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All Journal Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sistem Cerdas Jurnal Pendidikan Teknologi Informasi dan Vokasional Intellect : Indonesian Journal of Learning and Technological Innovation TOFEDU: The Future of Education Journal AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Sistem Informasi Karya Anak Bangsa Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi
Elviani, Ulva
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Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics 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.  
Bibliometric Study of TVET and Industry Synergies in the Digital Era on Global Research Direction and Strategy Rahmatya, Aura Salsabillah; Widodo, Suprih; Elviani, Ulva
Jurnal Pendidikan Teknologi Informasi dan Vokasional Vol 7, No 2 (2025): Jurnal Pendidikan Teknologi Informasi dan Vokasional
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/%x

Abstract

This study aims to assess the direction and strategy of global research related to the synergy between vocational education and training (TVET) and industrial needs in the digital era through a bibliometric approach. The analysis was conducted on 500 scientific documents obtained from the Scopus database using VOSviewer and Biblioshiny software. The analysis showed that keywords such as higher education, vocational education, workplace learning, innovation, employability, and industry 4.0 dominated the scientific discourse, signalling the important role of TVET in building employability skills based on digital industry needs. The thematic visualisation identified four main clusters in the research: (1) education and training, (2) digitalisation and innovation, (3) outcome orientation such as entrepreneurship and employability, and (4) sustainable development and well-being. Geographically, countries such as Germany, Australia, Malaysia, China, Indonesia, South Africa, and Nigeria emerged as major contributors with varied research focuses. Highlighted global strategies include revitalising TVET curricula, strengthening, triple helix collaboration (academic, industry, government), enhancing employability skills through work-based learning approaches, and digitalising learning processes. The findings provide a useful conceptual mapping for stakeholders in developing adaptive, collaborative, and sustainable vocational education policies and practies in the digital era.
Efektivitas Media Digital Gemas dalam Meningkatkan Pemahaman Memilah Sampah Anak Usia 5-6 Tahun Ardiyanti, Dhea; Elviani, Ulva; Putri, Hafiziani Eka; Jayadinata, Asep Kurnia; Rahmatillah, Diniah; Sahidah, Lala Nabila Azkia; Ariffin, Meylani Nur; Hopipah, Nurul; Mahardita, Rere Aulia
Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini Vol. 9 No. 6 (2025)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/obsesi.v9i6.7739

Abstract

Permasalahan sampah terus meningkat di Indonesia menunjukkan perlunya edukasi lingkungan sejak usia dini. Penelitian ini bertujuan menguji efektivitas media digital GEMAS (Gerakan Memilah Sampah) berbasis Book Creator dan PictoBlox dalam meningkatkan pemahaman anak usia 5–6 tahun mengenai pemilahan sampah organik dan anorganik. Metode deskriptif kuantitatif dengan desain pretest dan posttest pada 13 anak yang dipilih melalui purposive sampling. Instrumen pretest dan posttest diuji validitas serta reliabilitasnya, sedangkan analisis data menggunakan uji normalitas dan paired sample t-test. Hasil menunjukkan peningkatan signifikan dari nilai pretest (M = 4,54) ke posttest (M = 7,69) dengan nilai sig. 0,000 < 0,05. Maka, media GEMAS terbukti efektif meningkatkan pemahaman anak dalam memilah sampah. Validasi ahli juga menegaskan kelayakan aspek materi dan interaktivitas media. Secara praktis, GEMAS memperkuat literasi lingkungan melalui pengalaman belajar digital yang konkret dan menarik. Kebaruan penelitian ini terletak pada integrasi Book Creator dan PictoBlox sebagai media pemilahan sampah yang belum banyak diterapkan dalam pembelajaran PAUD.
Transformasi Pembelajaran Melalui Digital Twin: Systematic Literature Review Lintas Jenjang Pendidikan Thoniyah, Diana Qisthin; Widodo, Suprih; Elviani, Ulva
JATISI Vol 12 No 4 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i4.14246

