The Use of Big Data Analytics in Detecting Academic Fraud

Firdatul Jannah; Anara Indrany Nanda Ayu Anissa; Wanda Maulida; Novita Novita

doi:10.21532/apfjournal.v7i2.261

Authors

Firdatul Jannah Trilogi University, South Jakarta
Anara Indrany Nanda Ayu Anissa Trilogi University, South Jakarta
Wanda Maulida Trilogi University, South Jakarta
Novita Novita Trilogi University, South Jakarta

DOI:

https://doi.org/10.21532/apfjournal.v7i2.261

Keywords:

Big Data Analytics, Academic Fraud, Students, Higher Education

Abstract

This study aims to find out the effect of using big data analytics on the detection of academic fraud so that it can provide improvements and create significant changes, especially in reducing the level of academic fraud among students. The variables used in this research are big data analytics as the independent variable and academic fraud as the dependent variable. This study uses primary data obtained from ques-tionnaires distributed to Trilogy University students. The sample is 258 students from all study programs at Trilogy University class 2017 - 2020. The data processing and analysis method uses Partial Least Square (PLS). The results of this study indicate that the use of big data analytics has a positive and significant effect on the detection of academic fraud. This shows that universities that use big data analytics are able to detect academic fraud committed by students.

References

Agustini, K. (2017). Inovasi Teknologi dalam Pendidikan melalui Big Data Analytic dan Personalized Learning. Prosiding Seminar Nasional Pendidikan Teknik Informatika (SENAPATI) Ke-8, 0362, 27213.

Akenbor, C. O. and Oghoghomeh, T. (2013). Forensic auditing and financial crime in Nigerian banks: A proactive approach. The Business & Management Review, 4.

Aksa, A. F. (2018). Pencegahan dan Deteksi Kasus Korupsi Pada Sektor Publik Dengan Fraud Triangle. Jurnal Ekonomi, Bisnis, Dan Akuntansi (JEBA), 20.

Alvin, A. D. (2008). No TitleAuditing dan Jasa Assurance. Erlangga.

Briney, K. A. (2019). Data Management Pratices in Academic Library Learning Analytics: A Critial Review. Journal of Librarianship and Scholarly Communication, 7(General Issue), 1–39.

Campbell, J. P., DeBlois, P. B. ., & Oblinger, D. G. (2007). Academic Analytis New Tool fo A New Era. EDUCAUSE Review, 41–57.

Cressy, D. (1953). Teori Fraud Triangle (2nd ed). Salemba Empat.

Darono, A. (2018). Pembelajaran Business Analytics dan Big Data Dalam Pendidikan Ekonomi dan Bisnis.

Efgivia & Givia. (2020). No TitlePemanfaatan Big Data Dalam Penelitian Teknologi Pendidikan. Educate: Jurnal Teknologi Pendidikan, 107–119.

Efgivia, M. G. (2020). Pemanfaatan Big Data Dalam Penelitian Teknologi Pendidikan. Educate: Jurnal Teknologi Pendidikan, 107–119.

Ernawati, S. (2017). Kecurangan Akademik pada Mahasiswa Ditinjau dari Kepercayaan Diri dan Konformitas. 1–15.

Fitriana, A., & Baridwan, Z. (2012). Perilaku Kecurangan Akademik Mahasiswa Akuntansi: Dimensi Fraud Triangle. Jurnal Akuntansi Multiparadigma JAMAL, 242–254.

Ghozali, I., & Latan, H. (2015). Partial Least Squares: Konsep, Teknik, dan Aplikasi Menggunakan Program Smart PLS 3.0 (2nd ed). Universitas Diponegoro.

Hair Jr, J. F., Hult, G., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd Editio). SAGE.

Hartanto, D. (2012). Bimbingan & Konseling Menyontek: Mengungkap Akar Masalah dan SolusinyaTitle. Indeks.

Ali, I. (2021). Peran dan Kontribusi Big Data dalam Pendidikan dan Pelatihan Kepustakawanan. Madika : Media Informasi dan Komunikasi Diklat Kepustakawanan, 5(1), 8–15.

Pramudyastuti, O., Fatimah, A., & Wilujeng, D. (2020). Perilaku Kecurangan Akademik Mahasiswa Akuntansi: Investigasi Dimensi Fraud Diamond. Journal of Economic, Management, Accounting and Technology, 3(2), 147-153. https://doi.org/10.32500/jematech.v3i2.1301.

Purnama, D. (2013). Faktor-faktor yang mempengaruhi kecurangan aka-demik pada mahasiswa. Educational Psychology Journal, 2(1), 13–21.

Siemens, G., & Baker, R. S. J. d. (2012). Learning Analytics and Educational Data Mining: Towards Communication and Collaboration. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, Vancouver British Columbia Canada.

Suryana. (2010). Metode Penelitian: Model Praktis Penelitian Kuantitatif dan Kualitatif. Buku Ajar Perkuliahan UPI.

Varian, H. (2014). Big Data: New Tricks for Economictris. Journal of Economic Perspectives, 28(2): 3-28. https://doi.org/10.1257/jep.28.2.3.

Wibowo, D. H., & Wahyuningrum, E. (2019). Pencegahan Perilaku Kecurangan Akademik: Peran Penalaran Moral dan Konsep Diri Akademik Academic Fraud Prevention. Jurnal Ecopsy, 6(2), 86–90.