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Analisis Pola Penyakit Hipertensi Menggunakan Algoritma C4.5

Main Authors: Azwanti, Nurul, Elisa, Erlin
Format: Article info application/pdf eJournal
Bahasa: eng
Terbitan: Universitas Islam Sumatera Utara , 2019
Subjects:
Data mining
algoritm C4.5
hypertension
Online Access: https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/944
https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/944/pdf
ctrlnum --jurnal.uisu.ac.id-index.php-index-oai:article-944
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><title lang="en-US">Analisis Pola Penyakit Hipertensi Menggunakan Algoritma C4.5</title><creator>Azwanti, Nurul</creator><creator>Elisa, Erlin</creator><subject lang="en-US">Data mining, algoritm C4.5,hypertension</subject><description lang="en-US">There are approximately 95% of cases of unknown cause of hypertension, while the rest caused by other diseases such as coronary heart disease, impaired kidney function, and impaired cognitive function or stroke. RSUD Embung Fatimah is an Indonesian hospital located in Batam Island Riau Province. In 2015, the total number of inpatients for hospitalization reaches 10,317 inhabitants. With the large number of patients per year it causes patient data is increasing. To overcome the problem in tackling people with hypertension disease, it is necessary to analyze the existing disease data, to predict the patient's illness which must be handled based on the pattern of the disease. In data mining there is a model that can be used to predict a pattern in a condition that is predictive or prediction model. One of the algorithms that can be used to create a decision tree (decission tree) is the C4.5 algorithm. The C4.5 algorithm is a method used for predictive classification. Using C4.5 algorithm method, the researcher can classify the pattern of hypertension as a comorbid illness of heart failure, kidney failure, diabetes, stroke and hypoglycemia. In this study, researchers used WEKA (Waikato Environment for Knowledge Analysis) software as tools or tools used to perform testing in order to obtain the pattern of disease from hypertension. From the research findings in the find that in the prediction of hypertension disease as a disease, the attributes that are very influential to hypertension are heart failure.</description><publisher lang="en-US">Universitas Islam Sumatera Utara</publisher><contributor lang="en-US"/><date>2019-02-08</date><type>Journal:Article</type><type>Other:info:eu-repo/semantics/publishedVersion</type><type>Journal:Article</type><type>File:application/pdf</type><identifier>https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/944</identifier><identifier>10.30743/infotekjar.v3i2.944</identifier><source lang="en-US">InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan; Vol 3, No 2 (2019): InfoTekJar Maret; 116-123</source><source>2540-7600</source><source>2540-7597</source><source>10.30743/infotekjar.v3i2</source><language>eng</language><relation>https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/944/pdf</relation><rights lang="en-US">Copyright (c) 2019 InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan</rights><recordID>--jurnal.uisu.ac.id-index.php-index-oai:article-944</recordID></dc>
language eng
format Journal:Article
Journal
Other:info:eu-repo/semantics/publishedVersion
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File:application/pdf
File
Journal:eJournal
author Azwanti, Nurul
Elisa, Erlin
title Analisis Pola Penyakit Hipertensi Menggunakan Algoritma C4.5
publisher Universitas Islam Sumatera Utara
publishDate 2019
topic Data mining
algoritm C4.5
hypertension
url https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/944
https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/944/pdf
contents There are approximately 95% of cases of unknown cause of hypertension, while the rest caused by other diseases such as coronary heart disease, impaired kidney function, and impaired cognitive function or stroke. RSUD Embung Fatimah is an Indonesian hospital located in Batam Island Riau Province. In 2015, the total number of inpatients for hospitalization reaches 10,317 inhabitants. With the large number of patients per year it causes patient data is increasing. To overcome the problem in tackling people with hypertension disease, it is necessary to analyze the existing disease data, to predict the patient's illness which must be handled based on the pattern of the disease. In data mining there is a model that can be used to predict a pattern in a condition that is predictive or prediction model. One of the algorithms that can be used to create a decision tree (decission tree) is the C4.5 algorithm. The C4.5 algorithm is a method used for predictive classification. Using C4.5 algorithm method, the researcher can classify the pattern of hypertension as a comorbid illness of heart failure, kidney failure, diabetes, stroke and hypoglycemia. In this study, researchers used WEKA (Waikato Environment for Knowledge Analysis) software as tools or tools used to perform testing in order to obtain the pattern of disease from hypertension. From the research findings in the find that in the prediction of hypertension disease as a disease, the attributes that are very influential to hypertension are heart failure.
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subject_area Computer Modeling and Simulation/Model dan Simulasi Komputer
Computer Communications Networks/Jaringan Komunikasi Komputer
Algorithms/Algoritma
Computer Security, Data Security/Keamanan Komputer, Keamanan Data
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first_indexed 2019-09-23T21:31:47Z
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