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All Journal Jatilima : Jurnal Multimedia Dan Teknologi Informasi TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Journal of Artificial Intelligence and Engineering Applications (JAIEA) QISTINA: Jurnal Multidisiplin Indonesia AR-RUMMAN: Journal of Education and Learning Evaluation
Elsa Sabrina
Universitas Negeri Medan
Religion Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Public Health Other

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Peran Artificial Intelligence (AI) dalam Meningkatkan Kemampuan Berpikir Kritis Siswa Fahmy Syahputra; Elsa Sabrina; Alvin Evraim Situmorang; Marchell Gabriel Manurung; Safira Nazwa Putri; Sarwedi Parhehean Tua
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 6, No 4 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/trilogi.v6i4.13432

Abstract

This study aims to analyze the contribution of artificial intelligence (AI) use in supporting students’ critical thinking skills across the cognitive levels of Bloom’s taxonomy. A descriptive quantitative survey design was employed. Data were collected using a 20-item questionnaire administered via Google Forms to 45 students. Descriptive analysis was conducted by summarizing and reporting the proportion of responses for each Bloom level (remembering, understanding, applying, analyzing, evaluating). The results show that the highest proportion occurs at the understanding level (26.7%), followed by analyzing (22.2%), evaluating (20.0%), applying (17.8%), and remembering (13.3%). These findings indicate that students tend to use AI more to comprehend learning materials and break down information than merely to recall facts. The study concludes that AI can function as a learning partner that supports critical thinking processes—particularly at the understanding and analyzing levels—provided that its use is guided pedagogically to align with instructional goals.
Keamanan Pengenalan Wajah Berbasis Deep Learning: Tinjauan Sistematis Serangan Adversarial dan Strategi Pertahanan (Systematic Literature Review) Fahmy Syahputra; Elsa Sabrina; Andika Sitorus; Khodijah May Nuri Lubis; Frans Jhonatan Saragi; Suci Nurrahma; Novi Novanni Sinaga
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 6, No 4 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/trilogi.v6i4.13424

Abstract

Deep learning–based face recognition is widely adopted due to its strong performance, yet its susceptibility to attacks—particularly adversarial attacks—poses critical risks to the security and reliability of biometric systems. This study presents a Systematic Literature Review (SLR) to synthesize evidence on performance, vulnerabilities, and defense strategies in deep learning–based face recognition. The review follows PRISMA guidelines, including literature retrieval from reputable scholarly sources, deduplication, title/abstract screening, and full-text eligibility assessment based on predefined inclusion and exclusion criteria. Study quality is examined through critical appraisal, and findings are synthesized using thematic analysis, yielding four major themes: (1) model performance and factors influencing accuracy, (2) attack types and their impact on recognition outcomes, (3) defense mechanisms and their effectiveness, and (4) real-world deployment constraints (e.g., illumination, pose, image quality, and identity scale). The synthesis indicates that high accuracy does not necessarily imply high robustness; several defenses (e.g., adversarial training, attack detection, and robust learning) can improve resilience but may introduce trade-offs in computational cost and/or accuracy. This review provides a comparative synthesis and a conceptual model linking accuracy–attacks–defenses, and offers practical recommendations for model selection and security evaluation design. Limitations include heterogeneity in datasets and experimental protocols, inconsistent reporting metrics, and potential publication bias
Performance Evaluation of a Mobile Attendance System Using Dual-Factor Dynamic Qr Code and Gps Geofencing Rosma Siregar; Bagoes Maulana; Muhammad Isnaini; Elsa Sabrina; Harvei Desmon Hutahaean
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2281

Abstract

This study develops and evaluates an Android-based attendance system integrating dual-factor authentication using dynamic QR codes and GPS geofencing to prevent proxy attendance in higher education. The system was developed using the Waterfall model and evaluated through quantitative experiments measuring response time, GPS accuracy drift, and security robustness via Black-Box testing. Results show high efficiency with an average response time below 1.5 seconds. GPS validation achieved an average drift of 4.2 meters outdoors and 12.5 meters indoors, remaining within the 30-meter geofencing threshold. The system successfully rejected unauthorized attempts, including out-of-range scans and fake GPS spoofing. These findings demonstrate that combining dynamic QR codes with GPS validation significantly improves attendance authenticity and system reliability compared to single-factor methods. The study provides empirical evidence of a robust and scalable solution for secure mobile-based attendance systems in higher education.
Co-Authors Abel Frans Sinaga Abel Sinaga Alfi Rahmadhani Alvin Evraim Situmorang Alya Rahmi Andika Sitorus Ariyantika Br Ginting Artiani Zebua Christian Johansen Sihombing Cristina Elseria Rahelta Dheany Angelina Putri Sembiring Diyaul Fikri Erika Togito Siahaan Fadhil Ardiansyah Febrinata Silvianna Br Tarigan Frans Jhonatan Saragi Gali Armando Grace Roni Anuar Lase Hanifah Mardhiyah Harvei Desmon Hutahean Hutahaean, Harvei Desmon Hutri Ami Jauharah Jauharah Joko Hendratmo Khodijah May Nuri Lubis Laili Tanzila Loveyanni Marito Benedikta Gorat M Fajar Sahendra Chan M Farid Al Farishi M Raflie Alhadi Marchell Gabriel Manurung Marta Aulia Simangunsong Martino Bijeloys Siagian Matius Irvan Sarumaha Maulana, Bagoes Muhammad Fakhri Lubis Muhammad Fattah Muhammad Isnaini Muhammad Munawwar Muhammad Naufal Ilham Muhammad Zaki Ulwi Nadila Ramadani Novi Novanni Sinaga Rabiatul Adwiyah Reyvaldo Gilbert Sitinjak Rifki Fali Rosma Siregar Safira Nazwa Putri Samuel Jonathan Pangaribuan Sandha Calista Simanjorang Sarwedi Parhehean Tua Steven Eben Ezer Lase Suci Nurrahma Syahputra, Fahmy Teguh Arif Mediansyah Teguh Mediansyah Tirta Yasa Agung Barus Yohanes Febrian Silalahi Yosa Perangin Angin Zulkaidah Harahap