Proceeding International Applied Business and Engineering Conference
Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022

Early Detection Of Alzheimer Disease In Elderly Web-Based Using Support Vector Machine Classification Method

Juni Nurma Sari (Politeknik Caltex Riau)
Syaparudin BS (Politeknik Caltex Riau)
Kartina Diah KW (Politeknik Caltex Riau)
Puja Hanifah (Politeknik Caltex Riau)

Article Info

Publish Date
09 Jan 2023

Abstract

Alzheimer's disease is characterized by dimentia diseases that usually begin with a decrease in memory. The number of people in around the world with dimentia diseases is estimated to reach 47.5 million and is increased to quadruple by 2050. The risk factors that make someone exposed Alzheimer's disease are aging, alcohol consumption, anterosclerosis, diabetes mellitus, down syndrome, genetics, hypertension, depression, and smoking. Aging is the biggest risk factor for Alzheimer's disease. People with age 65 years and over have a higher risk. Therefore, it is important to early detect Alzheimer's disease in order to start planning adequate care and medical needs. This study aims to create a web-based system for early detection of Alzheimer's disease in the elderly using support vector machine classification. Detection of Alzheimer's disease using the metric Mini Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) obtained through questionnaires to find out about cognitive function, thinking ability and ability to perform daily tasks. Classification is carried out using the Support Vector Machine (SVM) algorithm. Alzheimer's classification testing uses a confusion matrix with an accuracy value of 85%. For system testing carried out User Acceptance Test with general practitioner, the results were obtained that all the features and functions of the system had run as expected.

Copyrights © 2022




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Full PDF
1777.15 KB
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
Proceeding International Applied Business and Engineering Conference
Website

Abbrev

iabec

Publisher

ABEC: Konsorsium Politeknik Se-Sumatra

Subject

Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Description

Proceedings of the Sumatra Polytechnic conference, scope: electrical engineering, mechanical engineering, computer engineering, civil engineering, social sciences, business administration, accounting, English, agriculture, ...