This study research attempts to prohibit privacy and loss of money for
individuals and organization by creating a reliable model which can detect the fraud exposure in the online recruitment
environments. This research presents a major contribution represented in
a reliable detection model using ensemble approach based on Random forest
classifier to detect Online Recruitment Fraud (ORF). The detection of Online
Recruitment Fraud is characterized by other types of electronic fraud detection
by its modern and the scarcity of studies on this concept. The researcher
proposed the detection model to achieve the objectives of this study. For
feature selection, support vector machine method is used and for classification
and detection, ensemble classifier using
Random Forest is employed. A freely available dataset called Employment Scam
Aegean Dataset (EMSCAD) is used to apply the model. Pre-processing step
had been applied before the selection and classification adoptions. The results
showed an obtained accuracy of 97.41%. Further, the findings presented the main features and important
factors in detection purpose include having a company profile feature, having a
company logo feature and an industry feature.
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