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All Journal Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Jurnal Sistem Cerdas BERNAS: Jurnal Pengabdian Kepada Masyarakat REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Intellect : Indonesian Journal of Learning and Technological Innovation AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi
Elviani, Ulva
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Face Recognition-Based Surveillance System in Mining Industry Hidayat, Fadhil; Elviani, Ulva; Agil Alunjati, Figo; Furqan Alfuady, Muhammad
Jurnal Sistem Cerdas Vol. 7 No. 2 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i2.434

Abstract

Access control in mining construction areas is crucial for the operations of mining companies. This access control functions to secure and restrict unauthorized parties from mining activities. Violations of access rights in the mining industry result in significant losses for companies. This access control can also be utilized to record employee attendance, serving as input for the contract work system commonly applied in mining areas. Closed-circuit television (CCTV) is commonly used to monitor activities; however, the current use of CCTV still requires direct human observation, which may result in important events being overlooked. The functionality of these CCTVs can be enhanced to manage access rights and monitor employee attendance to support company operations through face recognition methods. In this study, a system design was carried out through a research approach to determine the technology to be used in the system. The development of a face recognition-based access control system was conducted based on system engineering methodology. This development includes system requirements analysis, the design of a face recognition-based access control system, implementation, and system performance evaluation. The resulting system was tested through simulation processes based on actual field conditions, and the test results showed that the system could recognize faces registered in the dataset and identify subjects not registered in the dataset with an accuracy of 60%, precision of 96%, recall of 58%, and an F-score of 72%. Additionally, the system was able to connect to a database to store face recognition results and then display them on an employee attendance monitoring dashboard. The delay between the face recognition system and actual time ranged from 2-4 seconds and was still tolerable.
AI-Driven Learning Analytics for Self-Regulated and Metacognitive Learning: A Systematic Review Romdhoni, Rhezwan Dhaifullah; Arrasyid, Rafli; Widodo, Suprih; Elviani, Ulva
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1657

Abstract

Artificial intelligence (AI) and learning analytics are increasingly integrated into educational systems, yet their impact on self‑regulated learning (SRL) and metacognition remains not fully understood. This systematic review synthesizes findings from 34 empirical and review studies on AI‑driven learning analytics in formal education, focusing on their effects on SRL, metacognition, motivation, and academic performance. Following PRISMA guidelines, studies were identified through searches in Scopus, Web of Science, ERIC, and Google Scholar for articles published between 2020 and 2025, using keywords related to AI, learning analytics, SRL, and metacognition. Studies were included if they used AI‑based analytical or adaptive systems, standardized SRL or metacognitive measures, and pre–post or comparison data. Results show that AI‑based tools such as predictive models, intelligent tutoring systems, adaptive platforms, learning dashboards, and generative or conversational AI support goal setting, monitoring, strategy adjustment, and reflective evaluation through feedback, progress visualization, and personalized recommendations. Most studies report improvements in SRL strategies, metacognitive awareness, motivation, engagement, and learning outcomes, though effects vary across research design quality, educational levels, and subject areas. However, several challenges persist, including infrastructural limitations, limited teacher readiness, data privacy and ethical issues, algorithmic bias, and potential overreliance on AI that may weaken learners’ independent strategic thinking. Overall, AI‑driven learning analytics hold substantial potential to enhance SRL and metacognition when integrated within coherent pedagogical frameworks and supported by institutional policies promoting transparency, equity, and human agency. Abstrak Kecerdasan buatan (AI) dan learning analytics semakin meluas dalam sistem pendidikan, namun dampaknya terhadap self‑regulated learning (SRL) dan metakognisi masih belum sepenuhnya dipahami. Tinjauan sistematis ini mensintesis temuan dari 34 studi empiris dan tinjauan pustaka mengenai penerapan AI‑driven learning analytics di pendidikan formal, berfokus pada pengaruhnya terhadap SRL, metakognisi, motivasi, dan kinerja akademik. Dengan mengikuti pedoman PRISMA, artikel dipilih melalui pencarian di Scopus, Web of Science, ERIC, dan Google Scholar untuk periode 2020–2025 menggunakan kata kunci terkait AI, learning analytics, SRL, dan metakognisi. Studi disertakan jika menggunakan sistem analitik atau adaptif berbasis AI dengan instrumen terstandar dan data perbandingan pre–post. Hasil menunjukkan bahwa alat berbasis AI seperti model prediktif, sistem tutor cerdas, platform adaptif, dashboard pembelajaran, serta AI generatif atau konversasional mendukung penetapan tujuan, pemantauan, adaptasi strategi, dan refleksi melalui umpan balik, visualisasi kemajuan, dan rekomendasi otomatis. Sebagian besar studi melaporkan peningkatan strategi SRL, kesadaran metakognitif, motivasi, keterlibatan, dan hasil belajar, meski efek berbeda bergantung pada desain penelitian, jenjang pendidikan, dan bidang studi. Namun, tantangan tetap muncul, termasuk keterbatasan infrastruktur, kesiapan guru, privasi data, bias algoritmik, serta potensi ketergantungan berlebih pada AI yang dapat melemahkan kemandirian berpikir strategis. Secara keseluruhan, AI‑driven learning analytics berpotensi memperkuat SRL dan metakognisi bila diintegrasikan dalam kerangka pedagogis yang jelas dan didukung kebijakan institusional yang menegakkan transparansi, keadilan, dan agensi manusia.
Penyalahgunaan Deepfake dan Tantangan Tata Kelola AI: Tinjauan Literatur Sistematis Huwaida, Febviana Sulthanah; Widodo, Suprih; Elviani, Ulva
Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Vol. 5 No. 6 (2025): EduTIK : Desember 2025
Publisher : Jurusan PTIK Universitas Negeri Manado

