Penerapan Algoritma Naive Bayes Untuk Mengklasifikasi Pengaruh Negatif Game Online Bagi Remaja Milenial

JTIM : Jurnal Teknologi Informasi dan Multimedia

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Field Value
 
Title Penerapan Algoritma Naive Bayes Untuk Mengklasifikasi Pengaruh Negatif Game Online Bagi Remaja Milenial
 
Creator Asmiati, Nungky
Fatmawati
 
Subject Neural Network
Backpropagation
Classification
Biomedicine
Image Processing
 
Description In this modern era, the use of electronics such as cellphones, computers, laptops and others quite widely used for various needs. Information technology that is very developed today brings changes and affects social life. One of the problems in society is the large influence of online games because online games themselves have an attraction that makes people more fun playing than learning. It evidenced by the large number of millennial adolescents spending their daily time in front of computers or smartphones instead of books, and the lack of socializing is also one of the negative effects of playing online games and harms their health. To solve these problems, the classification method used is the naïve Bayes algorithm method, for classification in the form of online game user data as a whole, namely based on name, gender, age, number of days, duration and classification in the form of addiction and not addiction (normal). Therefore, this naïve Bayes algorithm can predict future opportunities based on past experiences. The results of the study of 100 online game user data in normal conditions were 78 respondents, and addiction was 22 respondents from the results of both concluded that the research results of millennial adolescents online game users were declared normal with an overall accuracy of 89.00%. Addicted recall class 77.27%, normal recall class 92.31%, addicted precision class 73.91%, normal precision class 93.51%.
 
Publisher Puslitbang Sekawan Institute Nusa Tenggara
 
Date 2020-11-28
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://journal.sekawan-org.id/index.php/jtim/article/view/102
10.35746/jtim.v2i3.102
 
Source JTIM : Jurnal Teknologi Informasi dan Multimedia; Vol 2 No 3 (2020): November; 141-149
2684-9151
10.35746/jtim.v2i3
 
Language eng
 
Relation https://journal.sekawan-org.id/index.php/jtim/article/view/102/74
 
Rights Copyright (c) 2020 Nungky Asmiati, Fatmawati
https://creativecommons.org/licenses/by-sa/4.0
 

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