HUBUNGAN ANTARA PROBLEMATIC CHATGPT USE DAN KETIDAKJUJURAN AKADEMIK PADA MAHASISWA
DOI:
https://doi.org/10.51878/paedagogy.v5i4.7628Keywords:
Ketidakjujuran Akademik, Penggunaan ChatGPT Secara Bermasalah, MahasiswaAbstract
Academic dishonesty among students is a serious challenge for higher education, especially in the digital era marked by advances in artificial intelligence technologies such as ChatGPT. This phenomenon encompasses various forms of cheating, including plagiarism, cheating on assignments, asking others to complete tasks, falsifying research data, and misusing AI to obtain instant results without independent effort. This study uses a quantitative approach with a convenience sampling technique, involving students aged 18-25 who use ChatGPT. The instruments used include the Problematic ChatGPT Use Scale, which has been adapted into Indonesian and proven valid and reliable, as well as an Academic Dishonesty Scale with 11 items, with CFA results showing a good and reliable fit. Data were analyzed using Pearson correlation with SPSS. This study aims to contribute to the oversight of AI usage, by strengthening academic integrity through campus policies, improving digital literacy, and providing ethical guidance. The findings show a very strong and significant positive correlation between the two variables, with a Pearson coefficient of r = 0.871 and a significance level of p < 0.001 (p = 0.000). These findings indicate that the higher the problematic use of ChatGPT, the higher the level of academic dishonesty. Based on these results, it is recommended that higher education institutions develop stricter policies regarding AI use, including formulating clear ethical guidelines and developing evaluation methods that emphasize students' critical thinking and independent abilities. This study also provides a foundation for the development of deeper digital literacy to ensure that AI technology is used wisely and responsibly without compromising academic integrity.
ABSTRAK
Ketidakjujuran akademik di kalangan mahasiswa menjadi tantangan serius bagi dunia pendidikan tinggi, terutama di era digital yang ditandai dengan kemajuan teknologi kecerdasan buatan seperti ChatGPT. Fenomena ini mencakup berbagai bentuk kecurangan, seperti plagiarisme, menyontek, meminta orang lain mengerjakan tugas, memalsukan data penelitian, serta penyalahgunaan AI untuk memperoleh hasil instan tanpa usaha mandiri. Penelitian ini menggunakan pendekatan kuantitatif dengan teknik convenience sampling, melibatkan mahasiswa berusia 18-25 tahun yang menggunakan ChatGPT. Instrumen yang digunakan adalah Problematic ChatGPT Use Scale yang telah diadaptasi ke dalam bahasa Indonesia dan terbukti valid serta reliabel, serta Skala Ketidakjujuran Akademik dengan 11 item yang hasil uji CFA menunjukkan model fit yang baik dan reliabel. Data dianalisis dengan korelasi Pearson menggunakan SPSS. Penelitian ini bertujuan untuk memberikan kontribusi terhadap pengawasan penggunaan AI, dengan memperkuat nilai integritas akademik melalui kebijakan kampus, peningkatan literasi digital, serta pendampingan etis. Temuan penelitian menunjukkan adanya korelasi positif yang sangat kuat dan signifikan antara kedua variabel, dengan nilai koefisien Pearson r = 0.871 dan tingkat signifikansi p < 0.001 (p = 0.000). Temuan ini menunjukkan bahwa semakin tinggi penggunaan ChatGPT yang bermasalah, semakin tinggi pula tingkat ketidakjujuran akademik. Berdasarkan hasil ini, disarankan agar institusi pendidikan tinggi merancang kebijakan yang lebih ketat terkait penggunaan AI, termasuk merumuskan pedoman etika yang jelas dan mengembangkan metode evaluasi yang menekankan kemampuan berpikir kritis serta independen mahasiswa. Penelitian ini juga memberikan dasar bagi pengembangan literasi digital yang lebih mendalam, untuk memastikan teknologi AI digunakan secara bijak dan bertanggung jawab tanpa merusak integritas akademik.
