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SABRINA, ELSA
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Rancang Bangun Sistem Absensi Otomatis Berbasis Pengenalan Wajah Menggunakan Model CNN Pretrained pada Platform Web Armando, Gali; Simangunsong, Marta Aulia; Mediansyah, Teguh Arif; Harahap, Zulkaidah; Rahelta, Cristina Elseria; Hutahean, Harvei Desmon; Syahputra, Fahmy; Sabrina, Elsa
QISTINA: Jurnal Multidisiplin Indonesia Vol 4, No 2 (2025): December 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v4i2.7555

Abstract

Conventional attendance methods often lead to queues, time inefficiency, and potential violation of health protocols, necessitating a fast, non-contact, and real-time attendance recording system. This research aims to design and implement a web-based attendance system as a local prototype using face recognition biometrics. The system was developed using Python with the Flask Framework and OpenCV. The core face recognition process combines Dlib's Pretrained CNN model for 128-dimensional feature vector extraction (face embedding) and the K-NN method for classification based on Euclidean Distance calculation. Testing results indicate that the system successfully performs accurate and real-time facial identification. The system is capable of automatically logging attendance times, providing audio feedback, and storing the attendance data recapitulation in an Excel (.xlsx) file. Thus, this system provides an effective and efficient non-contact attendance solution.
Systematic Literatur Riview Penerapan Logika Fuzzy pada Sistem Internet of Things Syahputra, Fahmy; Sabrina, Elsa; Ulwi, Muhammad Zaki; Fikri, Diyaul; Lubis, Muhammad Fakhri; Sembiring, Dheany Angelina Putri; Siahaan, Erika Togito
QISTINA: Jurnal Multidisiplin Indonesia Vol 4, No 2 (2025): December 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v4i2.7528

Abstract

Penelitian ini melakukan Systematic Literature Review (SLR) dan analisis bibliometrik untuk memetakan perkembangan penelitian mengenai penerapan Fuzzy Logic pada sistem Internet of Things (IoT) dalam periode 2020–2025. Sebanyak 200 artikel teridentifikasi melalui pencarian terstruktur menggunakan kata kunci “Fuzzy Logic” dan “Internet of Things (IoT)”, kemudian diseleksi berdasarkan kriteria inklusi dan eksklusi hingga menghasilkan 15 publikasi utama dengan sitasi tertinggi. Analisis tren menunjukkan dua periode puncak produktivitas penelitian, yaitu tahun 2020 dan 2024, masing-masing dengan 41 publikasi. Distribusi sitasi memperlihatkan bahwa artikel yang terbit pada tahun 2020, 2021, dan 2023 memiliki dampak akademik terbesar. Hasil bibliometrik mengungkapkan bahwa tema dominan meliputi pengembangan fuzzy logic controller, efisiensi energi, optimasi rute dan jaringan, keamanan perangkat IoT, serta implementasi pada sektor pertanian, kesehatan, dan industri. Visualisasi jejaring kata kunci (co-word) menunjukkan adanya beberapa kluster tematik yang saling terhubung dan bersifat multidisipliner. Temuan ini memberikan gambaran komprehensif mengenai lanskap penelitian terkini, sekaligus mengidentifikasi peluang riset lanjutan pada integrasi Fuzzy Logic dan IoT di masa mendatang.
Dampak Positif dan Negatif Penggunaan Artificial Intelligence terhadap Kecerdasan Intelektual Mahasiswa Siagian, Martino Bijeloys; Sitinjak, Reyvaldo Gilbert; Sihombing, Christian Johansen; Pangaribuan, Samuel Jonathan; Sabrina, Elsa; Syahputra, Fahmy
QISTINA: Jurnal Multidisiplin Indonesia Vol 4, No 2 (2025): December 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v4i2.7556

