison between Ferret, WCopyFind, and this algorithm. This algorithm gives the significant way to detect the plagiarism which is proven by TTest.