PERANCANGAN MODEL CONVOLUTIONAL NEURAL NETWORK 1-DIMENSI UNTUK MENINGKATKAN KINERJA KLASIFIKASI ATRIAL FIBRILLATION

ESAFRI, RIA and Nurmaini, Siti (2021) PERANCANGAN MODEL CONVOLUTIONAL NEURAL NETWORK 1-DIMENSI UNTUK MENINGKATKAN KINERJA KLASIFIKASI ATRIAL FIBRILLATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Atrial Fibrillation (AF) adalah salah satu jenis aritmia yang dapat menyebabkan terjadinya stroke dan gagal jantung jika tidak segera diatasi. Ciri umum dari penyakit AF yaitu tidak adanya gelombang P pada sinyal EKG dan interval RR yang tidak beraturan. Penelitian ini menyajikan klasifikasi AF menggunakan metode Convolutional Neural Network 1-Dimensi (CNN 1-Dimensi). Langkah pertama, dilakukan persiapan data yang digunakan yaitu AF Challange 2017, China Challenge 2018, MIT-BIH Atrial Fibrillation, Dataset dari Chapman University and Shaoxing Zhejiang. Kemudian dilanjutkan dengan pra-pemrosesan data dengan menggunakan Discrete Wavelete Transform (DWT), normalisasi sinyal, dan segmentasi sinyal. serta diakhiri dengan proses klasifikasi menggunakan arsitektur CNN 1-Dimensi. Hasil terbaik didapatkan dengan menggunakan pembagian data K-Fold Cross-Validation, pada klasifikasi 2 kelas (normal dan AF) didapat akurasi 99,80%, sensitivitas 99,70%, spesifikasi 99,67%, presisi 99,61%, f1 score 99,65% dan error 0,19%. Sedangkan, pada klasifikasi 3 kelas (normal, AF, dan Non-AF) didapat akurasi 96,54%, sensitivitas 94,14%, spesifikasi 97,34%, presisi 94,05%, f1 score 94,09% dan error 3,45%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Atrial Fibrillation, 1-Dimensional Convolutional Neural Network
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: Ria Esafri
Date Deposited: 09 Jul 2021 07:48
Last Modified: 09 Jul 2021 07:48
URI: http://repository.unsri.ac.id/id/eprint/49549

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