ANALYSIS OF DAILY LIFE OF STUDENTS BY DATA MINING TECHNIQUE CASE STUDY: THE STUDENTS AT THE UNIVERSITY OF THE THAI CHAMBER OF COMMERCE

Abstract

This research aims to analyze the daily life of students at the University of the Thai Chamber of Commerce related to health by Data Mining techniques, using Decision Tree method. Cross-Industry Standard Process for Data Mining (CRISP -DM) concept was applied for the data analysis. Start from the clarifying the objectives, gathering data, data preparation, by converting it into a data that can be analyzed, modeling, evaluation and deployment. In the modeling phase, the data is classified by the Decision Tree, based on the Accuracy, Precision, Recall. The results of research have shown that most students will not take supplementary food. But the ones who take supplementary food mostly for skin care, better health, and increasing muscles respectively. For students who take supplementary food for decreasing weight, BMI means Healthy, Moderately Obese, which the Accuracy is 91.06%. Most female students take supplementary food for facial skincare. For male students who want to take lean Food and BMI means Healthy. They need to have supplementary food for increasing muscles which the Accuracy is 53.85%.