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p-Index From 2020 - 2025
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All Journal Syntax Idea Jurnal Penelitian Sistem Informasi International Journal of Computer Technology and Science
Widya Aryani
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management

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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.
Co-Authors Ahmad Toni Danang Danang Greget Widhiati Maya Utami Dewi Siswanto Siswanto SITI KHOLIFAH