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All Journal Menara Perkebunan Sewagati: Jurnal Pengabdian Masyarakat Indonesia Jurnal Riset Rumpun Agama dan Filsafat Jurnal Kajian Penelitian Pendidikan dan Kebudayaan International Journal of Economics and Management Sciences Saturnus: Jurnal Teknologi dan Sistem Informasi Prosiding Seminar Nasional Ilmu Manajemen Kewirausahaan dan Bisnis Indonesian Journal of Science and Education Journal of New Trends in Sciences Journal of Engineering, Electrical and Informatics Metamorfosa: Journal of Biological Science Open Access DRIVERset
Siswanto Siswanto
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences Other

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Journal : Journal of Engineering, Electrical and Informatics

 1 
EXPLORATION OF AMPLITUDE CODING CAPACITIES FOR Q-ML MODEL Unang Achlison; Dendy Kurniawan; Toni Wijanarko Adi Putra; Siswanto Siswanto
Journal of Engineering, Electrical and Informatics Vol. 2 No. 3 (2022): Oktober: 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.v2i3.916

Abstract

Quantum computing implements computation adopting environmental phantasm and the foundation of quantum mechanics to clear up the issues. This design of calculation has been demonstrated to serve the acceleration of some modern processing issues. Current evolution in quantum technology is emerging, and the application of learning design to this current instrument is developing. With enough prospects, the application of quantum development in the area of Machine Learning has come clear. This research develops a TensorFlow Quantum (TF-Q) software framework model for machine learning functions. The two models advanced the application of material coding techniques from amplitude coding to constructing a case in the quantum learning model. This study aimed to explore the scope of amplitude coding to serve enhanced case establishment in learning techniques and in-depth investigation of data sets that bring insight into the practice data adopting the “Variational Quantum Classifier” (VQ-C). The emergence of this current method raises the investigation of how best this tool can be adopted, the aim is to provide several analysis explanations for the element of quantum machine learning that can be applied given the constraints of the actual device. The results of this study indicate there are clear advantages to adopting amplitude coding over another technique as demonstrated by adopting the combination of quantum-humanistic neural networks in TF-Q. In addition, the different preprocessing steps can generate more aspect-affluent data while using VQ-C the no-charge lunch assumption dominance for quantum learning technique for humanistic models. The material even though conceal in quantum by unadvanced data preparation steps but involves new ways of understanding and appreciating these new methods. Future studies will lack expansion into multi-type of analysis models that are sufficiently advanced to be relevant in work similar to this.
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 .
Co-Authors Ananda Ariviana Anita Rusmiati Bambang Subali Danang Danang Dendy Kurniawan Djoko Sri Bimo Esti Utarti Evy Indriasari Fajar Ari Sudewo Firda DIMAWARNITA Hartono Hartono Haryo Tejo PRAKOSO Imawan Sugiarto Irfani, Salistya Masturi Masturi Maya Utami Dewi Mazita, Aza Moh.Taufik Nuryunita Dewantari Priyo Wibowo Safira Isti’nafil Islam Sattya Arimurti Siti Kholifah Sutoyo Sutoyo Sutoyo Sutoyo Toni Wijanarko Adi Putra Unang Achlison Widya Aryani Yora FARAMITHA