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Abstract

Perkembangan teknologi deepfake menghadirkan tantangan baru dalam ekosistem digital, terutama terkait penyebaran disinformasi, penipuan identitas, dan eksploitasi visual yang berdampak pada keamanan siber serta perlindungan hak individu. Penelitian ini bertujuan untuk memetakan karakteristik penyalahgunaan deepfake, menilai kesiapan tata kelola kecerdasan buatan (AI governance), serta mengidentifikasi arah pengembangan strategi mitigasi yang efektif. Metode Systematic Literature Review (SLR) digunakan dengan mengacu pada protokol PRISMA, melibatkan proses seleksi ketat terhadap 20 artikel yang diperoleh dari database Scopus menggunakan kriteria inklusi–eksklusi yang terstandar. Hasil kajian menunjukkan tiga temuan utama. Pertama, penyalahgunaan deepfake meningkat secara signifikan di ranah media sosial dan keamanan siber, dengan kelompok rentan menunjukkan tingkat deteksi yang rendah. Kedua, tata kelola AI yang ada masih bersifat reaktif dan belum mampu mengikuti dinamika perkembangan teknologi. Ketiga, terdapat kesenjangan antara performa teknologi deteksi deepfake di lingkungan terkontrol dan efektivitasnya pada konteks dunia nyata. Kajian ini menyimpulkan bahwa mitigasi deepfake memerlukan pendekatan multidimensional yang mengintegrasikan inovasi teknologi, reformasi kebijakan, literasi digital yang inklusif, serta perlindungan korban. Temuan ini membuka peluang bagi pengembangan kebijakan yang lebih adaptif dan aplikatif dalam menciptakan ekosistem digital yang aman dan akuntabel.  
Analisis Komparatif Metode Bag Of Words, TF-IDF, dan Transformer pada Sistem Penilaian Esai Otomatis Berbasis Kecerdasan Buatan Agustin, Amara Seviany; Widodo, Suprih; Elviani, Ulva; Sari, Ayu Permata; Barri, Muhamad Akda Fathul
AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan Vol. 3 No. 2 (2025): Jurnal AI dan SPK : Jurnal Artificial Inteligent dan Sistem Penunjang Keputusan
Publisher : CV. Shofanah Media Berkah

