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All Journal Bigint Computing Journal JITCoS : Journal of Information Technology and Computer System
Legiman Samosir
Universitas Islam Negeri Sumatera Utara
Computer Science & IT Control & Systems Engineering

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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.
Application of Deterministic Simulation Modeling for Capital Structure Robustness Testing: A Case Study in the Capital-Intensive Industry (AGII) Legiman Samosir; Haikal Habibi Siregar
Journal of Information Technology and Computer System Vol. 2 No. 1 (2026): June
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v2i1.80

Abstract

In the capital-intensive sector, the strategic management of capital structure is often constrained by cost rigidity, where high fixed costs magnify the impact of demand volatility on corporate solvency. This study addresses the methodological gap in static financial analysis by applying Deterministic Simulation Modeling to conduct a Robustness Test on PT Aneka Gas Industri Tbk (AGII). The primary objective is to measure the structural resilience of the firm against operational shocks specifically demand fluctuations attributed to the bullwhip effect and to evaluate the efficacy of refinancing as a risk mitigation strategy. Using audited financial data, the simulation executes specific "what-if" scenarios to project changes in Net Income, Interest Coverage Ratio (ICR), and Financial Distress probability based on the Springate S-Score. The empirical results reveal a significant structural vulnerability: a moderate revenue decline of 5% plunges the baseline performance into a net loss of IDR 5,027 million, confirming the detrimental impact of high operating leverage. However, the simulation demonstrates that a strategic refinancing intervention, reducing the cost of debt from 8.1% to 6.75%, effectively transforms the company’s risk profile from fragile to robust. This optimization not only maintains profitability under stress but also significantly lowers the Break-Even Point (BEP), thereby widening the Margin of Safety. The study concludes that deterministic simulation offers a superior, forward-looking framework for management to identify financial "breaking points" and implement proactive liability management to ensure sustainability amidst economic uncertainty.
Co-Authors Bhagaskara Cahyadi Haikal Habibi Siregar Kardandi Alfarizi Siregar Supiyandi Supiyandi