Export Data Research Articles

Enhancing handicraft exports in West Java: A business intelligence approach to market expansion

The creative industries in West Java have significantly boosted the region's economy, contributing to higher GDP, more jobs, and increased exports. However, the handicraft sector seeks to grow its presence in the international market, where it currently holds a minor share. To address the challenges of expanding, such as limited information, marketing obstacles, and regulatory hurdles, the handicraft industry is encouraged to adopt a business intelligence (BI) platform. This study aims to use a BI platform to present and analyze export data for West Java's craft industry, examining its distribution, trends, and future prospects to help increase exports from this Indonesian province. The analysis employs clustering with k-means, time series analysis, and forecasting methods, including exponential smoothing and the compound annual growth rate (CAGR), using export data from 2018 to 2022. The process involves collecting primary and secondary data, transforming it through ETL (Extract, Transform, Load) technology, and integrating it into the BI platform for analysis. This analysis aims to identify export patterns, trends, and make forecasts that can guide decision-making. The findings indicate that handicraft exports are categorized into three destination country clusters, each favoring different product types, revealing trends and growth opportunities for various handicraft items. Additionally, the study provides forecasts for handicraft exports, offering valuable insights for strategic planning.

Simplifying Multimodal Clinical Research Data Management: Introducing an Integrated and User-friendly Database Concept.

Clinical research, particularly in scientific data, grapples with the efficient management of multimodal and longitudinal clinical data. Especially in neuroscience, the volume of heterogeneous longitudinal data challenges researchers. While current research data management systems offer rich functionality, they suffer from architectural complexity that makes them difficult to install and maintain and require extensive user training. The focus is the development and presentation of a data management approach specifically tailored for clinical researchers involved in active patient care, especially in the neuroscientific environment of German university hospitals. Our design considers the implementation of FAIR (Findable, Accessible, Interoperable, and Reusable) principles and the secure handling of sensitive data in compliance with the General Data Protection Regulation. We introduce a streamlined database concept, featuring an intuitive graphical interface built on Hypertext Markup Language revision 5 (HTML5)/Cascading Style Sheets (CSS) technology. The system can be effortlessly deployed within local networks, that is, in Microsoft Windows 10 environments. Our design incorporates FAIR principles for effective data management. Moreover, we have streamlined data interchange through established standards like HL7 Clinical Document Architecture (CDA). To ensure data integrity, we have integrated real-time validation mechanisms that cover data type, plausibility, and Clinical Quality Language logic during data import and entry. We have developed and evaluated our concept with clinicians using a sample dataset of subjects who visited our memory clinic over a 3-year period and collected several multimodal clinical parameters. A notable advantage is the unified data matrix, which simplifies data aggregation, anonymization, and export. THIS STREAMLINES DATA EXCHANGE AND ENHANCES DATABASE INTEGRATION WITH PLATFORMS LIKE KONSTANZ INFORMATION MINER (KNIME): . Our approach offers a significant advancement for capturing and managing clinical research data, specifically tailored for small-scale initiatives operating within limited information technology (IT) infrastructures. It is designed for immediate, hassle-free deployment by clinicians and researchers.The database template and precompiled versions of the user interface are available at: https://github.com/stebro01/research_database_sqlite_i2b2.git.

