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All Journal PROSIDING SEMINAR NASIONAL Autotech: Jurnal Pendidikan Teknik Otomotif Universitas Muhammadiyah Purworejo E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Elkom: Jurnal Elektronika dan Komputer PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer MANAJEMEN Journal of Engineering, Electrical and Informatics (JEEI) Jurnal Universal Technic Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Publikasi Ilmu Manajemen Jurnal Penelitian Rumpun Ilmu Teknik Jurnal Publikasi Teknik Informatika (JUPTI) Jurnal Sains dan Ilmu Terapan Jurnal Sistem Informasi dan Ilmu Komputer Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Jurnal Elektronika dan Teknik Informatika Terapan Journal of Technology Informatics and Engineering Seminar Nasional Teknologi dan Multidisiplin Ilmu Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Router : Jurnal Teknik Informatika dan Terapan Repeater: Publikasi Teknik Informatika dan Jaringan Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi International Journal of Computer Technology and Science International Journal of Information Engineering and Science International Journal of Electrical Engineering, Mathematics and Computer Science Jurnal Bengawan Solo: Pusat Kajian Penelitian dan Pengembangan Daerah Kota Surakarta Systematic Literature Review Journal Journal of New Trends in Sciences Router : Jurnal Teknik Informatika dan Terapan Journal of Engineering, Electrical and Informatics Global Science: Journal of Information Technology and Computer Science Jurnal Sistem Informasi dan Ilmu Komputer
Danang Danang
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Decision Making System For Selection Of Prospective Scholarship Recipients Using The Saw (Simple Additive Waighting) Method At Vocational School Bina Negara Gubug Uswatul Chasanah; Danang Danang; Teguh Setiadi
Journal of Engineering, Electrical and Informatics Vol. 4 No. 1 (2024): February : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v4i1.2871

Abstract

The selection system at Bina Negara Gubug Vocational School Jl. KH. Hasan Anwar No.9 Gubug currently processes data on the criteria for each student for each type of scholarship. It does not yet have a database system but uses a computerized system with Microsoft Excel, so there are often delays in the selection process in preparing the selection report for scholarship recipients. This research uses the Research and Development (R & D) development model by Borg and Gall with 6 steps of development, namely Research and Information Collecting, Planning, Develop Premilinary Form of Product, Premilinary Field Testing, Main Product Revision, Main Field Testing. The scholarship selection decision support system application product uses the SAW (Simple Additive Waighting) method. Visual Basic 6.0 development software and Microsoft Access database. This system can provide a useful solution for the decision-making system for selecting scholarship recipients for schools so that a better and faster selection can be achieved.
Hybrid Federated Ensemble Learning Approach for Re-al-Time Distributed DDoS Detection in IIoT Edge Compu-ting Environment Danang Danang; Siswanto Siswanto; Widya Aryani; Priyo Wibowo
Journal of Engineering, Electrical and Informatics Vol. 5 No. 1 (2025): Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i1.5099

Abstract

Development rapid from the Industrial Internet of Things ( IIoT ) and edge computing have revolutionize modern industry through distributed data processing with latency low . However , progress this also enlarges risk security cyber , in particular Distributed Denial of Service (DDoS) attacks can to disable operation industry that is critical . System Detection Conventional Intrusion (IDS) own limitations in matter scalability , data privacy , and capabilities generalization to environment Heterogeneous IIoT . For answer challenge said , research This propose A framework Hybrid Federated–Ensemble Learning (FL–EL) work to improve efficiency detection real -time DDoS attacks on networks IIoT edge -based . This model utilizing the Edge -IIoTset dataset which reflects pattern Then cross real in system industry . Federated learning is used For train the model collaborative across multiple edge nodes without need move data to center , so that guard data privacy . Each node performs training local using the basic model such as Random Forest (RF), XGBoost , and Support Vector Machine (SVM). Then , the central server do aggregation use ensemble techniques such as soft voting and stacking. The preprocessing process includes SMOTE technique and Z-score normalization for handle imbalance class and improve performance .Evaluation results show that This FL–EL hybrid approach capable reach performance high (F1-score > 99.5%) and significantly significant reduce level error positive as well as burden communication , compared with approach centralized . Framework this also shows ability detection fast with latency low , making it suitable For implementation in the system IIoT that requires resilience time real . Development advanced will covers Explainable AI integration for model interpretation and blockchain for secure and transparent logging .
Digital Twin-Based Cyber-Physical Security Framework Incorporating AI-Driven Predictive Maintenance and Zero-Trust Architecture in Smart Grid Systems Danang Danang; Febri Adi Prasetya; Rashad Huseynaga Asgarov
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 3 (2025): September: Global Science: Journal of Information Technology and Computer Scien
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i3.168

