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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Jurnal Ilmu Komputer Buletin Udayana Mengabdi Jurnal SPEKTRUM Jurnal Pendidikan Teknologi dan Kejuruan TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic PROSIDING CSGTEIS 2013 Jurnal Teknologi Informasi dan Ilmu Komputer JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Syntax Literate: Jurnal Ilmiah Indonesia Matrix : Jurnal Manajemen Teknologi dan Informatika Cetta: Jurnal Ilmu Pendidikan Jurnal RESISTOR (Rekayasa Sistem Komputer) Astonjadro International Journal of Advances in Data and Information Systems Jurnal Ilmiah Vastuwidya Jurnal Locus Penelitian dan Pengabdian Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal SPEKTRUM
I Made Oka Widyantara
Electrical Engineering Universitas Udayana
Aerospace Engineering Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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Bibliometric Analysis of AI-Based Prototype Proposal for User Security Awareness in Healthcare Pratama, I Putu Agus Eka; Widyantara, I Made Oka; Linawati, Linawati; Gunantara, Nyoman
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.3319

Abstract

In the realm of public healthcare, integrating information technology (IT) must be judiciously balanced with heightened security awareness among users, given the escalating frequency of cyberattacks targeting this sector. Despite the availability of various product and service solutions aimed at enhancing user security awareness, these efforts have yet to yield optimal outcomes. There is a pressing need for innovative approaches to bolster healthcare user security awareness through IT, particularly leveraging the rapidly advancing field of artificial intelligence (AI). This study conducts a comprehensive review of prior research on the application of AI, specifically Large Language Models (LLM), within the domain of healthcare cybersecurity from 2014 to 2024. The objective is to ascertain the volume of publications, trace the evolution of publication trends, and assess the potential and positioning of research in this area. Employing a bibliometric analysis methodology, this study analyzes a dataset comprising 1000 related publications indexed by Google Scholar. The findings reveal that publications concerning applying LLM AI in healthcare cybersecurity constituted 12.82% in 2023, with a significant increase to 87.18% in 2024, representing a 6.8-fold rise. The mapping of publication developments is categorized into 24 clusters, with large language models, healthcare, retrieval-augmented generation, LLM, artificial intelligence, and cybersecurity emerging as the six most frequently discussed keywords in the research landscape. Consequently, this study underscores the substantial potential for current and future research on the application of AI in healthcare cybersecurity, advocating for the development of AI-based solutions to enhance healthcare user security awareness.
Gamification Project-Based E-learning in Character Education: A Study in Senior High School Merliana, Ni Putu Eka; Widyantara, I Made Oka; Wirastuti, Ni Made Ary Esta Dewi; Saputra, Komang Oka; Setyohadi, Djoko Budiyanto
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.4033

Abstract

E-learning in education faces challenges in improving students' engagement, specifically regarding character education effectiveness. Gamification is among the strategies that can be applied to increase student engagement in the project-based learning process. Therefore, this study aimed to develop a Gamification Framework for Project-Based E-learning in Character Education (GaPolCE) as an innovative solution to improve engagement and character education at the senior high school level. A quantitative study was carried out using a quasi-experimental method, where data collection was carried out through a pre-post test and log data analysis to measure the effectiveness of gamification in achieving character education and student engagement. The results showed that the implementation of GaPolCE improved aspects of character education measured using the N-Gain score, where moral knowledge was in the high category (0.70) while moral feeling (0.49) and moral action (0.51) were in the moderate category. Student engagement increased significantly by 67%, 8%, and 25% for behavioral, emotional, and cognitive engagement. However, the effectiveness of in-depth character formation requires long-term evaluation. In addition, the assessment of the application of gamification in project learning for character education is still done manually, thus increasing teachers' workload. In this regard, further research is needed with a longitudinal approach to ensure the sustainability of its influence. In addition, it is necessary to develop an automatic assessment system based on artificial intelligence to increase the efficiency of character education evaluation. 
