dc.contributor.author |
Ihsan Omur Bucak; Department of Computer Engineering, Mevlana University |
|
dc.contributor.author |
Faruk Bulut; Department of Computer Engineering, Fatih University |
|
dc.date |
2013-06-17 09:16:50 |
|
dc.date.accessioned |
2013-07-15T11:51:55Z |
|
dc.date.accessioned |
2015-11-23T16:00:10Z |
|
dc.date.available |
2013-07-15T11:51:55Z |
|
dc.date.available |
2015-11-23T16:00:10Z |
|
dc.date.issued |
2013-07-15 |
|
dc.identifier |
http://ecs.epoka.edu.al/index.php/iscim/iscim2011/paper/view/688 |
|
dc.identifier.uri |
http://dspace.epoka.edu.al/handle/1/705 |
|
dc.description.abstract |
In recent years, the rising use of addictive drugs and substances has become one of the biggest social problems around the world. The illicit use of a variety of drugs appears to be increasing among elementary and high schools students in Turkey. Therefore, it can be said that there is a big rising risk for the youth: substance abuse and addiction. There are many reasons leading students to be an addicted user. At first an adolescent cannot see the bad sides and realize the harmful effects of the substances. After being a drug abuser, this person struggles with the addiction and his/her life gets worse. Scientific studies show that it becomes very difficult for aperson to get rid of this habit after being a user. Hence, preventing students from being addicted becomes an important issue. The aim of this study is to determine a young person's probability of becoming a drug user in the future by means of Bayesian classification algorithm. The study is focused on informing the educators and families about the students who entertain high risk, and taking precautions and counter measures before it is too late. As data collection method, a questionnaire is asked the elementary and high school students in Buyukcekmece district of Istanbul and to the patients of substance abuse and addiction in the hospitals. The data collected from the questionnaires are used to indicate the percentage of risk probability for each student with the aid of Bayesian classification algorithm. |
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dc.format |
application/pdf |
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dc.language |
en |
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dc.publisher |
International Symposium on Computing in Informatics and Mathematics |
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dc.source |
International Symposium on Computing in Informatics and Mathematics; 1st International Symposium on Computing in Informatics and Mathematics |
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dc.subject |
Substance abuse; Substance addiction; Bayesian classification; Machine learning |
|
dc.title |
The Evaluation of Risk of Substance Abuse Among The Youth through Bayesian Classification |
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dc.type |
Peer-reviewed Paper |
|