Classification of Document Similarity Using Winnowing Algorithm with Jaccard Coefficient Approach
Keywords:
Jaccard Coefficient, Plagiarisme, Similarity, Stopword, WinnowingAbstract
In the era of information technology advancement, easy access to various sources of information through the internet has changed the way students conduct research. While it provides significant benefits, this convenience also brings the problem of plagiarism, which is a detrimental act in the academic world. Plagiarism is the act of copying or taking ideas from someone else's work without giving proper credit, which is contrary to academic guidelines. This research aims to develop an effective plagiarism detection system that is in accordance with the Indonesian language. This system uses a Winnowing algorithm with a Jaccard Coefficient approach and a technique of eliminating non-descriptive words (stopwords) in Indonesian. Samples of documents in Indonesian were taken from the final project of Mercu Buana University students. The data is collected from the university's repository and will be analyzed to measure the level of similarity between documents and the performance of the Winnowing algorithm in detecting plagiarism. The results of this study show that the development of a plagiarism detection system using the Winnowing algorithm and the Jaccard Coefficient approach with an n-gram value of 7 succeeded in achieving optimal results with precision, recall, and accuracy results reaching 100%. The similarity index detection system is able to provide accurate and relevant results on Indonesian documents.
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