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All Journal Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) International Journal of Research in Vocational Studies (IJRVOCAS)
Nst, Tuti Adi Tama
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Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Development of an IoT-Based System for River Siren Control and Height Detection Utilizing LoRa and Solar Cell Technology Mardiana; Yuvina; Nst, Tuti Adi Tama; Benu, Siti Maretia
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 3 No. 4 (2024): IJRVOCAS - Special Issues - International Conference on Science, Technology and
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v3i4.45

Abstract

We need a tool that can measure river water levels automatically based on IoT so that water level data can be received in real time. This tool uses an Arduino microcontroller which functions to convert analog data into digital by measuring water level using an ultrasonic sensor so that the data can be converted into digital water level data and displayed via the internet and a buzzer or siren as a danger warning when the water level rises high as well as water level data. can be monitored as a whole. Apart from that, this tool is equipped with LoRa communication. This LoRa can send signals as far as 15 km without obstructions, so even if there is no internet, this tool can still work and can be used in areas without electricity because it uses solar cells as a power supply. If the water reaches the maximum limit, the siren will sound and stop again when the water in the river is at normal level.
Neural Network Algorithm for Biometric Analysis of Human Retina Image Nst, Tuti Adi Tama; DEA, Bambang Hidayat; Andini, Nur; Zakaria, Hasballah
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 5, No 2 (2024)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v5i2.20000

Abstract

Identity recognition is an important process because many systems require a valid user identity for security and access control. Identity recognition such as passwords, signatures, id cards have some weaknesses that are they can be duplicated, stolen, forgotten, and even lost. Identity recognition using biometric techniques is known to be more reliable. Biometric technique is a recognition and classification technique that uses human behavior and physical atributes. In this research, a non-realtime simulation system is designed to identify a person by biometric of retina image. The system can identify one's identity through pattern of retinal blood vessels. The processes of this system divided into two stages that are training stages and testing stage. The identification process begins with prepocessing retinal photo. Biometric features extracted by using Discrete Orthonormal S Transform (DOST). Biometric classification by using Adaptive Resonance Theory 2 (ART 2) with unsupervised learning process that can recall previously learned patterns . The results obtained from this study showed 65% of accuracy  for the right retina image and 50% of accuracy for the left retina image. Computing time is about 6 seconds. Further development is needed to improve the accuracy of the system as a security and access control systems.
Co-Authors Benu, Siti Maretia DEA, Bambang Hidayat MARDIANA Nur Andini yuvina Zakaria, Hasballah