ANALISIS KOMPLEKSITAS SINYAL EEG PADA PENDERITA MILD ALZHEIMER’S DISEASE MENGGUNAKAN METODE HIGUCHI FRACTAL DIMENSION DAN KATZ FRACTAL DIMENSION

Muhammad Abdul Haq Ashiddiqi, NIM.: 15620046 (2022) ANALISIS KOMPLEKSITAS SINYAL EEG PADA PENDERITA MILD ALZHEIMER’S DISEASE MENGGUNAKAN METODE HIGUCHI FRACTAL DIMENSION DAN KATZ FRACTAL DIMENSION. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Alzheimer's disease is an age-related dementia caused by a decrease in neuronal function characterized by memory loss and cognitive decline. One of the tools that can be used to detect Alzheimer's is the EEG. The complexity parameter can be used as one of the EEG biomarkers, which can indicate changes in brain areas thought to be affected by Alzheimer's. This study aims to analyze changes in the complexity of the EEG signal in patients with Mild Alzheimer's Disease by applying the HFD and KFD methods. This research was carried out in several stages, namely data retrieval, then pre-processing the data and dividing the data into 4 frequency ranges, namely Delta (0-4 Hz), Theta (4-7 Hz), Alpha (7-13 Hz) and Beta (13 -30 Hz). Furthermore, to test the resulting data, a non-parametric test was carried out, namely the Mann Whiney U Test. The calculation results show that the part that experienced the most significant decrease occurred at the F4 electrode in the alpha and beta frequency ranges for HFD. Meanwhile in KFD, the electrodes with the most consistent decrease in complexity are at electrodes F7, F3, FC5, O2, where all of the frequency ranges have decreased significantly. Calculations using HFD as a whole provide better performance when compared to KFD with a p-value of less than 0.05, while in KFD there is one frequency range that has a p-value of more than 0.05, namely in the beta frequency range.

Item Type: Thesis (Skripsi)
Additional Information: Pembimbing: Dr. Nita Handayani, S.Si, M.Si
Uncontrolled Keywords: EEG, HFD, KFD, Mild Alzheimer Disease
Subjects: Fisika
Divisions: Fakultas Sains dan Teknologi > Fisika (S1)
Depositing User: Muh Khabib, SIP.
Date Deposited: 11 Mar 2022 10:42
Last Modified: 11 Mar 2022 10:42
URI: http://digilib.uin-suka.ac.id/id/eprint/49964

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