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Journal : International Journal of Electrical Engineering, Mathematics and Computer Science

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): December : International Journal of Electrical Engineering, Mathematics and Com
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v1i4.108

Abstract

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 mosquitoes virtually in real-time through hand gesture recognition that is read by the camera and translated into in-game actions. RAD allows rapid development iterations and improvements based on user feedback, which is essential for improving system responsiveness and accuracy. This study focuses on detection precision, system responsiveness, and the impact of lighting on game performance, as measured using frames per second (FPS) and user gameplay results. The test results show that optimal lighting meets high detection accuracy, while low lighting conditions have a negative impact on accuracy and responsiveness. The results of this study provide insights for further development of gesture-based applications, especially regarding the importance of optimizing technical parameters and RAD methodology in improving user experience.
Analysis and Testing of the Combox Web Application System Using Black Box Testing with the Equivalence Partitioning Method Dini Nurul Azizah; Ibnu Aqil Mahendar; Muhammad Fillah Alfatih; Setiady Ibrahim Anwar; Nabil Malik Al Hapid; Aditya Wicaksono; Gema Parasti Mindara
International Journal of Electrical Engineering, Mathematics and Computer Science Vol. 1 No. 4 (2024): December : International Journal of Electrical Engineering, Mathematics and Com
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v1i4.118

Abstract

This research focuses on evaluating the Combox web application, a digital tool designed to help Food and Beverage (F&B) business owners strengthen their online presence. The analysis was carried out through Black Box Testing, specifically using the Equivalence Partitioning method, to assess core functionalities like login, logout, product management, and pagination. The findings reveal that while most features function as intended, there are issues with product addition and editing, as well as pagination when no data is available. These results highlight areas that need refinement to improve the application’s reliability and user experience. In summary, this research supports the advancement of a digital platform that enables F&B businesses to harness technology effectively in today’s competitive landscape.
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): December : International Journal of Electrical Engineering, Mathematics and Com
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v1i4.123

Abstract

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, demonstrating high performance in detecting happiness, sadness, and surprise. The results highlight the system's effectiveness in real-time applications, offering potential for use in mental health and customer behavior analysis.
Co-Authors Achmad Syahmi Rasendriya Aditya Wicaksono Alya Putri Salsabila Anatasya Wenita Putri Anggito Rangkuti Bagas Muzaqi Anka Luffi Ramdani Ari Dian Prastyo Arya Dimas Wicaksana Asa Yuaziva Aulia Anggraeni Azhar Nadhif Annaufal BAYU WIDODO Bima Julian Mahardika Budi Budi Budy Santoso Capriandika Putra Susanto Denty Nirwana Bintang Diana Putri Rahmani Dini Nurul Azizah Endang Purnama Giri Ester Olivia Silalahi Fauzi Adi Saputra Fikri Saputra Hafiz Fadli Faylasuf Hakim, Ghaeril Juniawan Parel Hassan Nasrallah Matouq Helena Dewi Hapsari Ibnu Aqil Mahendar Jasmine Aulia Mumtaz Joddy Lintar Balle Jonathan Cristiano Rabika Jonser Steven Rajali Manik Jovita Nabilah Azizi Kaisar Renaisance Al-Ars Kanaya Sabila Azzahra Keysha Maulina Halimi Kinaya Khairunnisa Komariansyah Kuntari, Wien Luthfi Dika Chandra Marsya Halya Alfrida Merry Ardelia Wirastuti Mia Putri Yeza Mira Fitria Dewi Mochamad Farras Fauzan Mochammad Alwan Al Ataya Muhamad Ali Imron Muhammad Al Amin Muhammad Farhan Fahrezy Muhammad Fillah Alfatih Muhammad Galuh Gumelar Muhammad Ilham Nurfajri Muhammad Naufal Ardhani Muhammad Rafi' Rusafni Muhammad Rahmat Maryadi Muhammad Shubhi Maulana Muhammad Yordi Septian Muthia Nurul Sa'adah Nabil Malik Al Hapid Nabila Fakhiratunisa Nasywa Shafa Salsabila Naufal Alif Falah Nur Iman Nugraha Nur Indah Chasanah Nur Rahma Ditta Zahra Rafli Damara Raisa Mutia Thahir Rajhaga Jevanya Meliala Rangga Wasita Ningrat Rayhan Ananda Hafiz Pradipta Reza Pratama Ridwan Siskandar Rivanka Marsha Adzani Rizki Juliansyah Rizky Fadlurohman Setiady Ibrahim Anwar Sharfina Andzani Minhalina Simangunsong, Gandi Abetnego Surya Agung Syah Bintang Tiara Ariyanto Putri Tria Febriayanti Tria Febriyanti Uding Sastrawan Vandame Ronald Suhada Wahyu Mustika Aji Wildan Holik