Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Algoritme Jurnal Mahasiswa Teknik Informatika
Julius Pratama
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Pengenalan Mata Uang Secara Real-Time Menggunakan Yolov8 Nano Dan Raspberry Pi Julius Pratama; Jusia Amanda Ginting
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 7 No 1 (2026): October 2026 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v7i1.16636

Abstract

Blind and low vision individuals experience difficulties in independently recognizing Indonesian banknote denominations, which may lead to errors in daily financial transactions. This study aims to develop an Internet of Things-based smart assistive device to identify Indonesian banknote denominations in real-time. The proposed system employs Raspberry Pi 4 as the processing unit, an OV5647 camera for image acquisition, an HC-SR04 ultrasonic sensor for distance measurement, YOLOv8 Nano for banknote detection, and fuzzy logic as a decision-making mechanism based on the confidence score and object distance. The detection results are delivered through audio output and stored in Firebase Realtime Database, allowing monitoring through a web-based dashboard. The dataset consists of seven Indonesian banknote denominations, namely Rp1,000, Rp2,000, Rp5,000, Rp10,000, Rp20,000, Rp50,000, and Rp100,000. Experimental results show that the proposed system achieves a detection accuracy of 91.43% with an average response time of 1.36 seconds. Therefore, the developed system is expected to improve the independence of blind and low vision individuals in conducting daily financial transactions.
Co-Authors Jusia Amanda Ginting