INDONESIAN TEXT DOCUMENT SIMILARITY DETECTION SYSTEM USING RABIN-KARP AND CONFIX-STRIPPING ALGORITHMS

Sinaga, Deardo Dibrianto and Hansun, Seng (2018) INDONESIAN TEXT DOCUMENT SIMILARITY DETECTION SYSTEM USING RABIN-KARP AND CONFIX-STRIPPING ALGORITHMS. International Journal of Innovative Computing, Information and Control, 14 (5). ISSN 1349-4198

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Abstract

Nowadays, negative impact, such as plagiarism, may arise along with faster and easier ways in finding information. There are many software and websites that can be used to check the occurrence of plagiarism, but unfortunately, they are not really suitable for scientific papers which are written in Bahasa Indonesia because it is designed for text in English. Therefore, a document similarity detection system that is more suitable for papers written in Bahasa Indonesia is needed. Rabin-Karp is an algorithm that can be used in checking the similarity between documents, while Confix-Stripping is an algorithm that can perform basic word search in Bahasa Indonesia. This research has successfully implemented Rabin-Karp and Confix-Stripping algorithms very well. Tests performed with various document scenarios as well as algorithms have given some performance results of the system in terms of time and similarity level. The system with the pure Rabin-Karp can provide the best system performance, both in terms of time and accuracy with an average total processing time speed of 0.0123 second and the average similarity rate of 89.1967%. The accuracy level given by the system is 0.7. The system that has been added with a stemming process or N-Gram can also improve some test results in terms of processing time and similarity level.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming
400 Language > 490 Other language
Divisions: Fakultas Teknik Informatika > Program Studi Informatika
Depositing User: mr admin umn
Date Deposited: 19 Oct 2021 04:49
Last Modified: 19 Oct 2021 04:49
URI: http://kc.umn.ac.id/id/eprint/18858

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