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All Journal GOVERNANCE: Jurnal Ilmiah Kajian Politik Lokal dan Pembangunan TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora QISTINA: Jurnal Multidisiplin Indonesia
Lubis, Khodijah May Nuri
Unknown Affiliation
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Public Health Social Sciences Other

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Interactive Teaching Media Design for Past Tense Lesson Material Using VB.NET Syahputra, Fahmy; Putri, Tansa Trisna Astono; Lubis, Khodijah May Nuri; Rahmadhani, Alfi; Fattah, M
QISTINA: Jurnal Multidisiplin Indonesia Vol 3, No 2 (2024): December 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v3i2.4228

Abstract

The development of information technology has influenced the use of various types of media, as a tool in the learning process. So teachers are expected to be able to use these tools or equipment effectively classroom learning. In this article, we design teaching media or applications for English subjects. This teaching media is designed using the Microsoft Visual Studio 2022/VB.Net programming language with Past Tense subject matter. The aim of this teaching media design is to increase students' understanding through a visual and interactive approach. This application provides a menu including simple past tense, past continuous tense, past perfect tense, past perfect continuous tense, and is equipped with quiz questions. With this, it is hoped that students will be more involved in the learning process so that they can master the use of past tense effectively and have fun.
MENGURAI PERMASALAHAN SISTEM PEMILU DI INDONESIA DAN DAMPAKNYA TERHADAP DEMOKRASI Barus, Tirta Yasa Agung; Adwiyah, Rabiatul; Lubis, Khodijah May Nuri; Rahma, Suci Nur; Faturrahman, M.Nadhif
GOVERNANCE: Jurnal Ilmiah Kajian Politik Lokal dan Pembangunan Vol. 11 No. 2 (2024): 2024 Desember
Publisher : Lembaga Kajian Ilmu Sosial dan Politik (LKISPOL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56015/gjikplp.v11i2.318

Abstract

General elections in Indonesia are an important mechanism in the democratic process that aims to elect people's representatives and government leaders. However, the electoral system in Indonesia faces various problems that can threaten the quality of democracy. These problems include the practice of money politics, vote manipulation, and lack of transparency in the election process. In addition, the existence of political intervention and bureaucracy that are not neutral are also serious challenges. The impact of these problems on democracy is very significant, including declining public trust in democratic institutions, weakening public political participation, and hampering the process of forming an accountable and responsive government. Therefore, a comprehensive electoral system reform is needed to strengthen democracy in Indonesia.
Keamanan Pengenalan Wajah Berbasis Deep Learning: Tinjauan Sistematis Serangan Adversarial dan Strategi Pertahanan (Systematic Literature Review) Syahputra, Fahmy; Sabrina, Elsa; Sitorus, Andika; Lubis, Khodijah May Nuri; Saragi, Frans Jhonatan; Nurrahma, Suci; Sinaga, Novi Novanni
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
Co-Authors Adwiyah, Rabiatul Barus, Tirta Yasa Agung Fattah, M Faturrahman, M.Nadhif Nurrahma, Suci Putri, Tansa Trisna Astono Rahma, Suci Nur Rahmadhani, Alfi SABRINA, ELSA Saragi, Frans Jhonatan Sinaga, Novi Novanni Sitorus, Andika Syahputra, Fahmy