Imbalanced Data Analysis of Adolescent Risk Behavior of Drug Abuse using Random Forest

Penulis: Ismaini Zain, Kartika Fithiasari, Erma Oktania Permatasari, Tyas Ajeng Nastiti, Mardyono Mardyono, Nilam Novita Sari, Resty Pujihasvuty, Sri Lilestina Nasution


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.

Kata Kunci: Adolescent Risk Behavior, Drug Abuse, Imbalanced Data, Random Forest, SMOTE-N

Diterbitkan di: Proceeding Research Meet Innovation

Link Artikel/DOI:

Tinggalkan Komentar

Alamat email Anda tidak akan dipublikasikan.