<![CDATA[Abstract : Brain tumor detection is an important task in medical image analysis and diagnosis. In this study, we propose a brain tumor detection model based on deep learning with YOLOv7 which can accurately detect brain tumors. The dataset used is divided into training and testing datasets. Pre-processing techniques are carried out on the dataset to get maximum results. Research produces a detection model for brain tumors. The model achieved a mAP of 93.2%, precision of 91.4%, recall of 90.2% and F1-score of 90.8%. The results demonstrate the effectiveness of the proposed model in accurately detecting brain tumors, which can assist early diagnosis and treatment planning. Abstrak : Deteksi tumor otak adalah tugas penting dalam analisis dan diagnosa citra medis. Dalam penelitian ini, kami mengusulkan model deteksi tumor otak berdasarkan deep learning dengan YOLOv7 yang dapat mendeteksi tumor otak secara akurat. Dataset yang digunakan terbagi menjadi dataset pelatihan dan pengujian. Teknik pra proses dilakukan pada dataset untuk mendapatkan hasil yang maksimal. Penelitian menghasilkan model deteksi untuk tumor otak. Model mencapai mAP 93,2%, precision 91,4%, recall 90,4%, dan F1-score 90,8%. Hasilnya menunjukkan keefektifan model yang diusulkan dalam mendeteksi tumor otak secara akurat, yang dapat membantu diagnosis dini dan perencanaan perawatan.]]>
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