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Design and Implementation Plagiarism Checker Application with DetectGPT using Scheduler Algorithm

Authors

  • Arif Supriyanto Politeknik Negeri Tanah Laut
  • Hendrik Setyo Utomo Politeknik Negeri Tanah Laut
  • Oky Rahmanto Politeknik Negeri Tanah Laut

DOI:

10.47709/brilliance.v3i2.3275

Keywords:

DetectGPT, AI, Scheduler, worker, Plagiarism

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Abstract

The increasing use of Generative AI in the field of writing in the academic world creates problems in the field of plagiarism. this problem has prompted an urgent need for plagiarism detection tools. However, not all universities are able to implement a system that is able to detect sentences or paragraphs resulting from generative AI. Recent research seeks to overcome this obstacle using AI itself, specifically through the DetectGPT model. However, the implementation of this technology has limitations, such as requiring large computing resources and quite a long examination time. Using a GPU can speed up the process, but not all users can implement it. Solutions to minimize processing time include using more than one worker, however, scheduling is essential to maximize plagiarism detection efficiency. This research proposes the implementation of the above system with the help of the scheduler. The results obtained in this system prototype are an average waiting time for checking of 457,778 seconds to complete 10 tasks with the help of 3 workers running at the same time.

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ARTICLE Published HISTORY

Submitted Date: 2023-12-10
Accepted Date: 2023-12-10
Published Date: 2023-12-26

How to Cite

Supriyanto, A., Utomo, H. S., & Rahmanto, O. (2023). Design and Implementation Plagiarism Checker Application with DetectGPT using Scheduler Algorithm. Brilliance: Research of Artificial Intelligence, 3(2), 338-342. https://doi.org/10.47709/brilliance.v3i2.3275

Issue

Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023

Section

Articles

License

Copyright (c) 2023 Arif Supriyanto, Hendrik Setyo Utomo, Oky Rahmanto

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.