The Classification Method for Risks of Dropout Students: a Case Study of Vocational Students

The paper proposes the new classification methodology using risk distance (RD). From 553 example students in the Chiang Rai Vocational College, dropout risk factors were chosen. The method was applied to classify the dropout examples using the risk factors. After that, the K-nearest neighbor (KNN) and the Artificial neural network (ANN) were applied to verify the accepted results. The experiment found that both KNN and ANN provide superb results by this proposed. It proves that the proposed methodology is efficient to use in the Vocational college that can help staff to prevent students from dropout of college in time.