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All Journal TRANSFORMATIKA: Jurnal Bahasa, Sastra, dan Pengajarannya
Haris Oktariansyah
Universitas Bina Darma Palembang
Humanities Languange, Linguistic, Communication & Media Other

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Identifikasi Jenis-Jenis Parafrasa Artificial Intelligence Quillbot dalam Bahasa Indonesia: Identification of Types of Paraphrasing by Artificial Intelligence Quillbot in Indonesian Haris Oktariansyah; Yeni Ernawati
Transformatika: Jurnal Bahasa, Sastra, dan Pengajarannya Vol. 9 No. 4 (2025): TRANSFORMATIKA: JURNAL BAHASA, SASTRA, DAN PENGAJARANNYA
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/transformatika.v9i4.2972

Abstract

This study aims to identify the types of paraphrases generated by the artificial intelligence tool QuillBot in Indonesian and to analyze its effectiveness in reducing plagiarism in academic writing. The research employed a descriptive qualitative method with documentation and data analysis techniques, based on Longacre’s (1995) paraphrase theory. The data were taken from 18 journal abstracts covering topics in linguistics, education, and artificial intelligence. Additionally, the abstracts were sourced from various study programs within the Faculty of Social Humanities at Universitas Bina Darma Palembang to ensure linguistic variety and enrich the analysis. All abstracts were paraphrased using QuillBot Premium and analyzed with Turnitin. The results show that from 123 sentences, QuillBot generated six of seven paraphrase types: Equivalent (74), Negative Antonym (2), Generic-to-Specific (1), Amplification (14), Specific-to-Generic (12), and Contraction (20). Furthermore, QuillBot was found effective in reducing plagiarism, with an average decrease of 28.89% based on Turnitin results. The greater the initial similarity, the higher the reduction after paraphrasing. As supporting data, the perceptions of five final-year students were gathered, and respondents stated that QuillBot helped simplify the paraphrasing process and reduce similarity scores, although manual revision was still needed to ensure accuracy and naturalness of meaning.
Co-Authors Yeni Ernawati