KLASIFIKASI TUMOR OTAK PADA CITRA MAGNETIC RESONANCE IMAGING MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK BERBASIS ARSITEKTUR VGG-16

NUGRAHA, FARHAN and Fachrurrozi, Muhammad (2025) KLASIFIKASI TUMOR OTAK PADA CITRA MAGNETIC RESONANCE IMAGING MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK BERBASIS ARSITEKTUR VGG-16. Undergraduate thesis, Sriwijaya University.

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Abstract

Tumor otak merupakan penyakit serius yang memerlukan deteksi dini agar dapat ditangani dengan tepat dan efektif. Magnetic Resonance Imaging (MRI) sering digunakan dalam diagnosis tumor otak, namun analisis manual masih memiliki keterbatasan, seperti ketergantungan pada keahlian radiologi serta subjektivitas dalam interpretasi hasil.Penelitian ini bertujuan untuk mengembangkan model klasifikasi tumor otak berbasis deep learning menggunakan Convolutional Neural Network berbasis arsitektur VGG-16. Penelitian ini menerapkan metode transfer learning, data augmentation, dan fine-tuning pada beberapa lapisan akhir untuk meningkatkan kemampuan dalam mengekstraksi fitur citra MRI. Hasil evaluasi model 2 menggunakan confusion matrix menunjukkan performa yang sangat baik, dengan accuracy 98%, precision 99%, recall 97%, dan F1-score 98%.Dengan pencapaian tersebut, model ini diharapkan dapat menjadi alat bantu yang andal bagi tenaga medis dalam mengklasifikasi tumor otak secara lebih akurat dan efisien. Selain itu, penerapan model ini dapat membantu mengurangi beban kerja tenaga medis serta meningkatkan kualitas layanan kesehatan dalam diagnosis berbasis pencitraan medis. Kata kunci: Tumor Otak, Magnetic Resonance Imaging (MRI), Deep Learning, Convolutional Neural Network (CNN), VGG-16, Transfer Learning, Data Augmentation, Fine-Tuning, Klasifikasi, Confusion Matrix.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Kata kunci: Tumor Otak, Magnetic Resonance Imaging (MRI), Deep Learning, Convolutional Neural Network (CNN), VGG-16, Transfer Learning, Data Augmentation, Fine-Tuning, Klasifikasi, Confusion Matrix.
Subjects:	L Education > L Education (General) > L7-991 Education (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Farhan Nugraha
Date Deposited:	15 Apr 2025 02:31
Last Modified:	15 Apr 2025 02:31
URI:	http://repository.unsri.ac.id/id/eprint/170298

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