• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.125-135
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• 2022

This study aims to explore variables using machine learning and provide analysis techniques suitable for predicting pharmacy sales whether government statistical indicators built to create an industrial ecosystem based on data, network, and artificial intelligence affect pharmacy sales. Therefore, this study explored predictive variables and performance through machine learning techniques such as Random Forest, XGBoost, LightGBM, and CatBoost using analysis data from January 2016 to December 2021 for 28 government statistical indicators and pharmacies in the retail sector. As a result of the analysis, economic sentiment index, economic accompanying index circulation change, and consumer sentiment index, which are economic indicators, were found to be important variables affecting pharmacy sales. As a result of examining the indicators MAE, MSE, and RMSE for regression performance, random forests showed the best performance than XGBoost, LightGBM, and CatBoost. Therefore, this study presented variables and optimal machine learning techniques that affect pharmacy sales based on machine learning results, and proposed several implications and follow-up studies.

• Proceedings of the Korean Association for Survey Research Conference
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• 2002.11a
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• pp.111-127
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• 2002

As the utilization of official statistics has been recently increased, the necessity of objective quality assessment also has been increased. Since mean square error(MSE) and response rate, which have been considered as representative quality indicators in the past, may have the limits of use, it has been demanded to develop new quality indicators which are able to reflect the various requirements of users. In this paper, regarding sample surveys conducted by governmental agencies, the flow of procedures in statistics production is analyzed using input-output of each procedure. As the result, how to identify and develop quality indicators for each procedure is discussed, with some instances of indicators. Finally, the quality index using the results of quality assessment would be calculated based on a weighting method by the size of deviation of statistical measures.

• 정보보호뉴스
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• s.137
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• pp.54-57
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• 2009

방통위가 지난 3월초 우리나라 민간영역의 개인정보보호 수준을 측정한 개인정보보호지수를 발표했다. 개인정보보호지수는 민간부문 의 개인정보보호 수준측정과 정부의 정책성과 평가 및 정책방향 수립 등을 위해 지난 2007년부터 실시한 것으로, 2008년 하반기에 실시한 정보보호 실태조사 결과를 반영해 최초로 공개한 자료다. 이번 자료에 따르면, 2008년 민간영역의 개인정보보호지수는 64.3점으로 2007년 결과인 52.2점에 비해 크게 개선된 것으로 나타났다. 기업 영역 세부지표와 개인영역 세부지표로 구성된 이번 조사결과를 통계를 중심으로 살펴보자.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.35-43
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• 2015

Regional comparative analysis for the variability of young man's employment indexes is important to unemployment or employment policy data of central and local government. Through the result of comparative analysis, central and local government can use differentiated policies for the regions and keep the efficiency for the application of detailed policy. In this study, based on economically active population survey data which consider economically active population rate, employment population rate and unemployment rate as typical employment indexes of young man, we analyzed the variability of these indexes by metropolitan cities and province regions using coefficient of variation. Also we proposed the largest index in variability of three employment indexes, and proposed the city and province region with the largest variability for each employment index.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.255-263
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• 2024

GDP represents the total market value of goods and services produced by all economic entities, including households, businesses, and governments in a country, during a specific time period. It is a representative economic indicator that helps identify the size of a country's economy and influences government policies, so various studies are being conducted on it. This paper presents a GDP growth rate forecasting model based on a dynamic factor model using key macroeconomic indicators of G20 countries. The extracted factors are combined with various regression analysis methodologies to compare results. Additionally, traditional time series forecasting methods such as the ARIMA model and forecasting using common components are also evaluated. Considering the significant volatility of indicators following the COVID-19 pandemic, the forecast period is divided into pre-COVID and post-COVID periods. The findings reveal that the dynamic factor model, incorporating ridge regression and lasso regression, demonstrates the best performance both before and after COVID.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.299-302
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• 2015

