IZZAH, NURUL and Yusliani, Novi and Rodiah, Desty (2021) DETEKSI KEMIRIPAN TEKS BERBAHASA INDONESIA MENGGUNAKAN ALGORITMA RATCLIFF/OBERSHELP. Undergraduate thesis, Sriwijaya University.
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Abstract
Acts of plagiarism in written works are often encountered in everyday life. More and more texts circulating on the internet result in increased acts of plagiarism without citations due to a lack of creativity in the community. Prevention of plagiarism can be done by creating a software that is able to detect text similarities. In this study, the Ratcliff/Obershelp algorithm is used to detect text similarity. The steps taken are in the form of combining strings from 2 pieces of text to get the total character length of the text (sequence (string) matching). Then the stage (sub-sequence) is carried out to find the same word in the 2 texts and calculate the character length. The calculation of the value and percentage of similarity strings is carried out to classify the types of plagiarism that exist in the text. Classification of types of plagiarism is divided into 5 types and categorized based on the results of the percentage similarity string. The data used in this study is secondary data in the form of 20 Indonesian news texts with different website sources and divided into 5 topics. This data is obtained by the documentation method and stored in a file with .txt format. This text similarity detection software can generate percentage values and classifications of text similarity types. Software testing is carried out based on 3 scenarios, each of which will detect the similarity of the text. This test produces an average error percentage value of 0% in scenario 1, 8,33% in scenario 2, and 14,65% in scenario 3. Based on the test results of the 3 scenarios, the average error percentage of the text similarity detection software is obtained. in Indonesian using the Ratcliff/Obershelp algorithm of 7,66%.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Algoritma Ratcliff/Obershelp, Internet, Plagiarisme, Deteksi Kemiripan Teks, Teks Berbahasa Indonesia |
| Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. |
| Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
| Depositing User: | Ms. NURUL IZZAH |
| Date Deposited: | 18 Jan 2022 05:15 |
| Last Modified: | 18 Jan 2022 05:15 |
| URI: | http://repository.unsri.ac.id/id/eprint/61421 |
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