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Menampilkan 1–10 dari 14 artikel
Sistem Deteksi Bahasa Isyarat Alfabet Menggunakan Dataset American Sign Language (ASL) dan Algoritma Random Forest
Siti Farah Fakhirah
; Muhammad Fillah Alfatih
; Hasna Nabiilah Widiani
; Thoriq Muhammad Pasya
; Endang Purnama Giri
; Gema Parasti Mindara
Jurnal Sistem Informasi dan Ilmu Komputer
Vol 2
, No 4
(2024)
Introducing alphabetical sign language is necessary to bridge communication between deaf and hard-of-hearing people and their surrounding environment. This research aims to develop a sign language alphabet letter detection system based on American Sign Language (ASL). The research methods include data collection, feature extraction with OpenCV and Mediapipe, model development with Random Forest algorithm, and real-time system testing. The test results show that the developed system can achieve 9...
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Enhancing Low-Resolution Facial Images for Forensic Identification Using ESRGAN
Helena Dewi Hapsari
; Arya Dimas Wicaksana
; Hafiz Fadli Faylasuf
; Asa Yuaziva
; Rivanka Marsha Adzani
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Multilingual Education and Applied Linguistics
Vol 1
, No 4
(2024)
This research is motivated by the challenges in facial identification for forensic investigations due to poor image quality, especially from low-resolution CCTV recordings. Images with noise, low lighting, and suboptimal angles often hinder accurate facial recognition. This study aims to examine the effectiveness of the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) method in enhancing the quality of forensic facial images. The methodology consists of three main stages: data p...
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Penerapan Klasifikasi Gambar Buah dalam Aplikasi FruityLens Menggunakan Metode CNN
Bagus Hardika
; Mahesa Dzikri Kurniawan
; Muhammad Adzka
; Daffarizqy Prastowiyono
; Apik Banyubasa
; Gema Parasti Mindara
; Endang Purnama Giri
Jurnal Sistem Informasi dan Ilmu Komputer
Vol 2
, No 4
(2024)
This research develops a fruit classification system using Convolutional Neural Network (CNN) in the educational application FruityLens, which helps children recognize different types of fruits through image recognition. The application can identify four types of fruits: apple, banana, orange, and watermelon, utilizing an image dataset from open sources. The research methods include dataset collection, image pre-processing, CNN model training, and classification accuracy evaluation. The results...
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Design GiggleGate as Desktop Virtual Assistant with Face and Speech Recognition Authentication System
Jasmine Aulia Mumtaz
; Kinaya Khairunnisa Komariansyah
; Wildan Holik
; Reza Pratama
; Muhammad Galuh Gumelar
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Computer Technology and Science
Vol 1
, No 4
(2024)
In recent years, virtual assistants have become an integral part of everyday life, simplifying routine tasks and allowing users to focus on more important matters. This research aiming to design GiggleGate, a virtual desktop assistant integrated with both face and speech recognition technology to enhance authentication security. The objective is to develop an authentication system that not only verifies user identity but also provides a more intuitive experience and seamless interaction. The res...
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Real-Time Facial Emotion Detection Application with Image Processing Based on Convolutional Neural Network (CNN)
Hakim, Ghaeril Juniawan Parel
; Simangunsong, Gandi Abetnego
; Rangga Wasita Ningrat
; Jonathan Cristiano Rabika
; Muhammad Rafi' Rusafni
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Electrical Engineering, Mathematics and Computer Science
Vol 1
, No 4
(2024)
Facial Emotion Recognition (FER) is a key technology for identifying emotions based on facial expressions, with applications in human-computer interaction, mental health monitoring, and customer analysis. This study presents the development of a real-time emotion recognition system using Convolutional Neural Networks (CNNs) and OpenCV, addressing challenges such as varying lighting and facial occlusions. The system, trained on the FER2013 dataset, achieved 85% accuracy in emotion classification,...