Downloads
References
Amalia, N. W., & Layyinah. (2025). Faktor-Faktor yang Mempengaruhi Kecurangan Akademik pada Siswa SMA dan SMK: Sebuah Scoping Review. Edukatif: Jurnal Ilmu Pendidikan, 7, 1-16. https://edukatif.org/edukatif/article/view/8252
Besalti, M. (2025). Harnessing Self-Control and AI: Understanding ChatGPT’s Impact on Academic Wellbeing. Behavioral Sciences, 15(9). https://doi.org/10.3390/bs15091181
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Education and Training, 65(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
Dehouche, N. (2021). Plagiarism In The Age Of Massive Generative Pre-Trained Transformers (GPT-3). Ethics in Science and Environmental Politics, 21, 17-23. https://doi.org/10.3354/esep00195
Eastman, K., Eastman, J., & Iyer, R. (2008). Academic Dishonesty: An Exploratory Study Examining Whether Insurance Students Are Different From Other College Students. Risk Management and Insurance Review, 11(1), 209–226. https://doi.org/10.1111/j.1540-6296.2008.00138.x
Faradiena, F. (2019). Uji Validitas Alat Ukur Ketidakjujuran Akademik. Jurnal Pengukuran Psikologi Dan Pendidikan Indonesia, 8(2), 88–104. https://doi.org/10.15408/jp3i.v8i2.13316
Fitriyani, I. (2021). Implementasi Teori Thomas Lickona Terhadap Problem Ketidak Jujuran. Jurnal Pendidikan Islam Al-Ilmi, 4(1). https://doi.org/https://doi.org/10.32529/al-ilmi.v4i1.932
Guillén-Gámez, F. D., Sánchez-Vega, E., Colomo-Magaña, E., & Sánchez-Rivas, E. (2025). Incident factors in the use of ChatGPT and dishonest practices as a system of academic plagiarism: the creation of a PLS-SEM model. Research and Practice in Technology Enhanced Learning, 20, 28. https://doi.org/10.58459/rptel.2025.20028
Hidayat, R. W., & Sangka, K. B. (2025). Penggunaan ChatGPT Sebagai Variabel Moderasi Pada Kecurangan Akademik Mahasiswa: Sebuah Tinjauan Fraud Pentagon. Jambura Economic Education Journal, 7(3), 215-225.https://doi.org/10.37479/jeej.v7i3.27613
Jones, S. M., & Kahn, J. (2017). Promoting Social And Emotional Learning In Schools: A Review Of The Literature. American Journal of Education, 123(1), 1-33. https://doi.org/10.1086/693002
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103. https://doi.org/10.1016/j.lindif.2023.102274
Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv:2506.08872 [cs.AI]. https://doi.org/10.48550/arXiv.2506.08872
Maral, S., Nayc?, N., Bilmez, H., Erdemir, E. ?., & Satici, S. A. (2025). Problematic ChatGPT Use Scale: AI-Human Collaboration or Unraveling the Dark Side of ChatGPT. International Journal of Mental Health and Addiction. https://doi.org/10.1007/s11469-025-01509-y
Mccabe, D. L., & Trevino, L. K. (1993). Academic Dishonesty: Honor Codes and Other Contextual Influences. Source: The Journal of Higher Education, 64(5), 522–538. https://www.jstor.org/stable/2959991
Mendolia, T. A. (2024). Academic Dishonesty In The Age Of AI: Connecting Student Generative AI Use And The Fraud Triangle Within Health Professions Education (Doctoral dissertation, University of North Texas). https://digital.library.unt.edu/ark:/67531/metadc2416007/
Narvaez, D., & Lapsley, D. K. (2017). Teaching for moral development and moral education. International Journal of Educational Research, 82, 71-84. https://doi.org/10.1016/j.ijer.2017.02.006
Nguyen, H. M., & Goto, D. (2024). Unmasking Academic Cheating Behavior In The Artificial Intelligence Era: Evidence From Vietnamese Undergraduates. Education and Information Technologies, 29(12), 15999–16025. https://doi.org/10.1007/s10639-024-12495-4
Phillips, B., & Shipps, B. (2022). Problematic Technology Use: The impact of personality and continued use. The Journal of the Southern Association for Information Systems, 9(1), 38–63. https://profiles.ncat.edu/en/publications/problematic-technology-use-the-impact-of-personality-and-continue-4/
Pratama, R. D., Sangka, K. B., & Nugroho, J. A. (2023). The Influence of Fraud Diamond Perspective and Artificial Intelligence Factors on Academic Dishonesty Indonesian College Student. International Journal of Multicultural and Multireligious Understanding, 10(11), 164. https://doi.org/10.18415/ijmmu.v10i11.5248
Sain, Z. H., Sari, V., & Kurniati, D. (2023). Exploring the Impact of Chat GPT on Higher Education: Advantages, Hurdles, and Prospective Research Avenues. Tamansiswa International Journal in Education and Science, 5(1), 34–61. https://doi.org/https://doi.org/10.30738/tijes.v5i1.16274
Sasmi, A. A., Ikhwan, M., Gurendrawati, E., Suherdi, & Nurfaizana, D. R. (2024). Ketika kecerdasan buatan menjadi alat kecurangan tingkat lanjut: Tantangan dan peran kepribadian mahasiswa. Jurnal Riset Pendidikan Ekonomi (JRPE), 9(2), 159–166. https://doi.org/10.21067/jrpe.v9i2.10523
Setyawan, H., Akhyar, M., & Widiastuti, I. (2021). Analisis Ketidakjujuran Akademik Pada Mahasiswa Calon Guru Kejuruan Bidang Teknik Mesin. Jurnal Ilmiah Pendidikan Teknik Dan Kejuruan, 14(2), 89. https://doi.org/10.20961/jiptek.v14i2.51789
Son, V. N., Huong, L. T., & Thanh, N. C. (2021). A two-phase plagiarism detection system based on multi-layer lstm networks. IAES International Journal of Artificial Intelligence, 10(3), 636–648. https://doi.org/10.11591/ijai.v10.i3.pp636-648
SPI Pendidikan. (2024). Hasil survei penilaian integritas pendidikan. SPI Pendidikan.
Sugiyono. (2023). Metode Penelitian Kuantitatif, Kualitatif, Dan R&D. Alfabeta.
Yu, S. C., Chen, H. R., & Yang, Y. W. (2024). Development and validation the Problematic ChatGPT Use Scale: a preliminary report. Current Psychology, 43(31), 26080–26092. https://doi.org/10.1007/s12144-024-06259-z
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Naftalia Rise Andi Putri, Silvia Nathania, Neisha Audrella, Rama Dwita, Aviva Leonisa, Pamela Hendra, Rita Markus Idulfilastri

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













