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All Journal Syntax Idea Jurnal Penelitian Sistem Informasi International Journal of Computer Technology and Science Journal of New Trends in Sciences Journal of Engineering, Electrical and Informatics
Widya Aryani
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering

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Analisis Semiotika Analisis Semiotika Charles Sanders Peirce Pada Logo PT Bank Mega Syariah Widya Aryani; Ahmad Toni
Syntax Idea Vol 2 No 11 (2020): Syntax Idea
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/syntax-idea.v2i11.647

Abstract

Tujuan penelitian ini untuk menganalisa dan mendeskripsikan makna dari tanda-tanda yang terdapat di dalam logo Bank Mega Syariah. Tujuan penelitian ini untuk menganalisa dan mendeskripsikan makna dari tanda-tanda yang terdapat di dalam logo Bank Mega Syariah. Identitas suatu lembaga merupakan cerminan dari visi, misi suatu lembaga / instansi yang divisualisasikan dalam logo instansi. Logo Bank Mega Syariah yang dibuat saat ini mencirikan identitas dan tujuan yang akan dicapai oleh Bank Mega Syariah, transformasi logo baru Bank Mega Syariah menjadi cerminan semangat seluruh elemen Bank Mega Syariah dalam mewujudkan cita-cita Indonesia. Penegasan symbol “M” yang selama ini sudah banyak dikenal, sebagai representasi dari aspirasi, optimism, peluang dan cita-cita masyarakat Indonesia serta keinginan untuk membangun masa depan keluarga dan bangsa yang lebih baik dan lebih sejahtera. Identitas suatu lembaga merupakan cerminan dari visi, misi suatu lembaga/instansi yang divisualisasikan dalam logo instansi. Logo Bank Mega Syariah yang dibuat saat ini mencirikan identitas dan tujuan yang akan dicapai oleh Bank Mega Syariah, transformasi logo baru Bank Mega Syariah menjadi cerminan semangat seluruh elemen Bank Mega Syariah dalam mewujudkan cita-cita Indonesia. Penegasan symbol “M” yang selama ini sudah banyak dikenal, sebagai representasi dari aspirasi, optimism, peluang dan cita-cita masyarakat Indonesia serta keinginan untuk membangun masa depan keluarga dan bangsa yang lebih baik dan lebih sejahtera.
Penggunaan Model Deep Learning Untuk Meningkatkan Efisiensi Dalam Aplikasi Machine Learning Siswanto Siswanto; Maya Utami Dewi; Siti Kholifah; Greget Widhiati; Widya Aryani
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 1 No. 4 (2023): NOVEMBER : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v1i4.1619

Abstract

The use of deep learning models has become a major focus in optimizing the efficiency of machine learning applications. This research discusses various deep learning models that can be applied to improve efficiency in the context of machine learning applications. These models are designed to handle the complexity of machine learning tasks with a high level of accuracy while still considering aspects of computational efficiency. This article involves an in-depth look at several deep learning models that have proven effective in various application domains. Discussion includes the use of convolutional neural network (CNNs) models for image processing, recurrent neural networks (RNNs) for sequential data, and transformer-based models for natural language processing tasks. In addition, deep learning model tuning and optimization strategies, such as pruning and quantization, are also discussed to improve the efficient use of computing resources. This research identifies challenges and opportunities in integrating these deep learning models into machine learning applications with maximum efficiency. By considering the need for accuracy and limited computational resources, this research provides a holistic view of the approaches that can be applied to deal with complexity in diverse machine learning scenarios. The results are expected to provide a significant contribution to the development of efficient and effective machine learning applications.
Systematic Literature Review on the Application of Blockchain in Enhancing Server Security: Research Methods for Mitigating Ransomware and Malware Attacks Danang Danang; Maya Utami Dewi; Widya Aryani
International Journal of Computer Technology and Science Vol. 1 No. 4 (2024): October: 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.v1i4.186

Abstract

This study aims to explore the application of blockchain in enhancing server security to mitigate ransomware and malware attacks in critical infrastructures such as healthcare, finance, and government sectors. Using a systematic literature review (SLR) approach, the research collects articles from four major databases (IEEE Xplore, Scopus, ScienceDirect, and SpringerLink) published between 2020 and 2024. The search focuses on keywords related to blockchain, server security, ransomware, malware, and attack mitigation. The results indicate that blockchain enhances data integrity, transaction security, and strengthens access control to protect sensitive data. Moreover, integrating blockchain with intrusion detection systems (IDS) and using smart contracts accelerates threat detection and response, allowing for automatic blocking and data recovery from attacks. This technology reduces reliance on manual intervention and increases operational efficiency. However, the main challenges in its implementation include high implementation costs, scalability, and technical complexity. Nevertheless, blockchain offers significant solutions for mitigating ransomware and malware attacks while enhancing the reliability and efficiency of systems. In conclusion, blockchain provides an effective solution for server security and cyber threat mitigation, although challenges related to cost and scalability need to be addressed. Further research is required to develop more efficient blockchain protocols and integrate them with other technologies to enhance threat detection and response speed.
Strategi Pendidikan STEM dalam Meningkatkan Keterampilan Pemecahan Masalah di Sekolah Menengah Greget Widhiati; Widya Aryani
Journal of New Trends in Sciences Vol. 1 No. 2 (2023): Mei: Journal of New Trends in Sciences
Publisher : CV. Aksara Global Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59031/jnts.v1i2.775

Abstract

This study examines the effectiveness of STEM (Science, Technology, Engineering, and Mathematics) education in enhancing problem-solving skills among high school students. With the increasing demand for critical thinking and problem-solving abilities in the workforce, STEM education has become a crucial approach to preparing students for future challenges. The study aims to evaluate how project-based STEM curricula impact students' creativity, analytical skills, and overall problem-solving capabilities. Using a quasi-experimental design with a control group, the research was conducted with high school students who participated in STEM-based lessons involving the 5E instructional model. Data collection involved pre- and post-tests, classroom observations, and semi-structured interviews to measure changes in student skills. The findings indicate that students exposed to STEM education demonstrated significant improvements in problem-solving, creativity, and analytical thinking compared to their peers in traditional lecture-based classes. The study highlights the advantages of project-based learning in promoting active student engagement and fostering skills necessary for addressing real-world problems. These results suggest that STEM education can be more effective than traditional methods in cultivating essential 21st-century skills. The study recommends the broader implementation of STEM strategies in secondary education and further exploration of the long-term impact of STEM learning on various skills required in the professional world.
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 Ahmad Toni Danang Danang Greget Widhiati Maya Utami Dewi Priyo Wibowo Siswanto Siswanto Siswanto Siswanto SITI KHOLIFAH