Abstract

Digital Twin (DT) is an innovative technology that creates virtual replicas of physical entities to simulate real-world behavior through real-time data. Although it has been successfully implemented in manufacturing, healthcare, and agriculture sectors, the application of DT in education remains fragmented and focused on specific domains. This study aims to conduct a systematic literature review to identify DT applications in education across various levels, map implementation methodologies, analyze impacts on learning outcomes, and identify challenges and best practices. The method used is a systematic literature review with the PRISMA framework. The search was conducted on the Scopus database for the period 2020-2025 using keywords related to Digital Twin, assessment, and education, yielding 773 articles which were then filtered to 32 final articles. After undergoing quality assessment, 17 articles were selected for further analysis. The research findings indicate that DT enhances students' conceptual understanding and practical skills, supports simulation-based learning, personalized learning, and remote collaboration. These findings provide comprehensive insights into DT utilization that can serve as a reference for researchers, educational practitioners, and policymakers in optimizing the implementation of this technology to improve educational quality.
ANALISIS AI, SISTEM, DAN UI/UX TIKTOK BERBASIS TAM: SYSTEMATIC LITERATURE REVIEW Gusanova, Agizka Rizqta; Widodo, Suprih; Elviani, Ulva
J-SIKA|Jurnal Sistem Informasi Karya Anak Bangsa Vol. 7 No. 02 (2025): Jurnal Sistem Informasi Karya Anak Bangsa (J-SIKA) Vol 7 No 2 edisi Desember 2
Publisher : Program Studi Sistem Informasi

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Abstract

Abstrak Dominasi TikTok dalam lanskap media sosial global sering kali hanya dilihat dari perspektif fenomena budaya, sementara arsitektur teknis yang mendasarinya masih jarang dieksplorasi secara mendalam. Penelitian ini bertujuan untuk menganalisis bagaimana integrasi teknologi di balik layar memengaruhi adopsi pengguna melalui perspektif Technology Acceptance Model (TAM). Menggunakan metode Systematic Literature Review (SLR) dengan protokol PRISMA, penelitian ini menyeleksi dan menganalisis 10 literatur primer yang diterbitkan antara tahun 2020 hingga 2025. Hasil analisis mengungkapkan bahwa persepsi pengguna dibentuk oleh tiga pilar teknis utama. Pertama, persepsi kegunaan (Perceived Usefulness) dikonstruksi oleh algoritma AI berbasis Multimodal Data Fusion yang menjamin personalisasi konten secara presisi. Kedua, persepsi kemudahan penggunaan (Perceived Ease of Use) dicapai melalui sinergi antara desain antarmuka imersif yang meminimalkan beban kognitif dan kinerja sistem berbasis Edge Caching serta Prefetching yang mengeliminasi latensi jaringan. Penelitian ini menyimpulkan bahwa keberhasilan retensi pengguna TikTok adalah hasil dari rekayasa teknis yang menciptakan pengalaman tanpa hambatan (frictionless), di mana stabilitas infrastruktur berfungsi sebagai anteseden vital bagi kepuasan psikologis pengguna. Kata Kunci: TikTok, Technology Acceptance Model (TAM), Kecerdasan Buatan, Desain Antarmuka, Kinerja Sistem. Abstract TikTok's dominance in the global social media landscape is often viewed merely as a cultural phenomenon, while the underlying technical architecture remains underexplored. This study aims to analyze how the integration of backend technologies influences user adoption through the perspective of the Technology Acceptance Model (TAM). Using a Systematic Literature Review (SLR) method with the PRISMA protocol, this study selected and analyzed 10 primary literatures published between 2020 and 2025. The results reveal that user perception is shaped by three main technical pillars. First, Perceived Usefulness is constructed by AI algorithms based on Multimodal Data Fusion which ensures precise content personalization. Second, Perceived Ease of Use is achieved through a synergy between immersive interface design that minimizes cognitive load and system performance based on Edge Caching and Prefetching strategies that eliminate network latency. This study concludes that TikTok's user retention success is the result of technical engineering that creates a frictionless experience, where infrastructure stability serves as a vital antecedent to user psychological satisfaction. Keywords: TikTok, Technology Acceptance Model (TAM), Artificial Intelligence, User Interface, System Performance.
Bridging Theory and Practice: A Review of CT in K-12 Problem-Solving Maghfira, Dinda Alya; Widodo, Suprih; Elviani, Ulva
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.4265

