AuthenTracK: Tracking and Verifying Content Authenticity with AI

Thorvi N., Dhawale and Khushi K., Bhanarkar and Riya R., Wakode and Snehal S., Dakhare and Prof. Suman, Sengupta (2024) AuthenTracK: Tracking and Verifying Content Authenticity with AI. International Journal of Trend in Scientific Research and Development, 8 (5). pp. 280-287. ISSN 2456-6470

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Abstract

Plagiarism is a significant problem in academic settings, compromising the values of originality and intellectual honesty. With the increasing availability of digital information, both accidental and deliberate plagiarism have become more prevalent. This paper presents a plagiarism detection tool designed with simplicity, efficiency, and accessibility in mind, specifically targeting college students and academic institutions. The main goal of this project is to develop a user-friendly tool that enables fast and accurate identification of potential plagiarism in academic writing. A key feature of the plagiarism checker is its simple design, which makes it accessible to both students and educators with minimal technical knowledge. It offers real-time analysis, allowing users to upload or paste their text and receive instant results. In conclusion, this research underscores the importance of accessible and efficient plagiarism detection tools in educational environments. By developing an easy-to-use plagiarism checker, this project promotes academic integrity and encourages students to create original content.

Item Type:	Article
Subjects:	Q Science > Q Science (General)
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	25 Oct 2024 05:23
Last Modified:	25 Oct 2024 05:23
URI:	http://eprints.umsida.ac.id/id/eprint/14387

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