OPTIMALISASI DETEKSI WAJAH DLIB-HOG PADA CITRA INTENSITAS RENDAH DENGAN PREPROCESSING CLAHE David Clemens Sumampouw; Prahasta Napolado Damanik; Feliks Sinaga; I Made Oka Widyantara; Ngurah Indra ER
Jurnal SPEKTRUM Vol. 12 No. 3 (2025): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2025.v12.i03.p25

Abstract

Face decection using Dlib-HOG offers high performance under ideal lighting condition but significantly degrades when applied to low-light images. This study evaluates the effectiveness of Contrast Limited Adaptive Histogram Equalization (CLAHE) as a preprocessing method to enhance face detection accuracy under poor lighting conditions. CLAHE is applied to grayscale images to improve local contrast without introducing excessive artifacts, thereby making facial features more distinguishable for the HOG-based algorithm. Experiments were conducted on a facial image dataset with varied lighting conditions, comparing detection results before and after preprocessing. The results show a notable improvement in detection accuracy from 85.7% to 96.4% and a reduction in false negatives, with only a minimal increase in processing time. These findings confirm that CLAHE is an efficient and lightweight enhancement technique for improving the performance of Dlib-HOG on low-quality images.
Semantic Ontologi Sebagai Solusi Potensial untuk Meningkatkan Interoperabilitas Data Rahmi Nur Shofa; I Made Oka Widyantara
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Digital transformation requires a modern management information system (MIS) to integrate data originating from various subsystems with heterogeneous formats, terminology and structure. Conventional schema mapping and extraction-transformation-load (ETL) based approaches are often incapable of addressing these challenges semantically. Semantic Ontologies offer conceptualization solutions that support interoperability and enable automated reasoning. This article presents a comprehensive understanding of the current literature on the application of semantic ontologies to information systems, highlighting the main contributions and limitations of previous research. The results show that most research still focuses on specific domains (culture, education, business), while semantic transmission across enterprise subsystems, ontology evolution issues, and performance evaluation measures are still rarely researched. Based on this mix, this research offers a semantic ontology framework designed for holistic data representation in integrated MIS, with the emphasis of ontology development across subsystems (ERP, CRM, SCM, HRIS), as well as performance evaluation measured in the aspects of interoperability, reasoning and query efficiency. It is hoped that this information contribution can strengthen the destruction of management systems while increasing the organization's adaptability to digital business dynamics.
Penerapan AI untuk Sistem HVAC Bangunan Pintar: Integrasi Prediksi Spasio-Temporal, MARL, dan Contrastive Learning Putu Bagus Adidyana Anugrah Putra; I Made Oka Widyantara
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The building sector accounts for over 40% of global energy consumption, with Heating, Ventilation, and Air Conditioning (HVAC) systems responsible for nearly 60% of this share. Improving HVAC efficiency while maintaining occupant comfort has therefore become a critical challenge for smart building management. Conventional control strategies, such as rule-based methods and Model Predictive Control (MPC), often fall short when dealing with dynamic, multi-zone environments. In response, recent advances in Artificial Intelligence (AI) have introduced new directions for HVAC prediction and control. This review systematically analyzes 15 recent studies (2023-2025), classified into three main categories: (i) Graph-SpatioTemporal Prediction (C1), focusing on graph neural networks combined with temporal modules for predicting temperature, CO?, occupancy, and energy demand; (ii) Multi-Agent Reinforcement Learning (C2), enabling adaptive and decentralized HVAC control across multiple zones and subsystems; and (iii) Representation & Contrastive Learning (C3), which enhances time-series representation to improve data efficiency and generalization. The synthesis highlights key achievements: high prediction accuracy from graph-temporal models, up to 40% energy savings using MARL, and improved robustness through contrastive learning. However, gaps remain, including the limited adoption of multi-task prediction, insufficient exploration of curriculum learning and policy distillation in MARL, and minimal integration of contrastive learning into HVAC applications. Looking ahead, the review outlines a 5-10 year roadmap, emphasizing hybrid multi-task models, curriculum MARL, contrastive-RL integration, cross-building transferability, federated learning, and the vision of autonomous, self-evolving HVAC systems. By providing a comprehensive mapping of the state of the art and future opportunities, this review aims to guide researchers and practitioners toward developing AI-based HVAC solutions that are more efficient, adaptive, and occupant-centered.