Abstract

The digital era demands students master 21st-century skills, with computational thinking (CT) as the fundamental cognitive foundation for problem-solving. Despite policies such as Indonesia's Kurikulum Merdeka integrating CT, significant implementation gaps persist due to insufficient comprehensive guidelines. This study aims to synthesize empirical evidence on CT implementation in enhancing K-12 students' problem-solving abilities through a Systematic Literature Review (SLR). Using ERIC, SpringerLink, ScienceDirect, IEEE Xplore, and Taylor & Francis databases via Publish or Perish, this research identified 973 articles, subsequently filtered to 27 final articles based on rigorous inclusion and exclusion criteria. Analysis reveals that algorithmic thinking (29%), debugging/evaluation (26%), and abstraction (24%) constitute the most dominant CT components developed. The plugged-in approach (69%) dominates implementation through structured/algorithm-based methods (50%) and game-based learning (31%), with Scratch (44%) and Code.org (38%) as primary platforms. The formulated implementation framework demonstrates developmentally appropriate progression from blended (unplugged-plugged) approaches in early elementary, game-based learning in middle elementary, to project-based learning in high school. Findings reveal that while block-based programming and game design are highly effective for algorithmic thinking and debugging, teaching abstraction remains challenging and requires more specific pedagogical strategies. This research contributes a comprehensive knowledge map bridging the gap between juridical policies and CT learning practices in the field, recommending future research directions for formal assessment development, teacher professional development, and interdisciplinary CT integration.
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.
The Transformation of Teachers' Digital Competence in Online Learning: Analysis of Success Factors and Implementation Challenges Fernandes, Muhammad Rafly Juliawan; Widodo, Suprih; Elviani, Ulva; Salsabila, Rahmawati
The Future of Education Journal Vol 4 No 9 (2025): #1
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v4i9.1265

Abstract

This study systematically analyzes the transformation of teachers' digital competence within the context of online and blended learning. Employing a Systematic Literature Review (SLR) of 25 articles published between 2019–2024, the research identifies the underlying success factors and implementation challenges. The findings reveal that TPACK and DigCompEdu are the most dominant frameworks guiding research and development. Key success factors include high Self-Efficacy and Internal Motivation among teachers, supported by Continuous Hands-on Training and Institutional Leadership. The greatest challenges are rooted in the Infrastructure Gap (First-Order Barriers), prevalent in developing countries, and the Pedagogical Digital Skill Gap (Second-Order Barriers), which refers to teachers' inability to integrate technology for effective interaction and assessment. Successful implementation requires a shift from passive training to Learning by Design models (TPACK-based projects) and continuous Coaching to bolster teacher confidence and bridge the Pedagogical Digital Gap.
Co-Authors Agil Alunjati, Figo Agustin, Amara Seviany Ardiyanti, Dhea Ariffin, Meylani Nur Arrasyid, Rafli Ayu Permata Sari Barri, Muhamad Akda Fathul Fernandes, Muhammad Rafly Juliawan Furqan Alfuady, Muhammad Gusanova, Agizka Rizqta Hafiziani Eka Putri, Hafiziani Eka Hidayat, Fadhil Hopipah, Nurul Huwaida, Febviana Sulthanah Jayadinata, Asep Kurnia Maghfira, Dinda Alya Mahardita, Rere Aulia Rahmatillah, Diniah Rahmatya, Aura Salsabillah Romdhoni, Rhezwan Dhaifullah Sahidah, Lala Nabila Azkia Salsabila, Rahmawati Suprih Widodo, Suprih Thoniyah, Diana Qisthin