Indonesian Journal of Electrical Engineering and Computer Science
Vol 40, No 3: December 2025

Mobile application for diagnosing alzheimer's based on clinical dementia rating

Supriyanti, Retno (Unknown)
Putra Yubiksana, Muhammad (Unknown)
Mahardika Wijonarko, Bintang Abelian (Unknown)
Ramadhani, Yogi (Unknown)
Syaiful Aliim, Muhammad (Unknown)
Irham Akbar, Mohammad (Unknown)
Budi Widodo, Haris (Unknown)
Widanarto, Wahyu (Unknown)
Alqaaf, Muhammad (Unknown)



Article Info

Publish Date
01 Dec 2025

Abstract

Alzheimer's is a neurodegenerative disease characterized by memory loss, impaired thinking abilities, and changes in behavior. It is the most common form of dementia, significantly affecting a person's ability to carry out daily activities. Statistics indicate that the number of individuals suffering from Alzheimer's worldwide continues to rise as the population ages. Diagnosing Alzheimer's is a complex process that typically requires a skilled medical team. One diagnostic tool that can be utilized is an MRI machine. Previous research focused on extracting features from MRI images taken from three different cross-sections: axial, coronal, and sagittal. Based on these three types of cross-sectional images, we developed a system to classify the severity of Alzheimer's. This paper focuses on creating an Alzheimer's classification system accessible through a mobile application. The results indicate that our system has a performance accuracy of 90% in classifying the severity of the disease.

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