Sistem Informasi Geografis Stasiun Pemantauan Spektrum Frekuensi Radio Di Wilayah Bali I Nyoman Suada; I Made Oka Widyantara
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The Radio Frequency Spectrum Monitoring Center Denpasar must carry out observation and monitoring. In carrying out this monitoring, there are eight fixed and transportable monitoring stations that have been placed in several locations in the Bali Province to carry out monitoring. However, given the scattered distribution of Radio Station Licenses across various locations in cities/regencies in the province of Bali, there are blind spots where some Radio Station Licenses are not covered by fixed and transportable stations. This will affect the achievement of the observation and monitoring performance agreement targets of the Radio Frequency Spectrum Monitoring Center. In practice, observations and monitoring must be carried out in uncovered locations using mobile or portable monitoring devices. The selection of monitoring locations is based on the distribution of ISRs, the coverage radius of monitoring points, and the conditions and contours of the area. This ensures that these locations are effective and efficient in providing optimal results, especially in achieving the observation and monitoring performance agreement targets. The analysis method utilizes the QGIS application, where optimal locations are identified based on the visual representation of locations in Google Earth, the locations of fixed and transportable stations, and the distribution of Radio Station Licenses, which are then visualized in the QGIS application. Based on the results of the analysis and visualization, it was found that the percentage of performance agreement achievement or the number of radio station licenses monitored at the monitoring location was achieved. The nine cities/regencies in Bali Province have the following achievement percentages: Badung 99%, Tabanan 85%, Klungkung 100%, Gianyar 99%, Karangasem 85%, Denpasar 100%, Bangli 100%, Jembrana 86%, and Buleleng 89%.
Perancangan Rating Tool untuk Evaluasi Green IT di Perguruan Tinggi Cecep Muhamad Sidik Ramdani; I Made Oka Widyantara
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Sustainability issues in information technology are gaining increasing attention as energy consumption, carbon emissions, and environmental impacts from the use of software and digital infrastructure increase. This research aims to develop a Green IT evaluation framework based on a rating tool that is integrated with the principles of the Green Software Foundation (GSF) and COBIT 2019 as an IT governance framework. This approach combines the basic principles of sustainable software evaluation, such as carbon efficiency, energy efficiency, hardware efficiency, networking efficiency, and holistic lifecycle evaluation, with relevant COBIT 2019 objectives, such as resource optimization, managing enterprise architecture, managing quality, and monitoring performance. The results of this integration form an Environmentally Sustainable Computing (ESC) framework that covers four main dimensions: design, deployment, monitoring & refactoring, and governance & policy. Each dimension has assessment indicators with a maturity level scale of 0–5, so it can be used as an evaluation tool for the level of IT sustainability in higher education. This research is expected to be able to provide conceptual and practical contributions in the development of a Green IT rating tool that is applicable in the academic environment.
Systematic Literature Review: Kecerdasan Buatan untuk Penilaian Kualitas Telur secara Non-Destruktif Andi Nur Rachman; I Made Oka Widyantara
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Systematic Literature Review (SLR) is a structured research approach used to map scientific developments, identify research gaps, and provide evidence-based knowledge synthesis. This study aims to systematically review the literature on the application of machine vision, artificial intelligence (AI), and deep learning in egg quality detection, with a particular focus on duck eggs as the research object. Egg quality assessment is crucial in the poultry industry, both to determine suitability for consumption and to ensure successful hatching. However, manual inspection methods are still widely applied, which often result in inaccuracies and inconsistencies. Using the PRISMA methodology, a total of 120 articles published between 2015–2024 were initially identified, of which 45 were selected as relevant studies after screening and eligibility checks. The review results indicate a significant increase in detection accuracy, shifting from conventional image-processing techniques to advanced algorithms such as CNN, ResNet-50, and YOLOv8, achieving accuracies above 94%. Major challenges remain, including the lack of publicly available datasets, risks of overfitting, and limited real-world implementation. This study concludes that future research directions should focus on the integration of lightweight IoT-based systems, standardized duck egg datasets, and hybrid methods (image–spectroscopy) to improve accuracy, robustness, and practical adoption of egg quality detection systems.
