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All Journal Jurnal ICT : Information Communication & Technology Jurnal Sains Indonesia Jurnal Sains Teknologi dan Sistem Informasi Journal of Scientech Research and Development Jurnal Teknik Mesin, Industri, Elektro dan Informatika AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan International Journal of Multilingual Education and Applied Linguistics International Journal of Computer Technology and Science International Journal of Information Engineering and Science International Journal of Electrical Engineering, Mathematics and Computer Science
Gema Parasti Mindara
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Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Pendeteksi Penggunaan Sabuk Pengaman Real Time Untuk Pengemudi Menggunakan Metode YOLOV5 Keysha Maulina Halimi; Tiara Ariyanto Putri; Muhammad Rahmat Maryadi; Rayhan Ananda Hafiz Pradipta; Hassan Nasrallah Matouq; Endang Purnama Giri; Gema Parasti Mindara
AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan Vol. 2 No. 2 (2024): Jurnal AI dan SPK : Jurnal Artificial Inteligent dan Sistem Penunjang Keputusan
Publisher : CV. Shofanah Media Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kecelakaan lalu lintas merupakan salah satu masalah yang sangat merugikan dan membutuhkan penanganan yang serius. Kecelakaan mobil menempati peringkat dua teratas kendaraan yang sering mengalami kecelakaan lalu lintas. Salah satu upaya yang dapat digunakan untuk meminimalisir akibat dari kecelakaan berkendara adalah menggunakan sabuk pengaman. Mengenakan sabuk pengaman mencegah tubuh penumpang bertabrakan dengan struktur rangka mobil, benda lain di dalam mobil, atau penumpang lain di dalam mobil yang sama. Meskipun penggunaan sabuk pengaman saat berkendara memiliki dampak yang besar, masih banyak pengendara yang masih menyepelekan pentingnya penggunaan sabuk pengaman dalam keselamatan berkendara di jalan raya. Pada penelitian ini, pendeteksian penggunaan sabuk pengaman secara realtime untuk pengemudi mobil di jalan raya telah dilakukan dengan menggunakan metode deep learning YOLOv5. Tujuan dari penelitian ini adalah untuk mengembangkan dan mengimplementasikan sistem pendeteksian penggunaan sabuk pengaman secara real-time bagi pengemudi mobil di jalan raya menggunakan model YOLOv5 sebagai salah satu usaha untuk meminimalisir risiko terjadinya kecelakaan lalu lintas.
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.
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): October: International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i4.113

Abstract

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 research employs a development methodology to create and implement the system, which integrates face recognition via OpenCV and speech recognition via a Python library. The findings indicate that the integration of these technologies enhances security and user experience by offering dual-factor authentication. The system is expected to contribute to more secure and accessible virtual assistant applications, offering both a practical and efficient solution for users. The implications of this study suggest that the combination of face and speech recognition can provide an effective means to protect user privacy and improve the overall functionality of desktop assistants.
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): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.121

Abstract

This study presents the development of an automatic passenger counting system for public buses using YOLOv8 based on Convolutional Neural Networks (CNN). The system detects and counts passengers in real-time to optimize bus capacity and enhance operational efficiency. Results indicate that the system achieves high accuracy in the front camera view (confidence score of 0.82). However, in the rear camera view the accuracy slightly decreases (confidence score of 0.76) due to object overlap, emphasizing the importance of proper camera placement. The system offers potential improvements in bus capacity management, reduced operational costs, and enhanced passenger comfort. These findings contribute to advancing smarter and more efficient public transportation systems.
E-Commerce FreezeMart untuk Penjualan Frozen Food dengan Sistem Rekomendasi Berbasis Content-Based Filtering Aditya Wicaksono; Setiady Ibrahim Anwar; Muhammad Al Amin; Rizki Juliansyah; Arya Dimas Wicaksana; Gema Parasti Mindara
Jurnal ICT: Information Communication & Technology Vol. 25 No. 1 (2025): JICT-IKMI, July, 2025
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

Kemajuan teknologi digital mendorong perkembangan platform e-commerce yang memudahkan transaksi secara cepat dan fleksibel. Penelitian ini membahas FreezeMart, situs e-commerce untuk penjualan makanan beku yang dilengkapi sistem rekomendasi terpersonalisasi. Sistem memanfaatkan content-based filtering dan analisis histori pembelian untuk menyarankan produk yang relevan. Masukan pengguna diproses menggunakan teknik Natural Language Processing seperti TF-IDF untuk mencocokkan preferensi dengan atribut produk. Pengembangan dilakukan dengan metode Agile Scrum dan mencakup tiga peran utama: guest, customer, dan admin. Pengguna dapat mengelola pesanan dan memperoleh rekomendasi sesuai kebutuhan, sementara admin bertanggung jawab atas pengelolaan sistem. Sistem rekomendasi yang diimplementasikan terbukti mampu meningkatkan pengalaman belanja pengguna. Pada tahap selanjutnya, pengembangan sistem dapat difokuskan pada penerapan collaborative filtering serta peningkatan kinerja platform.
Pengembangan Sistem Informasi Keterbukaan Desa (SiKD) Menggunakan Metode Spiral Berbasis Website Bayu Widodo; Uding Sastrawan; Gema Parasti Mindara; Wien Kuntari; Budi, Budi
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 4 No. 2 (2024): Oktober 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v4i2.3056

Abstract

The development of the Village Openness Information System (SiKD) aims to encourage transparency and community participation in managing village government. This research highlights the importance of using information technology in improving the performance of village governments, especially in Mekarsari Village (Sukabumi), Garumukti Village (Garut), and Bantar Kulon Village (Pekalongan). These three villages have mountainous geographical characteristics and limited transportation access, but have great potential in the agricultural sector. The research methodology uses the Spiral Model which involves the stages of problem identification, planning, risk analysis, engineering, construction and release, and user evaluation. Data collection was carried out through observation and interviews with village officials and community leaders. The research results show that the development of SiKD with the Spiral Model allows the preparation of detailed and systematic digital data, which is presented in the form of a dashboard. The SiKD dashboard facilitates measurable and sustainable village development planning, focuses on utilizing village funds according to residents' needs, and accelerates the achievement of Sustainable Development Goals (SDGs). The implementation of SiKD is expected to increase information transparency and the performance of village government services effectively and efficiently.
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