• Title/Summary/Keyword: Statistical indicators

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Export-Import Value Nowcasting Procedure Using Big Data-AIS and Machine Learning Techniques

  • NICKELSON, Jimmy;NOORAENI, Rani;EFLIZA, EFLIZA
    • Asian Journal of Business Environment
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    • v.12 no.3
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    • pp.1-12
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    • 2022
  • Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

A Necessity of Measurement Customer Satisfaction to NSO Products for Enhancing Quality

  • Choi, Kyung-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.781-790
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    • 2005
  • Nowaday, statistical data with coherence, accuracy and timeliness are necessary to government, company and research center for decision making or research. In other words, the importance of statistical data quality is steadily increasing. Thus, in this paper, we suggest necessity of measuring customer satisfaction with NSO products for enhancing quality. And we construct measurement scale for measuring customer satisfaction based on the statistical quality indicators. Also we advise use of structural equation model in relation analysis for statistic quality elevation.

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Empirical Analysis of 3 Statistical Models of Hospital Bankruptcy in Korea (병원도산 예측모형의 실증적 비교연구)

  • 이무식;서영준;양동현
    • Health Policy and Management
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    • v.9 no.2
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    • pp.1-20
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    • 1999
  • This study was conducted to investigate the predictors of hospital bankruptcy in Korea and to examine the predictive power for 3 types of statistical models of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 30 bankrupt and 30 profitable hospitals in 1. 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the predictive power of statistical models of hospital bankruptcy were compared. The major findings are as follows. 1. Nine out of 21 indicators - fixed ratio, quick ratio, operating profit to total assets, operating profit to gross revenue, normal profit to total assets,normal profit to gross revenue, net profit to gross revenue, inventories turnrounds, and added value per adjusted patient - were found to be significantly predictitive variables in Logit and Probit models. 2. The predicdtive power of discriminant model of hospital bankruptcy in 1. 2, and 3 years before bankruptcy were 85.4, 79.0, and 83.8% respectively. With regard to the predictive power of the Logit model of hospital bankruptcy, they were 82.3, 75.8, and 80.6% respectively, and of the Probit model. 87.1. 80.6, and 88.7% respectively. 3. The predictive power of the Probit model of hospital bankruptcy is better than the other two predictive models.

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Statistical Approach to Test Construct Validity and Obtain Weights for the Children's Dietary Life Recognition and Practice Index (우리나라 초등학교 어린이의 식생활 인지.실천 수준 평가지표 구성타당도 평가 및 산정방법 연구)

  • Kwon, Se-Hyug;Kim, Hye-Young P.;Lee, Jung-Sug;Kwa, Tong-Kyung;Chung, Hae-Rang;Choi, Young-Sun;Kang, Myung-Hee
    • Journal of Nutrition and Health
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    • v.44 no.1
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    • pp.41-48
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    • 2011
  • Constructs with seven latent evaluation indicators and 18 observable survey questions were developed by food and nutrition experts to calculate a food safety recognition and practice index for children. The purpose of this study was to suggest statistical approaches to test construction validity on the constructs, obtain weights of the evaluation indicators, and develop questionnaires to calculate a children's food recognition and practice index. Survey data of 2,400 elementary fifth grade students were used as empirical results. Test validity was evaluated by exploratory factor analysis and confirmed to be highly significant by confirmatory factor analysis [i.e., linear structural relations (LISREL) analysis]. Standardized path coefficients of the LISREL analysis were suggested based on weights, and the weights were compared using the AHP and Delphi methods.

Comparison of National Occupational Accident Fatality Rates using Statistical Analysis on Economic and Social Indicators (경제⋅사회지표의 다변량 통계 분석을 활용한 국가 간 산업재해 사고사망 상대수준 비교)

  • Kyunghun, Kim;Sudong, Lee
    • Journal of the Korean Society of Safety
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    • v.37 no.6
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    • pp.128-135
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    • 2022
  • The comparative evaluation of occupational accident fatality rates (OAFRs) of different countries is complicated owing to the differences in their level of socio-economic development. However, such evaluation is necessary to assess the national occupational safety and health system of a country. This study proposes a statistical method to compare the OAFRs of countries taking into consideration the difference in their level of socio-economic development. We first collected data on the socio-economic indicators and OAFRs of 11 countries over a 30-year period. Next, based on literature survey and statistical correlation analysis, we selected the significant independent variables and built multiple linear regression models to predict OAFR. We also determined the groups of countries having heterogeneous relationships between the independent variables and OAFRs, which are represented by the regression models. The proposed method is demonstrated by comparing the OAFR of Korea with the OAFRs of 10 other developed countries.

Discriminant Model for Pattern Identifications in Stroke Patients Based on Pattern Diagnosis Processed by Oriental Physicians (전문가 변증과정을 반영한 중풍 변증 판별모형)

  • Lee, Jung-Sup;Kim, So-Yeon;Kang, Byoung-Kab;Ko, Mi-Mi;Kim, Jeong-Cheol;Oh, Dal-Seok;Kim, No-Soo;Choi, Sun-Mi;Bang, Ok-Sun
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.23 no.6
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    • pp.1460-1464
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    • 2009
  • In spite of many studies on statistical model for pattern identifications (PIs), little attention has been paid to the complexity of pattern diagnosis processed by oriental physicians. The aim of this study is to develop a statistical diagnostic model which discriminates four PIs using multiple indicators in stroke. Clinical data were collected from 981 stroke patients and 516 data of which PIs were agreed by two independent physicians were included. Discriminant analysis was carried out using clinical indicators such as symptoms and signs which referred to pattern diagnosis, and applied to validation samples which contained all symptoms and signs manifested. Four Fischer's linear discriminant models were derived and their accuracy and prediction rates were 93.2% and 80.43%, respectively. It is important to consider the pattern diagnosis processed by oriental physicians in developing statistical model for PIs. The discriminant model developed in this study using multiple indicators is valid, and can be used in the clinical fields.

