An urgent precaution system to detect students at risk of substance abuse through classification algorithms

Faruk BULUT; İhsan Ömür BUCAK

Makale detayları

An urgent precaution system to detect students at risk of substance abuse through classification algorithms

Yazarlar:

Faruk BULUT | İhsan Ömür BUCAK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 3, pp.690-707

Belge Tipi:

Makale

Yayın Tarihi:

5/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000743004

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

In recent years, the use of addictive drugs and substances has turned out to   be a challenging social problem worldwide. The illicit use of these types of   drugs and substances appears to be increasing among elementary and high   school students. After becoming addicted to drugs, life becomes unbearable   and gets even worse for their users. Scientific studies show that it becomes   extremely difficult for an individual to break this habit after being a   user. Hence, preventing teenagers from addiction becomes an important issue.   This study focuses on an urgent precaution system that helps families and   educators prevent teenagers from developing this type of addiction. The aim   of this study is to detect a teenager's probability of being a drug abuser   using classification algorithms in machine learning and data mining. The   objective is not to test the classifiers theoretically on the benchmark   datasets, but rather to use this study as a basis for advanced and detailed   studies in this field in the future. This paper not only uses a special   dataset but also focuses on psychometrics and statistics. The findings of   this study show that if there is a computed high risk for a teenager, some   precautions, if necessary, may be taken by educators and parents to keep the   teenager away from those substances.

 

In recent years, the use of addictive drugs and substances has turned out to   be a challenging social problem worldwide. The illicit use of these types of   drugs and substances appears to be increasing among elementary and high   school students. After becoming addicted to drugs, life becomes unbearable   and gets even worse for their users. Scientific studies show that it becomes   extremely difficult for an individual to break this habit after being a   user. Hence, preventing teenagers from addiction becomes an important issue.   This study focuses on an urgent precaution system that helps families and   educators prevent teenagers from developing this type of addiction. The aim   of this study is to detect a teenager's probability of being a drug abuser   using classification algorithms in machine learning and data mining. The   objective is not to test the classifiers theoretically on the benchmark   datasets, but rather to use this study as a basis for advanced and detailed   studies in this field in the future. This paper not only uses a special   dataset but also focuses on psychometrics and statistics. The findings of   this study show that if there is a computed high risk for a teenager, some   precautions, if necessary, may be taken by educators and parents to keep the   teenager away from those substances.

Makale detayları

An urgent precaution system to detect students at risk of substance abuse through classification algorithms

Yazarlar: Faruk BULUT | İhsan Ömür BUCAK

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 3, pp.690-707

Belge Tipi: Makale

Yayın Tarihi: 5/2014

Belge Dili: Türkçe

Document ID (Org No.): 2000743004

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Faruk BULUT | İhsan Ömür BUCAK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 3, pp.690-707

Belge Tipi:

Makale

Yayın Tarihi:

5/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000743004

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632