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All Journal JSAI (Journal Scientific and Applied Informatics) Dinasti International Journal of Economics, Finance & Accounting (DIJEFA)
Uus Rusmawan
Universitas Dian Nusantara, Jakarta, Indonesia
Computer Science & IT Economics, Econometrics & Finance

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Model Deteksi Kecurangan Ujian Menggunakan Pendekatan SURF-CNN Berdasarkan Data Citra Digital Uus Rusmawan; Imam Mulya; Muchamad Sandy; Abd Rahman; Pupu Ramadhan
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9383

Abstract

Detecting cheating during examinations was one of the main challenges in maintaining academic integrity in educational environments. This study developed an approach to detect cheating behavior by utilizing a combination of Speeded Up Robust Features (SURF) and Convolutional Neural Networks (CNN) based on digital images. The novelty of this research lay in the application of the SURF method as a feature extraction technique to detect suspicious objects and movements, which were then further analyzed using CNN for student behavior classification. The main objective of this study was to design, develop, and test a digital image–based exam cheating detection model capable of recognizing various types of behavior, such as looking around, glancing suspiciously, as well as non-cheating behaviors like focusing and boredom. The dataset used in this study consisted of 1,200 digital images categorized into six different behavior classes. The dataset was divided into three parts: 70% for training (840 images), 10% for validation (120 images), and 20% for testing (240 images). The experimental results showed that the SURF-CNN approach achieved better performance compared to the standard CNN. The SURF-CNN model achieved an accuracy of 91.80% on training data, 88.65% on validation, and 86.15% on testing, while CNN only achieved 88.20% on training, 85.25% on validation, and 83.15% on testing
Study of the Role of Digital Literacy in Mitigating the Spread of Online Gambling as a Popular Cyber Crime in Indonesia Henri Septanto; Uus Rusmawan; Boy Yuliadi; Ari Hidayatullah
Dinasti International Journal of Economics, Finance & Accounting Vol. 5 No. 5 (2024): Dinasti International Journal of Economics, Finance & Accounting (November - De
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v5i5.3426

Abstract

The spread of online gambling as a cyber crime has become a major problem in Indonesia. This type of cyber crime has a huge influence on various levels of society, both from a social and economic perspective. This research aims to examine the role of digital literacy in mitigating the spread of online gambling using a literature study approach. This study examines the definition and components of digital literacy and their impact in dealing with the risks associated with online gambling, which is now one of the most popular types of cyber crime in Indonesia. Through a literature review, this article explores existing theory and data on digital literacy and its effectiveness in increasing public awareness and protecting individuals from the risks associated with online gambling. The findings from this research indicate that digital literacy plays a key role in equipping society with the knowledge and skills necessary to recognize the dangers and impacts of online gambling, while also identifying several gaps in the literature that require further attention. The conclusion of this article emphasizes the importance of integrating digital literacy in mitigation strategies and offers recommendations for improving digital literacy programs to combat the spread of online gambling in Indonesia.
Co-Authors Abd Rahman Ari Hidayatullah Boy Yuliadi Henri Septanto Imam Mulya Muchamad Sandy Pupu Ramadhan