Abstract

Perkembangan teknologi Artificial Intelligence (AI) telah membawa transformasi signifikan dalam dunia pendidikan tinggi, khususnya dalam proses pembelajaran mahasiswa. Penelitian ini bertujuan untuk mengkaji secara komprehensif dampak positif dan negatif penggunaan AI terhadap kecerdasan intelektual mahasiswa melalui tinjauan literatur sistematis. Metode yang digunakan adalah literature review dengan menganalisis berbagai jurnal ilmiah, artikel penelitian, dan publikasi terkait penggunaan AI dalam pendidikan tinggi periode 2020-2025. Hasil kajian menunjukkan bahwa penggunaan AI memberikan dampak positif yang signifikan, meliputi: peningkatan efisiensi pembelajaran, kemudahan akses informasi, personalisasi materi pembelajaran, pengembangan kreativitas, dan peningkatan pemahaman konsep yang kompleks. AI juga mendukung pembelajaran mandiri dan memberikan umpan balik real-time kepada mahasiswa. Namun, kajian ini juga mengidentifikasi berbagai dampak negatif, antara lain: penurunan kemampuan berpikir kritis, ketergantungan berlebihan pada teknologi, potensi plagiarisme dan pelanggaran integritas akademik, pemahaman yang dangkal terhadap materi, serta kekhawatiran terkait keamanan dan privasi data. Temuan menunjukkan bahwa penggunaan AI, khususnya ChatGPT, berpengaruh terhadap kecerdasan intelektual mahasiswa dengan kontribusi berkisar 57-75% terhadap peningkatan produktivitas akademik. Penelitian ini merekomendasikan perlunya strategi penggunaan AI yang bijak dan terarah, penguatan kebijakan institusi pendidikan, pelatihan literasi digital bagi mahasiswa dan dosen, serta pengembangan sistem evaluasi yang dapat mengidentifikasi orisinalitas karya mahasiswa. Dengan pendekatan yang seimbang, AI dapat dioptimalkan sebagai alat bantu pembelajaran yang meningkatkan kecerdasan intelektual tanpa mengorbankan kemampuan berpikir kritis dan kreativitas mahasiswa
Peran Artificial Intelligence (AI) dalam Meningkatkan Kemampuan Berpikir Kritis Siswa Syahputra, Fahmy; Sabrina, Elsa; Situmorang, Alvin Evraim; Manurung, Marchell Gabriel; Putri, Safira Nazwa; Parhehean Tua, Sarwedi
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) 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
Tinjauan Literatur Sistematis (2019–2025) Kinerja Decision Tree dan Neural Network (Deep Learning) serta Perbandingannya dengan Naive Bayes dan SVM Syahputra, Fahmy; Sabrina, Elsa; Br Tarigan, Febrinata Silvianna; Sarumaha, Matius Irvan; Rahmadhani, Alfi; Simanjorang, Sandha Calista; Gorat, Loveyanni Marito Benedikta
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.v6i4.13429

Abstract

This study presents a Systematic Literature Review (2019–2025) comparing the performance of Decision Tree and Neural Network (Deep Learning) models, alongside their relative performance against Naive Bayes and Support Vector Machine (SVM). The review synthesizes empirical findings across multiple application domains—including healthcare, education, industry, and finance—focusing on commonly reported classification metrics such as accuracy, precision, recall, and F1-score. The synthesis indicates that Decision Trees are frequently preferred for structured/tabular data due to their high interpretability and transparent decision rules, which are valuable for accountable decision-making. In contrast, Neural Networks/Deep Learning tend to outperform on unstructured data (e.g., medical images and text) and complex non-linear patterns, albeit often with reduced explainability. In several studies, Naive Bayes remains competitive as a lightweight baseline, while SVM continues to be effective for high-dimensional feature spaces and specific classification settings. Overall, the review highlights that algorithm selection should be driven by data characteristics, problem complexity, interpretability requirements, and computational constraints, since no single algorithm consistently dominates across all scenarios.
Dampak AI Generatif (LLMS) terhadap Keterampilan Menulis dan Integritas Akademik: Tinjauan Literatur Sistematis Syahputra, Fahmy; Sabrina, Elsa; Barus, Tirta Yasa Agung; Farishi, M Farid Al; Adwiyah, Rabiatul; Ramadani, Nadila; Jauharah, Jauharah
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.v6i4.13431

