IMPLEMENTASI ALGORITMA YOU ONLY LOOK ONCE (YOLO) PADA CITRA MAGNETIC RESONANCE IMAGING (MRI) UNTUK DETEKSI TUMOR OTAK

MONICA, CATRIN and Sutarno, Sutarno (2025) IMPLEMENTASI ALGORITMA YOU ONLY LOOK ONCE (YOLO) PADA CITRA MAGNETIC RESONANCE IMAGING (MRI) UNTUK DETEKSI TUMOR OTAK. Undergraduate thesis, Sriwijaya University.

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Abstract

Limitations of visual analysis by medical personnel. This study implements the YOLOv8 algorithm, a state-of-the-art deep learning method for object detection, to identify three types of brain tumors, namely glioma, meningioma, and pituitary. The dataset was obtained from Kaggle, then processed through the preprocessing and augmentation stages with Roboflow, and trained using several YOLOv8 variants (n, s, m, l) with hyperparameter tuning. Evaluation using precision, recall, mAP50, and mAP50-95 metrics. The results show that the YOLOv8s-E100-B64 model produces the best performance with a precision of 0.943, recall of 0.876, mAP50 of 0.94, and mAP50-95 of 0.744. This model is proven to be fast, accurate, and stable in all stages of testing, making it potential as a diagnostic tool based on MRI images. Keywords: Brain Tumor, YOLOv8, MRI Image, Deep Learning, Roboflow

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Tumor Otak, YOLOv8, Citra MRI, Deep Learning, Roboflow
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Catrin Monica
Date Deposited:	03 Sep 2025 05:19
Last Modified:	03 Sep 2025 05:19
URI:	http://repository.unsri.ac.id/id/eprint/183564

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