Hasan, Eric Ganiwijaya and Wicaksana, Arya and Hansun, Seng (2018) The Implementation of Winnowing Algorithm for Plagiarism Detection in Moodle-based E-learning. In: 2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS), 6-8 June 2018, Singapore.
Full text not available from this repository.Abstract
The act of plagiarism is inappropriate and untrue for any reasons, especially in the academic world. Academicians are aware of this and try to avoid the act of plagiarism by any means necessary. In Universitas Multimedia Nusantara (UMN), an online learning (E-learning) system is used as an additional tool to support teaching process. The E-learning system is Moodle-based with one of its features is the assignment submission. The preliminary survey shows that 23.2% respondents had committed the act of plagiarism when doing assignments in E-learning in the past. Due to the lack of plagiarism detection feature in Moodle-based E-learning system, thus this research proposes a plagiarism detection feature as a plug-in for the E-learning system. The plagiarism detection plug-in handles assignments that are in the format of text documents. The plug-in makes use of Winnowing algorithm for fingerprinting the assignment documents and the hashing technique chosen for the Winnowing algorithm is Rolling Hash. The similarity value is calculated using Jaccard Coefficient. As a demonstration of feasibility, the implementation is done in Moodle-based E-learning UMN. The test results show the combinations of parameters (k-gram, window length, and the base prime number) for the plug-in and the f-measure. The plug-in successfully detects plagiarism on student assignment in E-learning UMN.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 14 Oct 2021 04:00 |
| Last Modified: | 12 Jun 2024 04:22 |
| URI: | https://kc.umn.ac.id/id/eprint/18741 |
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