Abstract

The increasing integration and digitization of smart grid systems have exposed them to a variety of security threats, necessitating robust security measures to ensure their reliability and efficiency. This paper proposes a novel Digital Twin-Based Cyber-Physical Security Framework, incorporating AI-driven predictive maintenance and zero-trust architecture to address the evolving challenges of securing smart grids. By leveraging digital twin technology, this framework creates a real-time virtual representation of physical systems, enabling continuous monitoring and simulation for enhanced security and operational performance. Zero-trust security principles are integrated to ensure that no entity, whether inside or outside the network, is trusted by default, thus significantly reducing the risk of cyber-attacks. Additionally, AI-driven predictive maintenance enhances the framework’s reliability by proactively identifying potential failures before they occur, reducing downtime and improving system resilience. Through the development and simulation of this framework, including attack and failure scenarios, the paper demonstrates that the proposed system outperforms traditional methods in terms of anomaly detection, system downtime, and response times. The integration of predictive maintenance allows for early identification of component failures, thus enhancing the overall resilience of the grid. The zero-trust architecture further strengthens the cybersecurity posture, preventing unauthorized access and attacks. The study also identifies challenges, such as data synchronization and scalability, which must be addressed for broader implementation in large-scale smart grid systems. The findings suggest that the proposed framework could play a critical role in the future evolution of smart grid security, offering valuable insights for researchers and practitioners.
Evaluating Trust Aware Machine Learning Models for Secure Data Sharing in Distributed Internet of Things and Edge Computing Infrastructures Eko Siswanto; Danang Danang; Sunarmi Sunarmi
International Journal of Computer Technology and Science Vol. 1 No. 1 (2024): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i1.359

Abstract

The rapid growth of Internet of Things (IoT) and edge computing technologies has introduced new security challenges due to the distributed, heterogeneous, and dynamic nature of these environments. Conventional static security mechanisms, such as rulebased authentication and fixed trust models, are often inadequate for addressing evolving threats and abnormal behaviors in largescale IoT systems. To overcome these limitations, this study proposes a machine learningbased trust evaluation framework for enhancing security in distributed IoT environments. The proposed approach dynamically assesses the trustworthiness of IoT nodes by analyzing behavioral and interactionbased features collected at the edge layer. Machine learning models are trained to classify nodes into trusted and malicious categories and continuously update trust values in response to changing network conditions. Based on the predicted trust levels, adaptive security decisions are enforced to allow or restrict node participation in data sharing and computation processes. A quantitative experimental evaluation is conducted using simulated distributed IoT scenarios that include both normal and malicious behaviors. The performance of the proposed framework is evaluated using standard metrics such as accuracy, precision, recall, F1score, and detection effectiveness, and is compared against conventional static trust and rulebased security mechanisms. The results demonstrate that the proposed machine learningbased trust evaluation approach achieves significantly higher detection accuracy and robustness while maintaining low computational overhead. Overall, the findings confirm that integrating machine learning into trust management provides an effective and scalable solution for securing distributed IoT systems under dynamic and adversarial conditions.
Perancangan Tempat Sampah Pintar Berbasis Arduino Uno Fa`iq Khotibul Umam; Nuris Dwi Setiawan; Danang Danang; Mufadhol Mufadhol
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.2728

Abstract

The lack of awareness from Resto visitors in the process of disposing of garbage in its place makes the environment around the Resto polluted at least the awareness of Resto visitors to dispose of garbage in its place is still low. The purpose of this research is to create an automation system for the trash can. The problem that arises for Resto S2 is the lack of effectiveness, especially in the tissue waste section, one of the solutions that can be done for these problems, namely by designing a device in the form of a smart trash can that can open and close automatically, so that Resto visitors do not need to make direct contact with the trash can. Researchers aim to realize the design of the tool, as for the method carried out in this study is to implement the design of a smart trash can in the form of a box that has an input in the form of an ultrasonic sensor, and an output in the form of a servo motor. The results of input and output testing show that the ultrasonic sensor can detect movement in front of the trash can and the servo motor can move the trash can cover, so it can be concluded that the smart trash can work system as a whole can function properly in accordance with the design that has been made.
Co-Authors Agus Priyadi Agustinus Budi Santoso Ahmad Ashifuddin Aqham Ahmad Zainudin Aldo Raditya Pangestu Andik Prakasa Hadi Arie Atwa Magriyanti Budi Santoso Dani Sasmoko Daniel Rudjiono Dendy Kurniawan Dewi Retno Putri Eka Satria Wibawa Ekky Fredyan Eko Siswanto Eko Siswanto Eni Muhadi Fa`iq Khotibul Umam Febri Adi Prasetya Febryantahanuji Febryantahanuji Greget Widhiati Hanif Assabib Rosyid Hendri Rasminto Iman Saufik Suasana Indra Ava Dianta Joseph Teguh Santoso Kenny Setiawan Khoirur Rozikin Kusumajaya, Robby Andika Laily Eka Andrianni Lilis Suryani Mat Toyib Maya Utami Dewi Muhamad Khoirul Umam Muhammad Ainun Najib Muhammad Fauzi Alfikri Mukhammad Ibnu Khalim NUR FAUZIAH Nuris Dwi Setiawan PADJAR SETYO BUDI Priyadi Priyadi Priyo Wibowo Puteri Anindya Maulan Raden Mohamad Herdian Bhakti Rashad Huseynaga Asgarov Rizky Ni'ma Febriani Siswanto Siswanto Siswanto Siswanto Siswanto Siswanto Siswanto, Edy Siti Kholifah Sulartopo Sulartopo Sunarmi Suprapti Suprapti Suwardi Suwardi Tanveer Shah Teguh Setiadi Toni Wijanarko Adi Putra Uswatul Chasanah Widya Aryani Wijaya Heti Susanti Zaenal Mustofa Zellius Ragiliawan