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Abstract

Penilaian esai secara manual menghadapi kendala inkonsistensi, subjektivitas, dan keterbatasan waktu, terutama pada pembelajaran berskala besar. Penelitian ini membandingkan tiga pendekatan representasi teks pada sistem penilaian esai otomatis berbasis kecerdasan buatan, yaitu Bag of Words (BoW), Term Frequency–Inverse Document Frequency (TF-IDF), dan Transformer (IndoBERT). Dataset yang digunakan berasal dari Kaggle Learning Agency Lab Automated Essay Scoring 2.0 yang terdiri atas 17.207 esai berbahasa Inggris dan diterjemahkan ke bahasa Indonesia menggunakan model Helsinki-NLP opus-mt-en-id. Tahap prapemrosesan meliputi case folding, pembersihan teks, penghapusan stopword, dan stemming menggunakan pustaka Sastrawi. Metode BoW dan TF-IDF dipadukan dengan Support Vector Regression, sedangkan pendekatan Transformer menggunakan fine-tuning IndoBERT. Evaluasi dilakukan menggunakan metrik Quadratic Weighted Kappa (QWK). Hasil eksperimen menunjukkan bahwa IndoBERT mencapai performa tertinggi dengan nilai QWK sebesar 0,7842, diikuti TF-IDF sebesar 0,6521 dan BoW sebesar 0,6103. Meskipun Transformer unggul dari sisi akurasi, metode klasik tetap relevan untuk implementasi dengan keterbatasan sumber daya komputasi karena efisiensi waktu dan kompleksitas yang lebih rendah. Temuan ini menegaskan pentingnya pemilihan metode penilaian otomatis yang disesuaikan dengan konteks kebutuhan dan infrastruktur pendidikan.
KutaBaca: Developing and Implementation of an Offline Digital Library System to Enhance Literacy in the Low-Connectivity Environment of Wiyata Tech Village Purwakarta Venica, Liptia; Sodikin, Reisa Aulia; Herlina, Nina; Elviani, Ulva; Zahron, Aulia Aufa; Kurniawan, Muhammad Randy; Nugraha, Ariel Dwika; Putri, Dewi Indriati Hadi
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 7, No 1 (2026): Reka Elkomika
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v7i1.60-69

Abstract

Achieving Quality Education (Sustainable Development Goals, or SDGs, Point 4) remains a significant challenge in rural areas characterized by low digital infrastructure. Specifically, Kutamanah Village in Purwakarta faces critical literacy issues, with its primary school's literacy rate tragically categorized as ‘red,’ compounded by a low regional Quality Education Index score of 46.70. This research aims to address this digital and literacy gap through the systematic development and implementation of KutaBaca, an Offline Digital Library system. Utilizing a Research and Development (R&D) methodology based on the Software Development Life Cycle (SDLC) model, the system was designed with a local server and an internal wireless network, allowing students and teachers to access a vast collection of e-books and learning modules without relying on an external internet connection. Evaluation focused on rigorous Functional Testing and a System Usability Scale (SUS) assessment involving 30 students and 7 teachers. The results demonstrate a 100% functional success rate and an overall average SUS score of 83.1 ('Excellent'). This confirms that KutaBaca is a reliable, user-friendly, and replicable technological innovation, effectively increasing access to information and serving as a sustainable solution to boost literacy and support SDGs 4, 10, and 17 in low-connectivity regions.
Peningkatan Literasi Melalui Workshop Pemanfaatan Perpustakaan Digital Offline di SDN 1 Kutamanah Purwakarta Putri, Dewi Indriati Hadi; Venica, Liptia; Herlina, Nina; Sodikin, Reisa Aulia; Elviani, Ulva; Zahron, Aulia Aufa; Kurniawan, Muhammad Randy; Nugraha, Ariel Dwika
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v7i2.16275

