PENERAPAN METODE ADABOOST UNTUK MENGOPTIMASI PREDIKSI PENYAKIT STROKE DENGAN ALGORITMA NAÏVE BAYES

Jurnal Sisfokom (Sistem Informasi dan Komputer)

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Field Value
 
Title PENERAPAN METODE ADABOOST UNTUK MENGOPTIMASI PREDIKSI PENYAKIT STROKE DENGAN ALGORITMA NAÏVE BAYES
 
Creator Byna, Agus
Basit, Muhammad
 
Subject
Stroke; Machine Learning; Naïve Bayes; Adaboost

 
Description Stroke is the deadliest disease in the world. Creating injury to this nervous system because of this requires special attention in its treatment. The development of the Industrial Revolution Era 4.0 technology and health science can collaborate to become something beneficial by using machine learning. Currently the benefits are used in predicting several diseases to be anticipated. In particular, stroke using adaboost optimization with naïve Bayes which can provide an accuracy of 0.986 has an Excellent classification diagnosis with 70/30 split data. The previous accuracy without using optimization is 0.976. The result of this accuracy is used by health experts in making good decisions in the field of nursing and medicine. In order to speed up the results of diagnosis to stroke patients.
 
Publisher ISB Atma Luhur
 
Contributor
 
Date 2020-11-08
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article

 
Format application/pdf
 
Identifier http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/1023
10.32736/sisfokom.v9i3.1023
 
Source Jurnal Sisfokom (Sistem Informasi dan Komputer); Vol 9, No 3 (2020): NOVEMBER; 407-411
2581-0588
2301-7988
 
Language eng
 
Relation http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/1023/685
 
Coverage


 
Rights Copyright (c) 2020 Jurnal Sisfokom (Sistem Informasi dan Komputer)
http://creativecommons.org/licenses/by/4.0
 

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