사회복지 지표조사는 주민들의 사회복지에 관한 다양한 상태를 전체적으로 파악할 수 있는 조사로 다양한 복지정책 개발에 있어 지역 주민들의 욕구를 반영할 수 있는 장점이 있다. 따라서 사회복지 지표조사는 복지 욕구를 알 수 있는 중요한 척도의 기준이라 할 수 있어 많은 지자체 및 정부기관에서 예산과 시간을 들여 조사를 실시하고 있다. 그러나 조사에 대한 분석 결과가 기초적인 통계 분석 위주로 되어 있어 실제 자료를 제대로 할용하지 못하고 있는 것이 현실이다. 이에 본 논문에서는 데이터 마이닝 기법을 이용한 분석 방법론을 제시한다. 또한 이를 충청북도의 중장기 사회복지 정책을 위한 지표조사에 적용하였다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.19 no.1
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• pp.113-130
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• 2008

Performance indicators for academic libraries in Korea suggested in this research cover three areas, that is, collection, budget, and human resources, which consists of three subdivisions, respectively. Performance indicators and action plans in this research were prepared, based on the official documents which universities in Korea formally submitted to the Ministry of Education and Human Resources, and the data published by the related institutions. Performance indicators and action plans are intended to draw attentions of university administrators and headquarters, but do not require librarians to prepare for evaluation. The better results would be expected with the development and application of both quantitative and qualitative indicators for information services by standardizing and unifying the process of collecting statistics. It is also expected that periodic and continuing evaluation of academic libraries could help government and universities have a better understanding of and appreciate the significance of academic libraries.

• Journal of Nutrition and Health
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• v.51 no.2
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• pp.177-185
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• 2018

Purpose: This study analyzed the perception and importance of country-of-origin labeling at restaurants in 500 college students in Jeju surveyed from April 15 to May 5, 2016 with the aim of providing basic data. A total of 465 questionnaires out of 500 were used as base data for this study. Methods: The data were analyzed using descriptive analysis, ${\chi}^2-test$, and t-test using the SPSS Win program (version 21.0). Results: Regarding food safety-related dietary behaviors, average score was 3.65 points (out of 5), and 'put the food in a refrigerator or freezer immediately (4.07)' showed the highest score, whereas 'cool rapidly hot food prior to putting it in the refrigerator (3.08)' showed the lowest score. Regarding the awareness of country-of-origin labeling at restaurants, 67.5% of subjects were aware of it. With regard to dietary behavior of food safety, the high group showed a higher score than the low group (p < 0.001). Regarding reliability of the system, 4.9% of subjects indicated 'very reliable' and 45.4% 'somewhat reliable'. For perception of subject's country-of-origin labeling, the average score was 3.77 (out of 5). Regarding checking country-of-origin labeling at restaurants, 68.0% of subjects checked country-of-origin labeling, and the high group in the safety-related dietary behavior score ranking showed a higher rate (79.3%) than the low group (57.1%) (p < 0.001). With regard to importance by item, 'honest country-of-origin labeling of restaurants' showed the highest score at 4.27 (out of 5). Conclusion: It is necessary to provide continuing education for college students in order to enhance their perception of country-of-origin labeling at restaurants. Moreover, a systematic and appropriate support and control system by the government and local government needs to be developed in order to improve country-of-origin labeling at restaurants.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.301-310
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• 2020

The purpose of paper is to find index for building digital database of bike infrastructure statistics by analyzing the existing design standards and manuals. The design standards and guides of both central and local governments which designates the design elements of bikeway were investigated to find the primary index, and then the attribute data of bikeway were grouped into four categories including transportation, geometry, pavement, safety and utility facility, and were analyzed to find the secondary index. A FGI(Focus Group Interview) was conducted with experts in the arena of transportation to collect the opinions on the selected index. It is found that the final twenty four design elements were selected and additional six elements were added. The proposed twenty four index of bikeway design elements are considered to be included when building the digital bikeway register database.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.457-465
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• 2015

The long lasting world-wide recession and low economic progress have made it more important to predict future economic behavior. Accordingly, it is of interest to explore useful leading indicators, correlated with policy targets, to predict future economic growth. This study attempts to develop a model to evaluate the performance of consumer survey results from Statistics Korea to predict future economic activities. A statistical model is formulated and estimated to generate predictions by utilizing consumer expectations. The prediction is found improved in the distant future and consumer expectations appear to be a useful leading indicator to provide information of future real growth.