Integrasi Data Science dan AI untuk Optimalisasi Layanan Pemerintahan: Literatur Review Kadek Dwi Mahardika Adnyana; I Made Oka Widyantara; NMAED Wirastuti; Ida Bagus Gede Manuaba
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Indonesia’s digital government agenda establishes a policy backbone for data-driven and AI-enabled public services through the national Electronic-Based Government System (SPBE) and the One Data policy, while the Personal Data Protection Law (PDP) frames privacy-by-design obligations for public institutions. Building on international guidance (OECD’s G7 Toolkit; World Bank’s GovTech Maturity Index), this review synthesizes how Data Science (DS)—via reliable feature engineering and descriptive–predictive analytics—can be aligned with Artificial Intelligence (AI) for automation and decision support under public-sector accountability requirements. We identify recurrent enablers (interoperable data architecture, data governance, civil service capabilities, and MLOps) and barriers (data silos, legacy constraints, skills gaps, and explainability/ethics demands), and propose evaluation indicators that link model performance to service performance: service latency reduction, service quality, model fairness, and explainability. The contribution is a systems view that connects SPBE/Satu Data/PDP compliance to DS–AI operations across the lifecycle (governance ? pipeline/feature store ? training/validation ? deployment ? MLOps & audit), and a graduate-level research agenda on causal impact and federated collaboration across agencies.
Enhancing AI-driven Cybersecurity Awareness Smart Consultant using RAG Method with Hybrid Knowledge Based Pratama, I Putu Agus Eka; Widyantara, I Made Oka; Linawati, Linawati; Gunantara, Nyoman
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i1.1488

Abstract

The rapid advancement of Artificial Intelligence (AI), particularly in the realm of Large Language Model (LLM), holds significant potential for addressing the escalating issue of cyberattacks that exploit users' insufficient cybersecurity awareness. This study involves the design and development of a prototype cybersecurity awareness smart consultant, leveraging AI through the Retrieval Augmented Generation (RAG) method. This approach integrates hybrid knowledge derived from both user-specific internal cybersecurity documents and internet resources, thereby enhancing the validity of system responses and mitigating the risk of hallucinations. The prototype was evaluated using the Answer Accuracy Score (AAS) method, based on Black Box Testing and human evaluation, across four cybersecurity-related questions, yielding an average score of 0.925, accompanied by comprehensive analysis and discussion. The findings indicate that the system's response accuracy improves when knowledge is synthesized from both internal document resources and internet sources. Future research may focus on incorporating deliberative thinking to further enhance system performance in generating responses.
