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Home Assistant With IoT Smart Solution For Smart Home Sukma Rizki; Muhammad Fikry; M Ishlah Buana Angkasa; Fajar Rivaldi Chan
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

The advent of Internet of Things (IoT) technology has revolutionized various aspects of everyday life, particularly within the home environment. IoT-powered home assistants represent one of the primary implementations, offering intelligent automation and control solutions that enhance the modern home experience. This paper explores the implementation of IoT-based home assistants to improve convenience, security, and energy efficiency in smart homes. In addition, the challenges and future directions for the development of this technology are examined, with a focus on key areas such as device interoperability, data privacy and security, and user experience optimization. As demand for smart home solutions continues to rise, the integration of cloud computing, artificial intelligence (AI), and advanced communication protocols will further drive innovation in this field.
A Robust Approach to Student Attendance Using Web-Based Facial Recognition Irfan Sahputra; Muhammad Fikry; Kurniawati Kurniawati
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

In this paper, we introduce an innovative student attendance recording system that utilizes computer vision and machine learning to improve attendance management in educational settings. By employing YOLOv8 for real-time face detection and MobileNetV2 for face recognition, the system achieves high accuracy and efficiency across various classroom conditions. Rigorous testing in diverse lighting environments and varying student densities demonstrated a peak recognition accuracy of 98% in well-lit conditions, with an average face detection time of under one second. This system offers a more robust, efficient, and scalable solution than traditional manual attendance methods, addressing common limitations in accuracy and reliability. Future work will target optimization under low-light conditions, enhancing its applicability in real-world scenarios.
Enhancing Academic Security with RFID-Based Smart Locks and Real-Time Attendance Tracking System Muhammad Al Imran; Muhammad Fikry; Sujacka Retno
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

In this study, we propose a novel RFID-based smart lock system integrated with real-time attendance tracking to enhance academic security. Traditional security methods such as mechanical locks and manual attendance systems are prone to various limitations, including lost keys, falsification, and lack of automatic tracking. Our system utilizes E-KTP cards as RFID identification tools, supported by Internet of Things (IoT) technology, to provide automated door access and efficient attendance monitoring. The implementation results demonstrate a high accuracy rate of 99.5% in reading E-KTP cards, with an average response time of 850 Ms and a 99.5% uptime during a 30-day testing period. The system can handle up to 40 access requests per minute during peak hours. Additionally, it reduces access time by 91%, lowers errors from 5% to 0.2%, cuts operational costs by 60%, and decreases maintenance time by 75%. Security is reinforced through dual encryption using the Vigenère and Bcrypt algorithms, ensuring no security breaches over six months. The dashboard provides real-time monitoring, and the automated attendance system reduces human error, integrating seamlessly with academic databases for user verification and schedule management. This research demonstrates the effectiveness of RFID and IoT technologies in modernizing and securing academic environments.
ANALISIS RISIKO DAN PENENTUAN PRIORITAS MITIGASI ASET TEKNOLOGI INFORMASI PADA KOPERASI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING Wahdana, Aldi; Asrianda; Fikry, Muhammad
Journal of Information Technology (JINTECH) Vol. 7 No. 1 (2026): Februari 2026
Publisher : Prodi Teknologi Informasi UIN Ar-Raniry Bekerjasama dengan Pusat Penelitian dan Penerbitan LP2M Universitas Islam Negeri Ar-Raniry Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/jintech.v7i1.9511

Abstract

This study aims to analyze risks and determine mitigation priorities for information technology assets at the Melati Civil Servant Cooperative. The Simple Additive Weighting (SAW) method is used to determine mitigation priorities based on four main criteria: risk level, asset criticality, Return on Investment (ROI), and Total Cost of Ownership (TCO). This study involved eight information technology assets used to support the cooperative's daily operational activities. Research data was obtained through structured interviews with cooperative administrators to assess the probability and impact of possible risks, the criticality level of each asset, the cost of asset ownership during its useful life, and the resulting economic benefits. The obtained data was then processed using the SAW method to generate a preference value for each asset. The analysis results show that the Savings and Loans Data asset received the highest preference value of 0.876, making it the main mitigation priority. Furthermore, the Cooperative Member Data and Backup Storage Device assets were ranked next in priority. Based on these results, it can be concluded that the SAW method is able to assist cooperative administrators in determining risk mitigation priorities for information technology assets objectively and efficiently