Abstract

Keterbatasan infrastruktur digital masih menjadi kendala utama pemerataan akses pendidikan di daerah pedesaan Indonesia. Salah satunya dialami oleh Desa Kutamanah, Kecamatan Sukasari, Kabupaten Purwakarta, yang memiliki skor Indeks SDGs Desa pada aspek Pendidikan Berkualitas (SDGs 4) di bawah 50. Kondisi minimnya konektivitas internet menjadi salah satu penyebab rendahnya literasi membaca dan kemampuan pemanfaatan teknologi, khususnya di lingkungan sekolah dasar. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan literasi digital serta keterampilan teknologi melalui implementasi Workshop Pemanfaatan Teknologi Perpustakaan Digital Offline KutaBaca. Metode yang digunakan adalah pendekatan Participatory Action Research dengan melibatkan guru dan siswa secara aktif dalam tahapan perencanaan, pelatihan, observasi, dan evaluasi dengan instrumen pre-test dan post. Sebanyak 21 peserta mengikuti kegiatan ini. Hasil evaluasi menunjukkan peningkatan signifikan pada pemahaman konsep perpustakaan digital, dari skor rata-rata 2,6 (rendah) pada pre-test menjadi 4,7 (sangat baik) pada post-test. Selain itu, tingkat keterampilan digital meningkat dari skala 2-3 menjadi 4-5, sedangkan tingkat kepuasan peserta mencapai 4,62 (kategori sangat puas). Implementasi sistem perpustakaan digital offline KutaBaca terbukti efektif mendukung proses pembelajaran dan memperkuat budaya literasi digital di sekolah pedesaan. Kegiatan ini menghasilkan model pengabdian berbasis teknologi yang berkelanjutan dan dapat direplikasi di daerah lain dengan keterbatasan akses internet.
Efektivitas Efektivitas Sistem Bimbingan Cerdas, Pembelajaran Adaptif, dan Teknologi Berbasis Kecerdasan Buatan dalam Pembelajaran Matematika: Tinjauan Komprehensif dari Tinjauan Sistematis dan Meta-Analisis Ferdian Yunizar; Widodo, Suprih; Elviani, Ulva
Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Vol 10 No 2 (2026)
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/2q9whh74

Abstract

This umbrella review synthesizes evidence from systematic reviews and meta-analyses on the effectiveness of intelligent tutoring systems, adaptive learning platforms, and artificial intelligence-based technologies in mathematics learning. A semi-automated search was conducted on 18 December 2025 using an indexed academic search engine, complemented by forward-backward citation chasing. Eligible reviews were screened and appraised using a proxy version of AMSTAR 2 focused on critical domains. Across the included reviews, technology-enhanced and adaptive interventions generally showed small-to-moderate positive effects on mathematics achievement, with more consistent benefits when feedback was immediate, personalization was meaningful, and implementation was supported by teachers and well-aligned tasks. Evidence for non-cognitive outcomes (e.g., motivation, self-efficacy, engagement) was positive but less consistently reported. Heterogeneity across contexts and substantial overlap among primary studies remain major challenges. The review highlights implementation conditions, recurring moderators, and priority gaps to strengthen future research and reporting in mathematics education.
Co-Authors Agil Alunjati, Figo Agustin, Amara Seviany Arrasyid, Rafli Ayu Permata Sari Barri, Muhamad Akda Fathul Ferdian Yunizar Furqan Alfuady, Muhammad Hadi Putri, Dewi Indriati Hidayat, Fadhil Huwaida, Febviana Sulthanah Kurniawan, Muhammad Randy Liptia Venica Nina Herlina Nugraha, Ariel Dwika Romdhoni, Rhezwan Dhaifullah Sodikin, Reisa Aulia Suprih Widodo, Suprih Zahron, Aulia Aufa