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All Journal Bigint Computing Journal Jurnal Ilmu Komputer dan Informatika
Kardandi Alfarizi Siregar
Universitas Islam Negeri Sumatera Utara
Computer Science & IT Electrical & Electronics Engineering Engineering Mathematics

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Performance Evaluation of YOLOv8 for Vehicle License Plate Detection Using Standard Object Detection Metrics Kardandi Alfarizi Siregar; Bhagaskara Cahyadi; Legiman Samosir; Supiyandi Supiyandi
Bigint Computing Journal Vol 4 No 1 (2026)
Publisher : Ali Institute of Reseach and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/bigint.v4i1.1527

Abstract

Vehicle license plate detection is a crucial computer vision task for traffic monitoring, automated parking, and vehicle identification. This study evaluates the performance of a YOLO-based license plate detection system implemented in Python and executed on Google Colab to ensure reproducibility. A public dataset of vehicle images with variations in lighting conditions and viewing angles is used for testing. Performance is assessed using precision, recall, F1-score, mAP@0.5, and mAP@0.5:0.95. The results show a precision of 0.7653 and a recall of 0.6809, yielding an F1-score of 0.7206. The mAP@0.5 reaches 0.7776, while the mAP@0.5:0.95 drops to 0.3572. As a contribution, this work provides a simple and replicable baseline evaluation workflow for YOLO-based license plate detection using standard object-detection metrics. The large gap between mAP@0.5 and mAP@0.5:0.95 indicates that the model often detects the presence of license plates but struggles to localize them precisely under stricter IoU thresholds, highlighting localization sensitivity for small objects under real-world variations. These findings can guide future improvements through dataset diversification, augmentation, and higher-resolution training to enhance bounding box accuracy.
Analisis Sentimen Netizen Indonesia Terhadap Kampanye Penggunaan Kecerdasan Buatan Oleh Pemerintah Menggunakan Algoritma Naive Bayes Kardandi Alfarizi Siregar; Salsabila Nasution; Putri Nabawy
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 1 No. 4 (2025): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

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

Abstract

he development of artificial intelligence (AI) has encouraged the Indonesian government to adopt this technology in various public service sectors. However, the use of AI has received various responses from the public, especially on social media. This study aims to analyze the sentiment of Indonesian netizens towards the government's campaign to use AI using the Naive Bayes algorithm. Data were collected from the Twitter platform and analyzed through preprocessing, sentiment classification, and model evaluation stages. The results of the study show that the majority of netizen sentiment is negative, with concerns regarding injustice for creative workers, lack of regulation, and the use of AI for political interests. This study is expected to be an input for the government in designing a more ethical and inclusive AI adoption policy.
Co-Authors Bhagaskara Cahyadi Legiman Samosir Putri Nabawy Salsabila Nasution Supiyandi Supiyandi