• Journal of Digital Convergence
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• v.14 no.8
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• pp.163-175
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• 2016

The purpose of this study is to provide an efficient internal control system formation incentives for company and to confirm empirically usefulness of the internal accounting control system for financial institutions by analyzing whether the internal control vulnerabilities of companies related significantly to the classification and assessment of soundness of financial institutions. Empirical analysis covered KOSPI, KOSDAQ listed companies and unlisted companies with more than 100 billion won of assets which have trading performance with "K" financial institution from 2008 until 2013. Whereas non-internal control vulnerability reporting companies by the internal control of financial reporting received average credit rating of BBB on average, reporting companies received CCC rating. And statistically significantly, non-reporting companies are classified as "normal" and reporting companies are classified as "precautionary loan" when it comes to asset quality classification rating. Therefore, reported information of internal control vulnerability reduced the credibility of the financial data, which causes low credit ratings for companies and suggests financial institutions save additional allowance for asset insolvency prevention and require high interest rates. It is a major contribution of this study that vulnerability reporting of internal control in accordance with the internal control of financial reporting can be used as information significant for the evaluation of financial institutions on corporate soundness.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.321-331
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• 2020

The purpose of this study is to explore the impact of home stay platform on guests' willingness to comment online under the Shared home stay business model. Shared platform of home stay facility in addition to providing a variety of support services, help the landlord to the tenant do offline accommodation services, implementation, trading, will need to take some measures to actively promote the tenant groups to the landlord, the evaluation is objective, effective and sufficient number in order to better promote the sharing credit ecological establishment of home stay facility. In this study, consumers who have used the Shared home stay platform are taken as the research objects. The survey method adopts network questionnaire survey and Likert seven subscales. The statistical software SPSS24.0 program is used to process the data. Firstly, descriptive statistical analysis was conducted, followed by validity analysis and reliability analysis. After the reliability and validity of the questionnaire were determined, correlation analysis and regression analysis were used to verify the proposed hypothesis. The research results of this study are summarized as follows :(1) the usability of platform comment function, guest satisfaction and platform reward have a positive impact on the guest online comment willingness; (2) The credit mechanism of the platform has a positive regulating effect on the process of tenant satisfaction influencing tenant comment intention.

• PNF and Movement
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• v.11 no.1
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• pp.43-54
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• 2013

Purpose : The purpose of this research was to verify the effects of the clinical practice and the educational satisfaction through internship program on students of health-related majors. Methods : We investigated 120 students using a self-reporting method with experience of internship program. A statistical analysis was performed using SPSS 17.0 for window version. Results : It showed that educational satisfaction had scored 4.18 in curriculum, 4.16 in environment, 4.16 in schedule, 4.32 in teaching and 3.82 in evaluation, 4.21 in satisfaction for clinical practice. Conclusion : It was revealed by this survey that the educational satisfaction of internship program in school hospital had higher score in curriculum, environment, schedule, evaluation, teaching and clinical practice. To maximize the effects of internship program, a clinical internship program in school hospital is needed and further research and attention are suggested.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.617-625
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• IE interfaces
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• v.10 no.2
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• pp.15-28
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• 1997

Knowledge acquisition has been a major bottleneck in building expert systems. To ease the problems arising in knowledge acquisition, analog concept learning systems(ACLS) has been used. In this paper, in order to avoid the overfitting problem and secure a good performance, we propose the revised ACLS, which pruning methods -cost complexity, reduced error, pessimistic pruning and production rule- are incorporated into and apply them to the credit evaluation for Korean companies. The performances of the revised ACLS are evaluated in light of the prediction accuracy. To check the effect of the training data sampling on the performance, experiments are conducted using the different proportion of the training data. Experimental results show that the revised ACLS of combining cost complexity pruning with reduced error pruning performs best among original ACLS and other methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.81-100
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• 1996

