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All Journal Jurnal Pseudocode
Philip Faster Eka Adipraja
Asia Malang Institute of Technology and Business
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Optimizing YOLOv8 for Robusta Coffee Ripeness Detection in Unstructured Plantation Environments Annisa Zilvina Zahra; Philip Faster Eka Adipraja
Jurnal Pseudocode Vol 13 No 2 (2026): Volume 13 Nomor 2 September 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.2.95-107

Abstract

This study evaluates YOLOv8 performance for detecting Robusta coffee ripeness in unstructured Bondowoso plantations. Models trained on idealized data often degrade in chaotic real-world visual fields. To address this, this research establishes a realistic evaluation framework using a dual-source dataset strategy, leveraging public datasets for training and compiling a specialized primary field dataset from Bondowoso for independent testing under severe occlusion and dynamic illumination. Systematic tuning established an optimal configuration: 640x640 resolution, batch size of 8, and the AdamW optimizer. Internal testing achieved a robust mAP50 of 0.8144. However, in real-world deployment, the mAP50 dropped to 0.5254 due to environmental complexities. Despite this, the system maintained high precision (0.8390) and an exceptional standalone inference speed of 121.51 FPS. While high precision ensures reliable harvest assistance, the significant performance gap, characterized by a severe drop in recall, highlights architectural vulnerabilities in anchor-free detectors when handling dense clustering and foliage obstructions. These findings define the operational boundaries of lightweight detectors, providing a vital baseline for future domain adaptation and optimization in precision agriculture. Keywords: Bondowoso; Ripeness detection; Robusta coffee; Unstructured environment; YOLOv8.
Co-Authors Annisa Zilvina Zahra