DIAGNOSIS AWAL PADA PENYAKIT ALZHEIMER MENGGUNAKAN METODE VGG-19 CONVOLUTIONAL NEURAL NETWORK (CNN) BERDASARKAN CITRA MRI DARI OTAK MANUSIA

Dhany Umar, . (2022) DIAGNOSIS AWAL PADA PENYAKIT ALZHEIMER MENGGUNAKAN METODE VGG-19 CONVOLUTIONAL NEURAL NETWORK (CNN) BERDASARKAN CITRA MRI DARI OTAK MANUSIA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Alzheimer's dementia is now the 7th leading cause of death globally and is one of the diseases with the highest costs to society. Therefore the topic of Alzheimer's is very important and needs more attention. To overcome this problem, we need a system that can make it easier for doctors or health workers to make an early diagnosis of Alzheimer's disease, because an accurate and timely diagnosis can minimize the dysfunction that accompanies cognitive loss in people with Alzheimer's disease. Convolutional Neural Network (CNN) which is a method for image classification and object detection. CNN is the best method that is often used in solving image classification and object detection problems. In this research, the early diagnosis process for Alzheimer's disease will be carried out using a collection of Magnetic Resonance Imaging (MRI) image data of the human brain to classify 4 classes of Alzheimer's disease, namely Non Demented, Very Mild Demented, Mild Demented and Moderate Demented using the CNN method with architecture VGG-19 to perform image classification. Keywords : Alzheimer, Image Classification, Convolutional Neural Network (CNN), VGG-19, Deep Learning

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1910314032] [Pembimbing: Fajar Rahayu] [Penguji 1: Achmad Zuchriadi] [Penguji 2: Henry Binsar Hamonangan Sitorus]
Uncontrolled Keywords: Keywords: Alzheimer, Image Classification, Convolutional Neural Network (CNN), VGG-19, Deep Learning
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Teknik > Program Studi Teknik Elektro (S1)
Depositing User: Dhany Umar
Date Deposited: 13 Feb 2023 06:37
Last Modified: 13 Feb 2023 06:39
URI: http://repository.upnvj.ac.id/id/eprint/22383

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