Abstract

This study aims to examine the impact of Generative AI (LLMs), such as ChatGPT, on students' writing skills and academic integrity through a Systematic Literature Review (SLR) of 15 relevant articles. The synthesis results reveal a significant duality effect, creating a dilemma between efficiency and quality. On one hand, LLMs are proven to be effective assistive co-pilots, which clearly enhance the technical efficiency of writing, accelerate the research workflow, and improve text cohesion and precision. However, this convenience triggers a substance quality crisis because students experience cognitive over-reliance, leading to Academic Deskilling the loss of the ability to independently practice critical reasoning and idea synthesis. This dependency is exacerbated by blind reliance on AI output and vulnerability to hallucinations that threaten the originality of the work. The consequence is a shift in the form of misconduct to the sophisticated practice of prompt engineering. To address these challenges, the literature emphasizes the necessity of pedagogical redesign and assessment redesign, which must focus on establishing ethics that ensure full transparency and accountability from students, and designing tasks that demand personal synthesis and reflective thinking.
Co-Authors Abdurrahman, Umar Adwiyah, Rabiatul Afriansyah Pulungan, Wira Agustianingsih, Tri Al Husna, Saiba Alhadi, M Raflie Alhadi, M.Raflie Amalia, Mazaya Amanda, Nayla Ambiyar, Ambiyar Amirhud Dalimunthe Ananda, Muhammad Rendi Andini, Syasya Angelina Putri Sembiring, Dheany Anggraini, Ade Annisa, Selly Ardiansyah, Muhammad Fadhill Armando, Gali Asisah, Fatma Asmara, Tri Aulia Simangunsong, Marta Barus, Michael Steven F. Barus, Tirta Yasa Agung Br Tarigan, Febrinata Silvianna Chan, M Fajar Sahendra Dewi, Yasmin Aulia Elsadin, Ratih Tri Ernawati Ernawati Fakhri Lubis, Muhammad Farishi, M Farid Al Fikri, Diyaul Fitri, Destiana Gaol, Liska Yuni Br Lumban Ginting, Leo Elfrata Gorat, Loveyanni Marito Benedikta Harahap, Ihsan Heldi Harahap, Zulkaidah Hasan Maksum Hawari, Mhd Fadhlan Hawari, Muhammad Fadhlan Hendra Hidayat Hendratmo, Joko Heskia, Carlo Hutagalung, Namira Rahmadina Hutahean, Harvei Desmon Hutajulu, Olnes Yosefa Hutauruk, Karel Rolian Ilham, Muhammad Naufal Ingtyas , Fatma Tresno Ingtyas, Fatma Tresno Irfanny, Riza Jauharah, Jauharah Khojir Lubis, Khodijah May Nuri Lubis, Muhammad Fakhri Manurung, Marchell Gabriel Manurung, Ricardo Matondang, Ishaq Maya Sari Mediansyah, Teguh Arif Mendoza, Muhammad Dominique Muhammad Anwar Muhammad Ashari Munawwar, Muhammad Nababan, Leoni Try Oxana Nainggolan, Sindi Judiati Nasution, Aulia Rivansy Nasution, Henny Puspa Hendrani Nasution, Romadon Nasution, Willy Oktaviano Yehezkiel Naufal Ilham, Muhammad Nurrahma, Suci Pangaribuan, Samuel Jonathan Pardede, Rachel Christa Masniari Parhehean Tua, Sarwedi Perangin-Angin, Yosa Steven Perdana, Nugraha Aditama Putra Permata, Sahly Na’ila Pohan, Ahmad Rizal Padana Pradana, Raflie Sultan Pratama, Saras Putri, Desly Dwiyana Putri, Safira Nazwa Rahelta, Christina Elseria Rahelta, Cristina Elseria Rahmadhani, Alfi Ramadani, Nadila Ramadhani Pasi, Anggie Rambe, Rizkina Ramadhani Remon Lapisa Reni Rahmadani Rosma Siregar Saari, Erni Marlina Safira, Dira Safitri, Nisa Salsabila, Azura Sakhi Saragi, Frans Jhonatan Sari, Ressy Dwitias Sarumaha, Matius Irvan Sembiring, Dheany Angelina Putri Shafira, Amanda Shahdana, Shahdana Siagian, Martino Bijeloys Siahaan, Erika Togito Siboro, Sari Agustina Siburian, Joy Sihombing, Christian Johansen silaban, Silpia Silalahi, Yohanes Febrian Silitonga, Alfredo Alpansa Simangunsong, Marta Aulia Simanjorang, Sandha Calista Simanjuntak, Jeannete Claudia Stefany Simanjuntak, Nadia Costarika Simbolon, Angga Baginda Sinaga, Abel Frans Sinaga, Novi Novanni Sinaga, Nur Intan Sirait, Steven Sisrayanti Sitepu, Filza Kirani Br Sitepu, Jeremia Sitinjak, Reyvaldo Gilbert Sitorus, Andika Situmorang, Alvin Evraim Situmorang, Gaudensius J.A Syafaat, Muhammad Yoghi Syah, Razha Jamsik Syahbila, Azzahra Syahputra, Fahmy Tarigan, Gabriel Frandika Tarigan, Ray Rivandi Togito Siahaan, Erika Tresno Ingtyas, Fatma Ulwi, Muhammad Zaki Waskito Wulandari, Ririn Fairuz Wulansari, Rizky Ema Yeka Hendriyani Yunansyah Siregar, Wal Zai, Frans Pratamarifai Doya Zaki Ulwi, Muhammad Zulfa, Zaid Zaidan