THE ELECTRONIC SYSTEM FOR THE MANAGEMENT OF UNIVERSITY EDUCATIONAL PROGRAMS

The article presents the research results of the electronic system for managing university educational programs (EP). The analysis of scientific works showed that higher educational institutions need the introduction of integrated information systems. Such systems are the technical basis of the electronic university and have functionality for managing education and providing communications to university management. An analysis of the main processes of EP management was performed, and interested parties, their roles, and participation in the methods were determined. The proposed mathematical model is the basis of management for introducing the EP, its development, and implementation control based on quality parameters. The software module is a part of the university's management process support system and the JetIQ of Vinnytsia National Technical University's (VNTU's) comprehensive information system. For the analysis of the subject area and the formation of optimal management processes, the methodological recommendations of the National Agency for Higher Education Quality Assurance (NAQA), data export and import system for the Unified State Electronic Database on Education Issues, the experience, and recommendations of experts from the department of quality assurance of education of VNTU, experts and guarantors of educational programs were used. Precedent models are formed about such role scenarios – applicant, student, teacher, guarantor, management, expert, stakeholder (employer). Such models made it possible to create not only the software module for the management of educational programs (QEd – Quality Educational) but also to determine the conditions for publication on the main website of VNTU of educational programs and documentation of their development, syllabi on the foremost showcase and jet-sites of the department, to create scenarios for automatic quality control of the EP. The result of the creation of the software module for the management of educational programs is a system of structured information regarding the development and implementation of the educational program, which allows the guarantor and specialists of the department to ensure the quality of education by use special containers for documentation and interested parties to use public up-to-date information on the university's websites.

Does geopolitical risk affect exports? Evidence from China

Geopolitical conflicts and power games among major nations present substantial challenges to cross-border trade and global economic development; however, the existing literature has given limited attention to the underlying macroimpact mechanisms, especially the pivotal role of outward foreign direct investment (OFDI). This paper utilizes export data spanning 2003–2021 to empirically investigate the influence of geopolitical risk on China's exports and unveil its specific internal mechanisms. The findings reveal that China's exports are negatively affected when its trading partners are exposed to geopolitical risk. Notably, China's OFDI is instrumental in mitigating the adverse effects of geopolitical risk on exports. Moreover, the heterogeneity analysis shows that the impact of geopolitical risk on China's exports is more significant in non-Belt and Road countries than in Belt and Road countries. Furthermore, the impact of geopolitical risk on exports also shows significant differences before and after the 2008 financial crisis.

Time Series Model to Forecast Fresh Coconut Exports from Sri Lanka

Coconut accounts for approximately 12% of all agricultural produce in Sri Lanka with the total land area under cultivation covering 409, 244 hectares ranking second to rice production. The primary regions for coconut cultivation are the Puttalam and Kurunegala districts in North-Western Province and Gampaha district in the Western Province, forming what is known as the Coconut Triangle. This region accounts for 232,270 hectares (50.94%) of the overall coconut cultivation area. The remaining coconut cultivation areas are found in the Southern Province, specifically in the districts of Galle (13,833 hectares), Matara (14,946 hectares), and Hambantota (25,837 hectares), and in non-traditional regions of the Eastern and Northern provinces. The annual coconut production varies between 2,800 to 3,000 million nuts. Having advanced knowledge of exporting coconuts offers numerous advantages to Sri Lanka, particularly in terms of establishing forward contracts with other countries. Based on secondary data of annual fresh coconut exports from 1981 to 2020 obtained from the Coconut Development Authority (CDA) of Sri Lanka, the paper developed ARIMA (2,1,0) model to forecast export. The model was selected out of three parsimonious models which were identified from the Sample Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) of the stationary series and a comparison of significant parameters and lowest values of Akaike Information Criterion (AIC), Schwarz Bayesian Information Criterion (SBIC) and Hannan-Quinn Information Criterion (HQIC). The errors of the fitted model were found to be random and constant variance. The model was validated using 2021 and 2022 data. The percentage errors for 2021 and 2022 are 20.23% and -29.57% respectively. The predictions for 2023 and 2024 are 14696 and 15052 respectively. The model can be used effectively by the Coconut Development Authority for decision-making. However, it is suggested to develop the model further to reduce the percentage error. Keywords: ARIMA model, Forecast, Fresh Coconut Exports and Validate

Agri‐food trade liberalization, export prices, and quality upgrading: Evidence from the meat and chocolate sectors in OECD countries

