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Decision Support System for Determining Recipients of Subsidized Foodstuffs for Poor Families Using the Simple Addictive Weighting Method Afifah Sagita Pratiwi; Gushelmi; Sepsa Nur Rahman
Journal of Computer Scine and Information Technology Volume 10 Issue 4 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i4.111

Abstract

Technology is increasingly becoming a necessity that must be met, both in the world of education and in the world of business and social, especially information technology is used not only as a support but also as a primary need that can be used to provide information quickly. In accordance with what has been determined to obtain Subsidized Food, criteria are needed to determine who will be selected to receive subsidized food. The distribution of subsidized food is distributed to underprivileged or poor citizens. To assist in determining who is eligible to receive subsidized food, a decision support system is needed. One method that can be used for Decision Support Systems is by using Simple Additive Weighting (SAW). In this study, a case will be raised, namely finding the best alternative based on predetermined criteria by using the SAW method to calculate the method in the case. This method was chosen because it is able to select the best alternative from a number of alternatives, in this case the intended alternative is those who are entitled to receive subsidized food based on the specified criteria. The study was conducted by finding the weight value for each attribute, then a ranking process was carried out which would determine the optimal alternative, namely the poor. After the study was conducted, the results obtained were that there were 4 alternatives receiving Subsidized Food and the one with the highest value was alternative 5 with the name Yuhel Fentri with a value of 0.875.
Implementasi Face Recognition dan Algoritma Otp Pada Akses Keamanan Monitoring Pembangkit Listrik Masril, Mardhiah; Yesha Aishya Aprila; Sepsa Nur Rahman; Firdaus
JURNAL QUANCOM: QUANTUM COMPUTER JURNAL Vol. 4 No. 1 (2026): Juni 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/d13myx30

Abstract

The development of digital technology demands smarter and more integrated security systems, particularly for critical infrastructure such as power plants, which play a crucial role in national energy distribution. Power plant monitoring systems that still use conventional authentication methods like static passwords and RFID have weaknesses such as the risk of theft, forgery, and access misuse. Furthermore, the lack of integration with Internet of Things (IoT) systems means that the monitoring process is not fully real-time and potentially causes delays in detecting intrusions and security threats. This situation highlights the need for a layered security system capable of accurately and dynamically verifying user identity. This research aims to implement facial recognition technology and the Time-Based One-Time Password (TOTP) algorithm as a layered authentication system for IoT-based power plant monitoring. The system is designed to combine facial biometric verification with a time-based OTP code that can be generated independently of an internet connection. The integration of these two methods is expected to improve access security by minimizing the risk of identity spoofing, credential theft, and cyberattacks. The methods used include system design, hardware and software implementation, and performance testing of authentication and IoT integration. The expected outcome of this research is the creation of a more adaptive, reliable security system capable of recording access activity in real time. Therefore, the implementation of IoT-based facial recognition and TOTP can be an effective solution for enhancing protection for power plant monitoring systems, which are vital national assets.