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All Journal Jurnal Linguistik Komputasional
Novi Yusliani
Teknik Informatika, Univeristas Sriwijaya
Computer Science & IT

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Sistem Deteksi Kemiripan Teks Pada Berita Berbahasa Indonesia Menggunakan algoritma Ratcliff/Obershelp Nurul Izzah; Novi Yusliani; Desty Roodiah
Jurnal Linguistik Komputasional Vol 5 No 1 (2022): Vol. 5, NO. 1
Publisher : Indonesia Association of Computational Linguistics (INACL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jlk.v5i1.65

Abstract

Plagiarism in writing is often found in various media, one of which is the internet. Prevention can be done by creating an intelligent system capable of detecting text. One of the algorithms used to create a text finding system is the Ratcliff/Obershelp algorithm. This algorithm combines a string of 2 pieces of text to get the total character length (sequence (string) matching). The results are used to search for similar words ( sub-sequence ) and calculate the character length. The calculation of the similarity value and the percentage is carried out to classify the types of plagiarism that exist in the text. The data used are 8 Indonesian news texts with different internet sources which are divided into 2 topics and the average error percentage is 0.26%.
Co-Authors Desty Roodiah Nurul Izzah