• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.1029-1041
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• 2013

Recently, along with emergence of big data, there are incresing demands for releasing information and micro data for public use so that protecting privacy and measuring risk of disclosure for released database become important issues in goverment and business sector as well as academic community. This paper reviews statistical methods for protecting privacy and measuring risk of disclosure when micro data or data analysis sever is released for public use.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.225-235
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• 2021

The objective of this study is to identify the effects of ethical values reflected on zakat and Corporate Social Responsibility (CSR) on the financial performance of sharia banking in Indonesia. This study contributes to the Indonesia Financial Service Authority (Otoritas Jasa Keuangan (OJK) policies concerning the need for implementing ethical values in sharia banking and other sharia financial entities based on the philanthropic model, this study posits that firms undertaking zakat and charity are ethical firms. The population of this study is 8 sharia banks listed on the Indonesia Stock Exchange (IDX) in 2014-2018. The result of the study showed that zakat disclosure significantly affected financial performance. Moreover, ethical values that were proxied by CSR disclosure did not significantly affect financial performance. The limitation of the study is the limited number of the sample; therefore, it is expected that the future research adds other sharia financial entities and adds the dimension of management, sustainability, product, and the environment as benchmarks of ethical values. The originality of this study offers an additional explanation of the relationship between ethical values and performance by investigating zakat and CSR disclosure which is a unique factor in Indonesia.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.23-33
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• 2021

The main objective of this research is to examine the effect of organizational culture, environmental uncertainty, and manager's personnel value on environmental disclosure through the environmental organizational structure of manufacturing companies on the Indonesia Stock Exchange. This research uses the structuration and contingency theory. The sample in this study focused on the level of heads or managers or directors of manufacturing companies listed on the Indonesia Stock Exchange. The research data was obtained through an online questionnaire distributed to heads or managers. The total sample of this study is 161 manufacturing companies. The data comprising of 64 respondents was completed and can be processed. Empirical testing used Structural Equation Modeling (SEM) through Partial Least Square (PLS). The result shows that environmental uncertainty and management personnel value have a positive effect on the environmental organizational structure, as well as the environmental organizational structure has a positive effect on the environmental disclosure. However, organizational culture has no effect on the environmental organizational structure. This research can provide benefits for manufacturing companies. The limitation include the low level of response from the respondents. Also the results cannot be generalized due to its specific focus on the manufacturing companies.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.151-157
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• 2017

In the case of uploading privacy information of an information owner in the Internet, the information owner may want to deliver the privacy information itself or remove such information from the search list in order to prevent third parties from accessing the privacy information of the information owner. Such a right to be forgotten may collide with the freedom of expression of a third party. The right to be forgotten, which originates from the self-determination right on privacy information based on Article 10 and 17 of the Constitution and the freedom of expression, which is based on Article 21 thereof are all relative basic rights and are both limited by Item 2 under Article 37 of the same law, which is the general limitation provision for the basic rights. Therefore, when the right to be forgotten and the freedom of expression collides, it is not possible to give priority to one of the those unilaterally. It depends on the nature of the case at hand to find a natural balance for the harmonious solution for both parties. The criteria can be the sensitivity to the privacy of the information owner caused by the disclose of the privacy information, the public benefits such information may serve, the social common good that could be expected by the disclosure of the privacy information and the damages suffered in terms of the personal interest caused by the disclosure of the information, in a comprehensive manner.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.313-325
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• 2008

Large amounts of information on individuals is available to many organizations and data users and government agencies release microdata files from their survey data or administrative records data. However, if a microdata file is released without any limitation, an invasion of privacy is likely to occur. Therefore, in creating a microdata file, agencies attempt to eliminate disclosure risk of the file while maintaining maximum utility of the data. In this paper, we introduce the concept of disclosure risk, identification and uniqueness. Also, we show the method for creating a 2% microdata file using the 2005 Korean census microdata.

• The Korean Journal of Archival Studies
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• no.13
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• pp.135-178
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• 2006

The response of public organizations on information offerings has affirmed that the arrangement of the management of records is an important project to be implemented ahead of the enforcement of the information disclosure system. In particular, the absence or non-disclosure of information of public organizations on records containing significant information and abuse of the secret disposition of information has demonstrated that it is imperative to improve radically the management of secret or non-disclosed records as well as overall changes of awareness. This study reviewed the reality of the current non-disclosure and management of confidential records based on the awareness on such records and proposed improvement measures. The study on non-disclosed and confidential records has been discussed from legal and administrative perspectives so that the main focus has been on the institutional aspect. Yet, there is a limitation on such discussions in that there cannot be fundamental access to issues of non-disclosed and confidential records. That is because the management of information classified as non-disclosed and confidential can be improved fundamentally when all processes from the production of the records to their management are carried out reasonably. Accordingly, since our record management system is divided into three phases of the disposition division, record center, and archives and takes a management record by being applied to the flow of the life cycle of records, we have reviewed overall issues from the production of non-disclosed and confidential records to the utilization of the records pursuant to these steps and offered directions for improvement.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.141-151
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• 2009

According to the type of microdata, the various methods have been in use for masking microdata. Multiplicative noise is the one of popular schemes for masking continuous variables. In this paper, we introduce the method of masking based on multiplicative noise and show some results of the application on the 2006 Householder Income and Expenditure Survey (HIES) data. To create the multiplicative noise factor, we used the triangular distribution. truncated triangular distribution, trapezoidal distribution, and double triangular distribution. Also, formulas for the domain estimation for the data masked by the multiplicative noise are developed.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.5
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• pp.532-537
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• 2015

In this paper, we propose target range estimation method using ghost target in the submarine linear array sonar. Usually, when submarine detect target, they use passive sonar detection to avoid self-disclosure by active sonar transmission. But, originally, passive linear array sonar have limitation for target range estimation and additional processing is required to get target range information. For the case of near-field target, typical range estimation method is using multiple information by multipath effect in underwater environment. Acoustic signal generated from target are propagated along with numerous multipath in underwater environment. Since multipath target signals received in the linear array sonar have different conic angles each other, ghost target is appeared at the bearing different with real target bearing and sonar operator can find these information on the operation console. Under several assumption, this geometric properties can be analysed mathematically and we get the target range by derivation of this geometric equations using measured conic angles of real target and ghost target.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.377-388
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• 2022

The purpose of this article is to investigate the impact of competition on the performance of Indian banks. The survey includes banks from both the public and private sectors. The study will collect data for four years, from 2015 to 2019. Dynamic and static panel data are applied to estimate the association between competition and the bank's performance. Profitability and risk-taking are the performance measures used in the study. The study's main findings are that competition does not impact the banks' profitability in India. However, the findings concerning risk-taking are mixed. Therefore, it can be inferred that overall competition does not impact the banks' performance in India. Other measures of performance of the banks could have been used in the study. It is a limitation to use data of four years. Data for a much more extended period could have also been used. This is one of the few papers on the subject. Therefore, its contribution is very significant. The gap in studies on the topic of competition versus performance of the banks is veritably filled by the current study's findings.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.