Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal JTEV (Jurnal Teknik Elektro dan Vokasional KOMPUTIKA - Jurnal Sistem Komputer
Eniman Yunus Syamsuddin
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Perancangan Algoritma Optimasi Pada Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Pengolahan Citra Sugeng Sugeng; Eniman Yunus Syamsuddin
Komputika : Jurnal Sistem Komputer Vol 9 No 2 (2020): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v9i2.3682

Abstract

Pengenalan plat nomor kendaraan khususnya plat nomor Indonesia menggunakan pengolahan citra belum banyak digunakan secara luas. Baru dari pemerintah yang memanfaatkan pengenalan plat nomor kendaraan dengan pengolahan citra sebagai alat otomatis tilang elektronik yang dipasang pada rambu lalu lintas. Beberapa penelitian pengenalan plat nomor dilakukan untuk menghasilakan pengenalan yang terbaik. Pada penelitian ini dibuat sebuah metoda untuk melakukan optimasi pengenalan karakter menggunakan pengolahan citra. Metoda ini menganalisa bentuk kemiripan karakter terhadap karakter utama plat nomor kendaran serta menganalisa dimana posisi karakter tersebut berada. Metoda ini mampu meningkatkan pengenalan karakter plat nomor kendaraan menggunakan pengolahan citra dengan presentase peningkatan akurasi dari 80% menjadi 94%.
Designing Automatic Number Plate Recognition (ANPR) Systems Based on K-NN Machine Learning on the Raspberry Pi Embedded System Sugeng Sugeng; Eniman Yunus Syamsuddin
JTEV (Jurnal Teknik Elektro dan Vokasional) Vol 5, No 1.1 (2019): Edisi khusus prosiding FORTEI 2019
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (799.12 KB) | DOI: 10.24036/jtev.v5i1.1.106135

Abstract

Research on vehicle number plate recognition or Automatic Number Plate Recognition (ANPR) is mostly done by researchers to produce an introduction that has high accuracy. Several methods of introduction are carried out such as introduction to edge detection and morphology, relationship analysis between objects, machine learning and deep learning. In this research a K-NN machine learning ANPR system was developed in character recognition. The method of analyzing relationships between objects is used to localize number plates. The system that was developed also added an artificial intelligence to be able to find out the fault of the number plate recognition and fix it based on the position of the character group in the number plate. The ANPR system is designed to be an Embedded system so that it can be implemented to be able to carry out the identification of two-wheeled and four-wheeled vehicle license plates. The ANPR system was also developed to be used in the parking management system. In this research the recognized number plates are limited to private number plates in Indonesia. In testing, the system is made capable of recognizing the number plates of two-wheeled vehicles and four-wheeled vehicles on vehicles that have a standard license plate according to Polri regulations, both in the font type and the number plate writing format. The results of vehicle number plate recognition reached an accuracy of 98%.
Co-Authors Sugeng Sugeng