• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.249-257
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• 2009

The purpose of this study is to find a classification method with high accuracy in regard with sasang constitutional diagnosis. The BMI, blood pressure, pulse wave, and Sasang constitution diagnosed by a specialist was collected from 2848 subjects who were apparently healthy. Through a selective procedure, the data of 1635 subjects was used in the analysis. The results with the classification methods such as the discriminant analysis, regression, decision tree and neural network were compared with the diagnosis of a Sasang constitutional specialist. In result, the discriminant analysis method was hard to qualify the assumption of the equality of covariance matrices within constitutional groups. Moreover, without BMI, the decision tree and neural network methods were very sensitive to the change of the analysis data. Therefore, the Logistic regression and the decision tree is recommended on condition that the decisive factors of constitution are well concerned.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.129-136
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• 2023

The study aims to examine the determinants that affect satisfaction, revisit intention, and recommendation intention with foreign tourists who visited Korea despite the threat of COVID-19. This study employs the survey data collected by the Korea Tourism Organization from 8,135 foreign tourists who visited Korea in 2020. As the survey data contains a mixture of continuous and categorical variables, decision tree analysis can ensure analytical validity for the research. According to the analytical results, the determinants affecting satisfaction are the purpose of the visit and acceptance of self-quarantine during their stay. The factors influencing revisit intention are the purpose of the visit, frequency of the visit, and acceptance of self-quarantine during their stay. The determinants affecting recommendation intention are the purpose of the visit, length of stay, and gender. Based on the results of this analysis, this study not only explains the relationship between these determinants and tourism satisfaction, revisit intention, and recommendation intention, but also suggests implications for revitalizing tourism activities.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.729-736
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• 2010

In this paper, we study the influence analysis of admission variables including their characteristics on academic achievements of freshmen at K university in Busan. First, multiple regression analysis is used to examine the main effects of admission variables including students' characteristics on the academic achievements. Also, Decision tree analysis is used to examine the interaction effects for the admission variables on the academic achievements. The results of this paper may be helpful to K university in designing effective admissions strategies for recruiting students.

• Journal of Service Research and Studies
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• v.3 no.1
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• pp.9-16
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• 2013

Data analysis is the universal classification techniques, which requires a lot of effort. It can be easily analyzed to understand the results. Decision tree which is developed by Breiman can be the most representative methods. There are two core contents in decision tree. One of the core content is to divide dimensional space of the independent variables repeatedly, Another is pruning using the data for evaluation. In classification problem, the response variables are categorical variables. It should be repeatedly splitting the dimension of the variable space into a multidimensional rectangular non overlapping share. Where the continuous variables, binary, or a scale of sequences, etc. varies. In this paper, we obtain the coefficients of precision, reproducibility and accuracy of the classification tree to classify and evaluate the performance of the new cases, and through experiments to evaluate.

• Journal of Industrial Convergence
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• v.21 no.10
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• pp.21-28
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• 2023

As the need for the use of big data increases, various analysis activities using big data, including SNS data, are being carried out in individuals, companies, and countries. However, existing research on predicting technology market trends has been mainly conducted using expert-dependent or patent or literature research-based data, and objective technology prediction using big data is needed. Therefore, this study aims to present a model for predicting future technologies through decision tree analysis, visualization analysis, and percentage analysis with data from social network services (SNS). As a result of the study, percentage analysis was better able to predict positive techniques compared to other analysis results, and visualization analysis was better able to predict negative techniques compared to other analysis results. The decision tree analysis was also able to make meaningful predictions.

• Information Systems Review
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• v.22 no.4
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• pp.41-58
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• 2020

This study addresses the issue of which factors make domestic works have turnover intention. To pursue this research issue, we utilized a public database "2017 Occupational Migration Path Survey", administerd by Korea Employment Information Service (KEIS). Decision tree method was applied to extract crucial factors influencing workers' turnover intention. They include 'the degree of matching the level of education with the level of work', 'the possibility of individual development', 'the job-related education and training', 'the promotion system', 'wage and income', 'social reputation for work' and 'the stability of employment'.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.45-54
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• 2008

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model, which is one of the statistical analysis methods. The slope hazards data of Seoul and Kyonggi Province, which were induced by heavy rainfall in 1998, were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. Among these data, the number of data occurred slope hazards was 34 sections and the number of data non-occurred slope hazards was 27 sections. The statistical analyses using the decision tree model were applied to chi-square statistics, gini index and entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320 m, respectively.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.849-856
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• 2011

In this paper, we study the influence analysis of admission and enrollment variables including individual characteristics variables on employment of graduate students at K university. First, logistic regression analysis is used to examine the main effects of admission, enrollment variables including student's individual characteristics on employment. Also, decision tree analysis is used to examine the interaction effects for the variables on employment. The results of this paper may be helpful to K university in designing effective job finding strategies for graduate students.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.197-208
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• 2016

In this paper, data mining regression analysis and decision tree analysis techniques were used to analyze factors affecting the life satisfaction of middle school students. For this purpose, we analyzed Korean Children and Youth Panel Survey(KCYPS) data. As results, the common influencing factors to the life satisfaction were derived from regression analysis. Those factors are self-esteem, depression, total grade satisfaction, regional community awareness, career identity, annual delinquency damage experience, siblings' factors, trust, behavioral control, and concentration. Based on the result described by decision tree analysis, the factors that indicate a significant impact on the life satisfaction of middle school students were self-esteem, depression, career identity and attention factor.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.693-701
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• 2012

Recently, the number of students who get double majors has tended to increase in many universities. As results, many problems occur because immoderate inflow of double-major students is concentrated in a specific popular department. In this paper, we study the characteristic of inflow and outflow of double majors using social network analysis and decision tree analysis. According to the results, SAT score affected the inflow of double majors the most. Additionally, department category, course evaluation score, employment rate also affected the inflow of double majors in the order named. On the other hand, department category affected the outflow of double majors the most. Additionally, SAT score, employment rate, course evaluation score also affected the outflow of double majors in the order named.