본 연구에서는 보다 효과적인 기업신용평가를 위하여, 통계적 방법과 인공지능 방법을 결합한 결합모형을 제시햐고자 한다. 이를 위하여 본 연ㄴ구에서는 통계적인 모형중에서 가장 널리 활용되고 있는 MDA (Multivariate Discriminant Analysis) 와 인공지능적인 방법으로서 최근에 널리 사용되고 있는 인공싱경망( neural network)모형을 휴리스틱한 방법으로 결합한다. 이러한 결합모형의 성과를 증명하기 위하여 우리나라의 대표적인 3대 기업신용평가 기관에서 수집한 1043개의 기업신용평가자료를 기초로 실혐을 하고, 그 결과를 기존의 MDA 및 인공신경망 방법에 의한 결과와 비교하였다. 실험결과, 통계적으로도 유의하고, 실무적인 관점에서도 의미가 있는 기업신용펑가 결과를 유도할 수 있었다.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1027-1036
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• 2012

Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions. We could obtain confidence intervals of similarity distance for the same and different persons, and optimal thresholds to minimize two kinds of error rates for distance distributions. It is found that the two confidence intervals of the same and different persons are not overlapped and that the optimal threshold locates between two confidence intervals. Hence an alternative statistical matching method can be suggested by using nonoverlapped confidence intervals and optimal thresholds obtained from the distributions of similarity distances.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• Journal of Distribution Science
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• v.14 no.12
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• pp.141-151
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• 2016

Purpose - Salesperson perceptions of the fairness and accuracy of a performance evaluation system were examined by managerial and professional employees of large organization. The performance evaluation process is central to many personal decisions such as attitude for job and sales performance. This study investigates the relationship between perceived evaluation fairness, job satisfaction, organizational commitment, and sales performance. The main purpose of this study is to develop and empirically test a comprehensive model of salespersons' perceived evaluation fairness on sales performance. For this purpose, we identified the structural relationship between perceived evaluation fairness, job satisfaction, organizational commitment, and sales performance. Also we investigate the mediating effects on job satisfaction and organizational commitment between perceived evaluation fairness and sales performance. Research design, data, and methodology - To empirically test these relationships, data were collected by in-depth interviews from sales managers and questionnaire surveys from 300 salespersons who work for sales area (credit card company, insurance company). Demographically, the overall sample was 91.6% female, 77.9% 30s and 40s, and 34% college educated, with an average tenure with their present organizations of 4 years. The questionnaire was composed of total 20 items dealing with frequency, quality, and consequences of perceived evaluation fairness, job satisfaction, organizational commitment, and sales performance. To test the research hypotheses, collected data analyzed by confirmatory factor analysis (CFA) and structure equation model (SEM). Results - Through extensive and rigorous literature review process of related literature(Perceived evaluation fairness, Job satisfaction, Organizational commitment, Sales performance), research model and research hypothesis was set up. This study obtains the following research results. First, perceived evaluation fairness has a positive effect on job satisfaction, whereas the effects of perceived evaluation fairness on organizational commitment and sales performance did not show statistically significant result. Second, job satisfaction and organizational commitment have complete mediating roles to the relationship between perceived evaluation fairness and organizational commitment, and relationship between perceived evaluation fairness and sales performance. Conclusions - Based on the results, salespersons' perceived evaluation fairness is one of the key independent variable for making high job satisfaction, organizational commitment, and sales performance. Finally the theoretical, managerial implication and research limitations are mentioned in the discussion.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.193-200
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• 2018

Recently, there are high expectations of a society benefitting from a digital sharing economy. However, to establish a digital sharing economy, one needs to first create a reliable social structure. Transparency is recognized as the most important measure of value in not just politics or economics, but also in all domains of our lives. Although all nations strive to create "societies based on credit and trust," in truth, rigidity, irregularity, corruption, and inefficiency are widespread in all aspects of society. Thus, there is a growing interest in blockchain technology, also called the "second Internet revolution," seeking trust in digital environments, although it is difficult to obtain trust in such environments. However, the principles and methods of evaluating blockchain technologies are still unclear and not standardized. This study addresses the evaluation indexes such as transaction per second, maximum data size per one transaction, accuracy and blockchain technology application methods in the digital sharing economy and suggest ways to safely vitalize a blockchain-based digital sharing economy.