Statistical bias indicators for the long-term displacement of steel-concrete composite beams

  • Moreno, Julian A.;Tamayo, Jorge L.P.;Morsch, Inacio B.;Miranda, Marcela P.;Reginato, Lucas H.
    • Computers and Concrete
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    • v.24 no.4
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    • pp.379-397
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    • 2019
  • Steel-concrete composite beams are widely employed in constructions and their performance at the serviceability stage is of concern among practitioners and design regulations. In this context, an accurate evaluation of long-term deflections via various rheological concrete models is needed. In this work, the performance and predict capability of some concrete creep and shrinkage models ACI, CEB, B3, FIB and GL2000 are ascertained, and compared by using statistical bias indicators. Ten steel-concrete composite beams with existing experimental and numerical results are then modeled for this purpose. The proposed modeling technique uses the finite element method, where the concrete slab and steel beam are modeled with shell finite elements. Concrete is considered as an aging viscoelastic material and cracking is treated with the common smeared approach. The results show that when the experimental ultimate shrinkage strain is used for calibration, all studied rheological models predict nearly similar deflections, which agree with the experimental data. In contrast, significance differences are encountered for some models, when none calibration is made prior to. A value between twenty and thirty times the cracking strain is recommended for the ultimate tensile strain in the tension stiffening model. Also, increasing the relative humidity and decreasing the ambient temperature can lead to a substantial reduction of slab cracking for beams under negative flexure. Finally, there is not a unique rheological model that clearly excels in all scenarios.

Consideration of Limitations related to the International Comparison of Statistics on Fatal Occupational Injuries per 100,000 Workers (산재 사망십만인률 국제비교와 관련된 한계점 고찰)

  • Kim, Jin Hyun;Seo, Dong-Hyun;Kang, Sung yun;Baek, Bitna;Bae, Gye wan
    • Journal of the Korean Society of Safety
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    • v.36 no.4
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    • pp.99-107
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    • 2021
  • This study analyzes the differences in definitions and concepts of terms used in the statistical indicators of fatal occupational injuries per 100,000 workers among countries included in the ILOSTAT data explorer. In addition, improvement measures focusing on the limitations in international comparison are proposed. Five countries-the Republic of Korea, Germany, Japan, United Kingdom, United States-- were comparatively analyzed. These countries were selected according to the significance of differences in their definitions of workplace injuries, workers, and compensation insurance, and their reporting systems. Considering these differences before directly comparing statistical indicators of fatal occupational injuries per 100,000 workers among countries is necessary because the range of comparison groups and the definition of fatal occupational injury are different for each country. While one can also compare trends by country, it is necessary to investigate beforehand whether the criteria and methods for processing statistics have changed. Misinterpretation can be minimized by properly understanding the process and limitations of fatal occupational statistical indicators that may differ from country to country.

Development of the Sentiment Indicators of Housing Welfare (주거복지지표 개발에 관한 연구 II - 수요자 측면의 주거복지체감지표와 지수를 중심으로 -)

  • Jee, Eun-Young;Eun, Nan-Soon;Hong, Hyung-Ock
    • Journal of the Korean housing association
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    • v.19 no.5
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    • pp.85-92
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    • 2008
  • The aim of this research is to develop the sentiment indicators of housing welfare for evaluating housing welfare policies conducted by the Korean government. The methods of this research are used by analysis of related documents, FGI (Focus Group Interview), and survey. The survey was made by experts and consumers. To analyze the survey, this research also uses confirmatory factor analysis by SPSS (Statistical Package for the Social Science) program, AHP (Analytical Hierarchy Process) by Expert Choice program, frequency, average, percentages, Factor analysis etc. As a result of this research, selected housing welfare indicators are settled as follows: In the housing welfare aspect, 11 indicators in the department of 'Housing Satisfaction' and 11 indicators in the department of 'Community Satisfaction' (22 in total) are suggested. The indicators are 1) Water Supply and Distribution Equipment 2) Heating equipment 3) the size of the exclusive residential area 4) the number of rooms 5) Ventilation and Lighting 6) Sound Insulation (Indoor Noise) 7) Air Pollution/Odor 8) House Deposit 9) Rent Paid 10) Maintenance (Dwelling) Cost 11) The length of Occupation 12) Proximity to Welfare Facilities 13) Educational Environment 14) Convenience of Facilities (shops, hospitals etc.) 15) Convenience of Transportation and Commuting 16) Distance from Workplace 17) Landscape and Green Space (Tree, Flowers, Grass etc.) 18) Vandalism (Destruction Behavior, graffiti etc.) 19) Privacy 20) Noise in Public Places (Drinking, Loudly Talking etc.) 21) Safety from Crime 22) Safety from a Disaster. As of 2007, the housing welfare sentiment index is measured by the survey of 1,000 inhabitants in the public housing, which shows 3.51.