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All Journal Jupiter E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Pixel : Jurnal Ilmiah Komputer Grafis Elkom: Jurnal Elektronika dan Komputer Jurnal Teknologi Informasi dan Komunikasi Teknik: Jurnal Ilmu Teknik dan Informatika Journal of Engineering, Electrical and Informatics (JEEI) Jurnal Teknik Informatika dan Elektro (JURTIE) Jurnal Pengabdian Masyarakat Sains dan Teknologi Jurnal Maklumatika Journal of Management and Informatics Journal of Technology Informatics and Engineering
Fujiama Diapoldo Silalahi
Universitas Sains Dan Teknologi Komputer
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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Journal : Journal of Technology Informatics and Engineering

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Error-Free Arduino Communication: Integrating Hamming Code for UART Serial Transmission Raharjo, Budi; Silalahi, Fujiama Diapoldo
Journal of Technology Informatics and Engineering Vol. 3 No. 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.187

Abstract

Serial communication is a fundamental method for data transfer in electronic devices, particularly in Arduino-based systems. However, existing protocols, such as Universal Asynchronous Receiver/Transmitter (UART), often lack robust error detection mechanisms, leading to potential data integrity issues. This study aims to address the knowledge gap regarding error detection in UART communication by implementing Hamming Code, a well-established method for detecting and correcting single-bit errors. The research employs a systematic approach, including data encoding before transmission and decoding with error correction at the receiver end. The results demonstrate that the integration of the Hamming Code significantly enhances the reliability of data transmission, reducing error rates and improving overall system performance. The implications of this research extend to various applications requiring high data integrity, such as industrial control systems and Internet of Things (IoT) devices. By providing a practical solution to the challenges of error detection in serial communication, this study contributes to the advancement of reliable communication systems in modern technology.
Framework-Driven Design: Analyzing the Impact of the Zachman Framework on LMS Effectiveness Silalahi, Fujiama Diapoldo; Nugroho, Setiyo Adi; Hartono, Budi
Journal of Technology Informatics and Engineering Vol. 3 No. 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.196

Abstract

In today's digital era, Learning Management Systems (LMS) play a crucial role in education. Despite the availability of numerous LMS platforms, challenges in designing effective and efficient systems persist, particularly in integrating comprehensive frameworks like the Zachman Framework. This study aims to explore the application of the Zachman Framework in LMS design to enhance system effectiveness and user satisfaction. The research employs a mixed-methods approach, combining qualitative and quantitative methods. Data is collected through a survey involving 100 respondents, including instructors, LMS developers, and students. The study analyzes qualitative data using thematic analysis and quantitative data through descriptive statistical techniques. The findings reveal that 85% of respondents believe that applying the Zachman Framework in LMS design significantly improves system effectiveness. Additionally, the average user satisfaction score for LMS designed using this framework is 4.2 on a 5-point scale, indicating a high level of satisfaction. This research concludes that implementing the Zachman Framework not only aids in identifying user needs and designing essential system functions but also ensures that all elements are well-integrated. These findings provide valuable insights for LMS developers and educational institutions in creating more effective and responsive systems that meet user needs..
Transformers in Cybersecurity: Advancing Threat Detection and Response through Machine Learning Architectures Hartono, Budi; Silalahi, Fujiama Diapoldo; Muthohir, Moh
Journal of Technology Informatics and Engineering Vol. 3 No. 3 (2024): December (Special Issue: Big Data Analytics) | JTIE: Journal of Technology Info
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i3.211

Abstract

The increasing sophistication of cyber threats has outpaced the capabilities of traditional detection and response systems, necessitating the adoption of advanced machine learning architectures. This study investigates the application of Transformer-based models in cybersecurity, focusing on their ability to enhance threat detection and response. Leveraging publicly available datasets, including CICIDS 2017 and UNSW-NB15, the research employs a systematic methodology encompassing data preprocessing, model optimization, and comparative performance evaluation. The Transformer model, tailored for cybersecurity, integrates self-attention mechanisms and positional encoding to capture complex dependencies in network traffic data. The experimental results reveal that the proposed model achieves an accuracy of 97.8%, outperforming conventional methods such as Random Forest (92.3%) and deep learning approaches like CNN (94.1%) and LSTM (95.6%). Additionally, the Transformer demonstrates high detection rates across diverse attack types, with rates exceeding 98% for Denial of Service and Brute Force attacks. Attention heatmaps provide valuable insights into feature importance, enhancing the interpretability of the model’s decisions. Scalability tests confirm the model’s ability to handle large datasets efficiently, positioning it as a robust solution for dynamic cybersecurity environments. This research contributes to the field by demonstrating the feasibility and advantages of employing Transformer architectures for complex threat detection tasks. The findings have significant implications for developing scalable, interpretable, and adaptive cybersecurity systems. Future studies should explore lightweight Transformer variants and evaluate the model in operational environments to address practical deployment challenges.
Co-Authors Budi Hartono budi hartono Budi Hartono Budi Raharjo Candra Supriadi Candra Supriadi Candra Supriadi Danang, Danang Daniel Rudjiono Dian Noor Hamami Dwi Prasetyaningsih Firman Murtadlo Galeh Septiar Pontang Hendri Rasminto Indrawan Nagasus Iwan Koerniawan Jarot Dian Jarot Dian Joseph Teguh Santoso Joseph Teguh Santoso Khoirur Rozikin Khoirur Rozikin Laksamana Rajendra Haidar Moh Muthohir Muhammad Sholikhan Mukhoyyarotul Jannah Nandito Putra Prabawa Nia Dharma Pertiwi Nia Dharma Pertiwi Nuris Dwi Setiawan Raden Mohamad Herdian Bhakti Setiyo Prihatmoko Sigit Umar Anggono Sigit Umar Anggono Siswanto, Edy Sitinjak, Charli Sumaryanto Toni Wijanarko Adi Putra Unang Achlison Yogiswara Yogiswara Yogiswara