AbstractThis article examines the impact of trade liberalization on export prices and quality. The article is innovative in two respects. First, unlike previous studies, it considers both input and output tariffs simultaneously in a theoretical model. Second, it empirically tests the effects of a combination of specific and ad‐valorem tariffs on quality improvement. The theoretical analysis suggests that when firms face reduced output and input tariffs, they tend to improve their export quality and increase export prices. Using export data from 33 OECD countries, the empirical analysis demonstrates that output tariff reduction increases export quality but decreases prices. However, the effects of input tariff reduction on price and quality depend on product differentiation. The results also indicate that the presence of specific tariffs increase product quality while amplifying the positive effects of the reduction of ad‐valorem tariffs on quality. This implies that to improve export quality, reducing ad‐valorem tariffs is more efficient than a specific tariff. [EconLit Citations: F12, F14, Q17].

The Effect Of Visa Exemption Policy On Indonesian Export

This study examines the effect of the visa exemption policy on Indonesia’s exports, by using Staggered Difference in Difference (DID) method and Indonesia's export data to 191 partner countries in 2015 - 2019 period. This study finds that visa exemption policy of Indonesia has effect on its export, but it is not "one size fits all". A significant positive effect was generated by visa-exemption received by American region, and a significant negative effect on exports was generated by visa exemption received by Oceania region. American region is one of the priority recipients of visa exemption policy of Indonesia, and provides the most visa exemption to Indonesia after the Asian region. Meanwhile, Oceania is the most restricted region in terms of visa exemption policy both unilaterally or reciprocally with Indonesia.
 
 Keywords: Visa Exemption, International Trade, Export, Staggered DID
 JEL Codes: F13, F16, F22

Design of Three-Dimensional Electrical Impedance Tomography System for Rock Samples

Research on the electrical properties of rocks and ores plays a crucial role in the development of geophysical electromagnetism methods. However, currently available instruments suffer from high power consumption, a limited number of electrodes, inaccurate measurements, poor portability, and a limited ability to measure the electrical parameters of rocks and ores. To address these issues, this paper presents a three-dimensional electrical impedance tomography system for rock samples with high-density microelectrodes based on an Android system and STM32 microcontroller. The system features high observation accuracy, dense electrode arrays (with 384 current and potential electrodes), flexible electrode selection, user-friendly human–computer interaction, good stability, and real-time performance. Powered by a single power bank, the entire instrument can be controlled and monitored wirelessly via Bluetooth and Wi-Fi technology using an Android smartphone. Additionally, the system not only enables accurate measurement of electrical parameters, but also facilitates the generation of three-dimensional impedance imaging of specimens via inversion algorithms after data export, allowing for a comprehensive understanding of the electrical properties of rocks and ores. This system holds great potential for future research in this field.

Mapping on Islamic Microfinance Research: Lesson Learn from Indonesia and Turkey

This study reviews the scientific literature on Islamic microfinance in Scopus-indexed journals. This analysis uses descriptive statistical analysis based on 345 papers from 2007 to 2023 related to the theme of Islamic microfinance. The export data was then processed and analyzed using the R-Biblioshiny application program to determine bibliometric visualization maps and topic trends in scientific literature. This bibliometric mapping research shows the mapping of sources, authors, affiliations, countries, documents, keywords, and thematic maps. This research finds that Islamic microfinance is essential in financial relations and sustainable development because it aligns with Islamic principles and encourages inclusive economic growth. In addition, this research also discusses more about Islamic microfinance from Indonesia and Turkey.

State-Dependent Model Based on Singular Spectrum Analysis Vector for Modeling Structural Breaks: Forecasting Indonesian Export

Standard time-series modeling requires the stability of model parameters over time. The instability of model parameters is often caused by structural breaks, leading to the formation of nonlinear models. A state-dependent model (SDM) is a more general and flexible scheme in nonlinear modeling. On the other hand, time-series data often exhibit multiple frequency components, such as trends, seasonality, cycles, and noise. These frequency components can be optimized in forecasting using Singular Spectrum Analysis (SSA). Furthermore, the two most widely used approaches in SSA are Linear Recurrent Formula (SSAR) and Vector (SSAV). SSAV has better accuracy and robustness than SSAR, especially in handling structural breaks. Therefore, this research proposes modeling the SSAV coefficient with an SDM approach to take structural breaks called SDM-SSAV. SDM recursively updates the SSAV coefficient to adapt over time and between states using an Extended Kalman Filter (EKF). Empirical results with Indonesian Export data and simulation studies show that the accuracy of SDM-SSAV outperforms SSAR, SSAV, SDM-SSAR, hybrid ARIMA-LSTM, and VARI.