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Automatic Passenger Counting System on Public Buses Using CNN YOLOv8 Model for Passenger Capacity Optimization
Ari Dian Prastyo
; Sharfina Andzani Minhalina
; Surya Agung
; Denty Nirwana Bintang
; Muhammad Yordi Septian
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Information Engineering and Science
Vol 1
, No 4
(2024)
This study presents the development and evaluation of an automatic passenger counting system for public buses using the YOLOv8 algorithm based on Convolutional Neural Networks (CNN). Accurate passenger counting plays a crucial role in optimizing public transportation operations, as it enables effective capacity management, reduces operational costs, and improves overall passenger comfort. Conventional manual counting methods are often inefficient, time-consuming, and prone to human error, partic...
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Implementasi Sistem Deteksi Kantuk Secara Real-Time Bagi Pengemudi Menggunakan Metode Eye Aspect Ratio
Mochammad Fadiil Thoriq
; Muhammad Fathi Ramdhana
; Desinta Nur Rahma
; Najla Amelia Putri
; Rafi Hilal Zahir
; Gema Parasti Mindara
; Endang Purnama Giri
Jurnal Sistem Informasi dan Ilmu Komputer
Vol 2
, No 4
(2024)
Traffic accidents are one of the leading causes of death worldwide, where drowsiness while driving is a significant factor that reduces driver alertness. This study develops a real-time driver drowsiness detection system using the Eye Aspect Ratio (EAR) method to avoid this. EAR calculates the ratio of the upper and lower eyelid distances to detect signs of drowsiness based on changes in eye shape. This system utilizes the OpenCV and Dlib libraries to identify faces and measure EAR, with a thres...
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Sistem Pengenalan Warna Berbasis OpenCV untuk Mendukung Aksesibilitas pada Individu dengan Buta Warna
Ferrol Azki Mashudi
; Dimas Akbar Tama
; Mario Raditya Nugroho
; Syifa Nursaadah
; Fatih Kawakib Kartono
; Gema Parasti Mindara
; Endang Purnama Giri
Jurnal Sistem Informasi dan Ilmu Komputer
Vol 2
, No 4
(2024)
This study develops an OpenCV-based color recognition system to support individuals with color blindness, aiming to enhance their independence in recognizing colors. The User-Centered Design (UCD) methodology was employed, allowing direct user feedback for development tailored to their needs. The developed system showed significant capability in detecting and identifying colors with a camera and analyzing them using OpenCV. The system provides text output to facilitate use by color-blind individ...
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Traspoter Application Development: Website-Based Automatic Garbage Classification Using CNN Method
Bima Julian Mahardika
; Budy Santoso
; Aulia Anggraeni
; Muhamad Ali Imron
; Anatasya Wenita Putri
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Multilingual Education and Applied Linguistics
Vol 1
, No 4
(2024)
This research focuses on the development of automatic waste classification by applying the Convolutional Neural Network (CNN) method in a web-based application. This system is designed to help the waste management process through automatic sorting between organic and inorganic waste, so that it can support recycling efforts and reduce environmental impacts. In its application, this application utilizes the CNN algorithm to analyze images and recognize the type of waste with good accuracy. The de...
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Development of Hand Gesture Detection Application for Slap Mosquito Game Based on Image Processing
Rajhaga Jevanya Meliala
; Nur Indah Chasanah
; Jonser Steven Rajali Manik
; Anggito Rangkuti Bagas Muzaqi
; Syah Bintang
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Electrical Engineering, Mathematics and Computer Science
Vol 1
, No 4
(2024)
The development of technology with digital image processing is often utilized to solve various problems in image processing, such as facial recognition, object detection, and interaction between users. In this study, we developed an interactive hand gesture-based game titled "Slap Mosquito" that utilizes image processing techniques to control the game through hand gestures. Using Rapid Application Development (RAD), Python, OpenCV, and Pygame methodologies, this game allows users to slap mosquit...
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