Research Article
Imbalanced Data Analysis of Adolescent Risk Behavior of Drug Abuse using Random Forest
@INPROCEEDINGS{10.4108/eai.19-12-2020.2309145, author={Ismaini Zain and Kartika Fithiasari and Erma Oktania Permatasari and Tyas Ajeng Nastiti and Mardyono Mardyono and Nilam Novita Sari and Resti Pujihasvuty and Sri Lilestina Nasution}, title={Imbalanced Data Analysis of Adolescent Risk Behavior of Drug Abuse using Random Forest}, proceedings={Proceedings of The 6th Asia-Pacific Education And Science Conference, AECon 2020, 19-20 December 2020, Purwokerto, Indonesia}, publisher={EAI}, proceedings_a={AECON}, year={2021}, month={8}, keywords={adolescent risk behavior drug abuse imbalanced data random forest smote-n}, doi={10.4108/eai.19-12-2020.2309145} }- Ismaini Zain
Kartika Fithiasari
Erma Oktania Permatasari
Tyas Ajeng Nastiti
Mardyono Mardyono
Nilam Novita Sari
Resti Pujihasvuty
Sri Lilestina Nasution
Year: 2021
Imbalanced Data Analysis of Adolescent Risk Behavior of Drug Abuse using Random Forest
AECON
EAI
DOI: 10.4108/eai.19-12-2020.2309145
Abstract
Adolescence represents a period of self-searching and vulnerability to fall into risky behavior such as drug abuse. In Indonesia, the case of drug abuse by adolescents is high. Therefore, to know the factors behind it can be done using classification such as random forest. The data used in this research were adolescent risk behavior of drug abuse based on SKAP. The percentage of drug abuse among adolescents are 4.1% shows that there is an imbalanced class in the data. It is necessary to handle the imbalanced data by applying the SMOTE-N. This study will classify the adolescent risk behavior of drug abuse using random forest combine with SMOTE-N to handle the imbalanced class. The results show that the model using SMOTE-N is better because it can increase specificity and g-means. The variables affect the classification of drug abuse among adolescents are the age, sex, and psychology consequence
