Spare Part Detection and Counting System using YOLOv8 - Prasetyo, Ariansyah Aryo; Wibowo, Dwi Agung; Rizki, Afian Syafaadi; Karima, Cahya; Permatasari, Nindy (Cattleya Darmaya Fortuna, 2025)
This research aims to create a spare part detection and counting system to assist employees in calculating stock quantities. The system utilizes artificial intelligence (AI) and computer vision with the YOLOv8 algorithm. The research was conducted at PT Rezki Batulicin Transport Site Sebamban, a company specializing in land transportation services, particularly for coal mining products. The company is located in Tanah Bumbu Regency, South Kalimantan. The spare part detection and counting system has been successfully implemented. Evaluation results show an F1-score reaching a maximum value of approximately 0.86 at a confidence threshold of around 0.385. Precision values remained above 0.8 for most of the confidence range, while maximum recall reached 0.95.