Co-Authors A. T. A Prawira Kusuma A.A. Made Agung Istri Iswari Aditya Dwipayana Aditya Widhiatama, Ngakan Putu Agus Anwar Eka Wahyudi Anak Agung Ayu Putri Ardyanti Anang Kusnadi Andi Nur Rachman Aniek Laksmidewi Arda Narendra, I Gusti Lanang Asana, I Made Dwi Putra Atmaja, Ketut Jaya Ayuni Harianti Ayuni Harianti Bagus D. Cahyono Cecep Muhamad Sidik Ramdani Christanto Nadeak, Yobel Cokis Ratih Kumbara David Clemens Sumampouw Derry Suia Pathentantama Desak Ayu Sista Dewi Dessy Hariyanti, NK Dewa Ayu Indah Cahya Dewi Dewa Made Sri Arsa, Dewa Made Dewa Made Wiharta Edo Halim Saputra Fajar Purnama Feliks Sinaga Gamantyo Hendrantoro Gede Manuaba, Ida Bagus Gede Sukadarmika Haris Chandra Agustina I Dewa Gede Hardi Rastama I G. A. K. Diafari Djuni Hartawan I G.A.K. Warmayana I Gede Iwan Sudipa I Gede Sudiantara I Gede Sudiantara I Gusti Agus Adek Putra Ardiwinata I Gusti Ayu Garnita Darma Putri I Gusti Nyoman Dharmayana I Gusti Rai Agung Sugiartha I Kadek Adi Wiguna Sanjaya I Kadek Noppi Adi Jaya I Komang Adi Bayu Adnyana I Made Aditya Virgiawan I Made Arsa Suyadnya I Made Bayu Dibawan I Made Dhanan Pradipta I Made Dwi Putra Asana I Made Rai Putera Yasa I Made Sukarsa I Made Yudi Candra Putra I Nyoman Gede Arya Astawa I Nyoman Gunantara I Nyoman Suada I Nyoman Suada I Putu Agus Eka Pratama I Putu Ardana I Putu Gd Sukenada Andisana I Putu Noven Hartawan I Wayan Kayun Wardana I Wayan Shandyasa I Wayan Shandyasa I.A Laksmi IBGD. Dhyaksa Ida Bagus A. Swamardika Ida Bagus Gede Manuaba Ida Bagus Putu Adnyana Ida Bagus Putu Adnyana Indra Dwi Cahya Setyawan Janice Jessica Indrayani Jayantari, Made Widya Juliawan Pawana, I Wayan Adi Kadek Dwi Mahardika Adnyana Kadek Surya Adi Saputra Kamarudin, Nur Diyana Ketut Bagus Bayu Sanjaya Komang Ery Rusdiana Komang Gede Widi Adnyana Komang Kompyang Agus Subrata Komang Oka Saputra Komang Tri Wahyuni . L Linawati L.D. Purnamasari Linawati Linawati Linawati Linawati Linawati Linawati linawati linawati Lintin, Yosep Tara M Acarya Mordekhai Karang M Zatiar Erwan Kalam M. Azman Maricar made andyka Made Arya Putra Kusuma Made Sudarma Made Sudarma Muhammad Audy Bazly N Utami Wedanti N. M. A. E. Dewi Wirastuti N.M.A.E.D Wirastuti Ngurah Indra ER Ni Komang Ayu Suandaniasih Ni Made Ary Esta Dewi Wirastuti Ni Made Ary Esta Dewi Wirastuti Ni Putu Eka Merliana Ni Putu Widya Yuniari NMAED Wirastuti Nyoman Pramaita Nyoman Pramaita Nyoman Putra Sastra P. A. Satya Prabhawa Pawana P., I Gusti Ngurah Agung Pawana, I Wayan Adi Juliawan Prabawa, I Nyoman Angga Pradnyana, I Made Prahasta Napolado Damanik Putra, Putu Bagus Adidyana Anugrah Putri Alit Widyastuti Santiary Putu Agus Pradnyana Jaya Putu Arya Mertasana Putu Krisna Adi, I Gusti Ngurah Putu Prima Winangun Putu Sintia Susiani Pande R. Sapto Hendri Boedi Soesatyo Rahmi Nur Shofa Rukmi Sari Hartati Santi Ika Murpratiwi Saputra, Komang Oka Setyohadi, Djoko Budiyanto Sri Andriati Asri Sri Andriati Asri, Sri Andriati Susila, Anak Agung Ngurah Hary Tri Febriana Handayani W. Setiawan Widiadnyana, Putu Widyadi Setiawan Widyanto, I Putu Wikananda, I Gusti Ngurah Satya Wirawan Wirawan