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All Journal Journal of Intelligent Systems Conference SENATIK STT Adisutjipto Yogyakarta JSI (Jurnal sistem Informasi) Universitas Suryadarma JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research Jurnal Nasional Teknik Elektro dan Teknologi Informasi CKI On Spot Journal Of Artificial Intelligence And Software Engineering Jurnal Teknologi Industri JURNAL MITRA MANAJEMEN Jurnal Mahasiswa Informatika dan Desain (JURMASIN) Jurnal Bakti Dirgantara
Muryan Awaludin
Universitas Dirgantara Marsekal Suryadarma
Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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Optimizing YOLOv8 Architecture and Augmentation for Efficient License Plate Detection Muryan Awaludin; Yoke Lucia R Rehatalanit
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 15 No 2: Mei 2026 (dalam proses)
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v15i2.24886

Abstract

Automatic Number Plate Recognition (ANPR) is crucial for intelligent transportation systems but often falters in real-world conditions due to environmental variations. This study constructed a robust and computationally efficient vehicle license plate detection system that achieved high accuracy under diverse real-world challenges and was deployable on resource-constrained edge hardware for real-time operation. The proposed holistic framework integrated three key components: (a) the creation of the Dynamic Vehicle License Plate Dataset (DVLPD) v1.0, containing 866 annotated images with variations in lighting, weather, and camera angles; (b) the implementation of a targeted data augmentation pipeline employing geometric and photometric transformations to enhance model robustness; and (3) the architectural optimization of a You Only Look Once (YOLO) version 8 or YOLOv8 model through pruning, quantization, and hyperparameter tuning specifically for edge deployment. The optimized model achieved a mean average precision (mAP) of 91% on the test set. When deployed on a Raspberry Pi 4 in a prototype parking system, it demonstrated practical viability with an inference latency of 0.4 seconds per frame and an error rate of 4.2%. The results validate that the integration of a diverse dataset, strategic augmentation, and model optimization can yield an accurate and efficient ANPR solution suitable for real-time edge applications. Future work will focus on expanding the dataset to include more extreme conditions for greater generalization.
Penerapan Algoritma Convolutional Neural Network untuk Meningkatkan Akurasi Pengenalan Bahasa Isyarat Indonesia Muryan Awaludin; Yohannes Dewanto
JSI (Jurnal Sistem Informasi) Universitas Suryadarma Vol. 13 No. 1 (2026): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Fakultas Ilmu Komputer dan Desain - Unsurya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v13i1.1737

Abstract

Tujuan dari penelitian ini adalah untuk memasukkan algoritma Convolutional Neural Network (CNN) ke dalam sistem pengenalan bahasa isyarat statis Indonesia Bahasa Isyarat (BISINDO). Latar belakang penelitian adalah pentingnya pengembangan teknologi yang membantu penyandang tunarungu berkomunikasi dengan masyarakat umum. Metode ini menggunakan arsitektur CNN khusus yang terdiri dari lapisan konvolusi, pooling, dan seluruhnya terhubung. Dataset yang digunakan terdiri dari 1.500 gambar 26 huruf alfabet BISINDO, yang telah diperluas untuk meningkatkan variasi dan ketahanan model melalui proses augmentasi data. Hasil dari eksperimen menunjukkan bahwa model yang diusulkan dapat beroperasi dengan sangat baik. Akurasi deteksi model sebesar 98,5% pada data pengujian. Hasil evaluasi tambahan menunjukkan bahwa model memiliki nilai akurasi sebesar 97,8%, nilai recall sebesar 98,2%, dan nilai F1-Score sebesar 98,0%. Hasil ini menunjukkan bahwa CNN tidak hanya akurat tetapi juga handal dalam mengklasifikasikan bentuk tangan yang kompleks dalam BISINDO. Oleh karena itu, sangat mungkin untuk CNN digunakan dalam sistem translator real-time.
Co-Authors Achmad Ramadhany Alcianno G. Gani Alfatonah, Siti Amelia, Lesti Vicky Anggito Setiawan Aji Avrilia, Nuris Ayu Yudianingsih Bekti Yulianti Betesda Betesda Christoper Dendra Dedi Setiadi Dewanto, Yohanes Dimpo Sinaga Efiyah, Efiyah F Firdaus, Venus F. Firdaus, Venus Fadillah, Fadli Fauziyah Putri, Dewi Fitria Risyda Fitria Risyda Hari Bagus Mantik Hari Purwanto Herlina, Nike Herny Nurhayati Ilham, Ilham Kudratul Alam Iman Nugroho, Mohammad Irianti, Widiyaningrum Ivan Ismail Jasudin Jehan Saptia Kurnia Joko Habib Kaidafi Joni Efendi, Joni Komalasari, Weni kurnia, jehan Kurnia, Jehan Saptia Kusuma Wijaya, Dedi Longdong, Marcelino Paul Edwil Lukman Cahyono Mega Wahyuningsih Milakurnianingsih Muhammad Ali Machrus Muhammad Ichsan Nudin Muhammad Solehfuddin Muhyi, Annissa Muksin, Abdullah Mulyana, Andi Murtomy Nadeak, Pelita Nafisah Julia Putri Nasukha, Gerly Nugroho, Mohammad Iman Nurlita, Rika Nurwijayanti Nuryadi, Hepi Paltrow Artahsasta Talanila Peniarsih, Peniarsih Permadi Yoga Mitra Perdana Pribadi, Gerly Nasuha Pribadi, Gerly Nasukha Raden Ramadhan Putra Hermawan Raessang, Suhaimi Arung Raveena, Rinta Ridyustia Rina Novia Priyanti Rismen Sinambela Rohayati, Siti Romi Satria Wahono Safri Safri Sarpan, Sarpan Sinaga, Dimpo Suci Eka Puspitasari, Fitriana Sutarno Syachroni Syahrul Syahrul Syahrul Syalwa Daniarsyah Tanjung, Rudy Tata Sumitra Tateng Sukendar Tegar Prakoso, Alessandro Verdi Yasin Verdi Yasin Verdi Yasin Wahyuningsih, Mega Wasiyo, Yohanes Windy Maharani, Septania Yohannes Dewanto Yoke Lucia R Rehatalanit Yoke Lucia Renica Rehatalanit Yolanda, Natasya Erent Yolanda, Natasya Erent Yuhanes Zico Rahwanto Yulisa Gardenia Yusuf Fadila Husein Zebua, Martalena