An Interactive Dashboard for Statistical Analysis of Intensive Care Unit COVID-19 Data

Background: COVID-19 caused a pandemic, due to its ease of transmission and high number of infections. The evolution of the pandemic and its consequences for the mortality and morbidity of populations, especially the elderly, generated several scientific studies and many research projects. Among them, we have the Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine (PREMO) research project. For such a project with many data records, it is necessary to provide a smooth graphical analysis to extract value from it. Methods: In this paper, we present the development of a full-stack Web application for the PREMO project, consisting of a dashboard providing statistical analysis, data visualization, data import, and data export. The main aspects of the application are described, as well as the diverse types of graphical representations and the possibility to use filters to extract relevant information for clinical practice. Results: The application, accessible through a browser, provides an interactive visualization of data from patients admitted to the intensive care unit (ICU), throughout the six waves of COVID-19 in two hospitals in Lisbon, Portugal. The analysis can be isolated per wave or can be seen in an aggregated view, allowing clinicians to create many views of the data and to study the behavior and consequences of different waves. For instance, the experimental results show clearly the effect of vaccination as well as the changes on the most relevant clinical parameters on each wave. Conclusions: The dashboard allows clinicians to analyze many variables of each of the six waves as well as aggregated data for all the waves. The application allows the user to extract information and scientific knowledge about COVID-19’s evolution, yielding insights for this pandemic and for future pandemics.

Instantaneous Electricity Peak Load Forecasting Using Optimization and Machine Learning

Accurate instantaneous electricity peak load prediction is crucial for efficient capacity planning and cost-effective electricity network establishment. This paper aims to enhance the accuracy of instantaneous peak load forecasting by employing models incorporating various optimization and machine learning (ML) methods. This study examines the impact of independent inputs on peak load estimation through various combinations and subsets using multilinear regression (MLR) equations. This research utilizes input data from 1980 to 2020, including import and export data, population, and gross domestic product (GDP), to forecast the instantaneous electricity peak load as the output value. The effectiveness of these techniques is evaluated based on error metrics, including mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE), root mean square error (RMSE), and R2. The comparison extends to popular optimization methods, such as particle swarm optimization (PSO), and the newest method in the field, including dandelion optimizer (DO) and gold rush optimizer (GRO). This comparison is made against conventional machine learning methods, such as support vector regression (SVR) and artificial neural network (ANN), in terms of their prediction accuracy. The findings indicate that the ANN and GRO approaches produce the least statistical errors. Furthermore, the correlation matrix indicates a robust positive linear correlation between GDP and instantaneous peak load. The proposed model demonstrates strong predictive capabilities for estimating peak load, with ANN and GRO performing exceptionally well compared to other methods.

Literature on Tawhidi String Relation (TSR) Concept: A Text Mining

The universal paradigm presents concepts and applications, institutions, and a sustainable future or oneness of divine rule, which is referred to as monotheism. Economics, Finance, Society and Science are sub-systems of the supplemental global order system of Tawhidi String Relation (TSR). This study seeks to figure out the map of the development and trend of TSR published by well-known publications in the field of Economics and Finance. The data analysed were 50 research publications indexed by Google Scholar. The export data is then processed and analysed using the R Biblioshiny application program to determine the bibliometric map of TSR development. The conceptual structure of R 'biblioshiny' displays the network and the main research themes in a thematic map in the development of TSR theme research. The resulting mapping is in the form of most relevant words, word cloud, word treemap, word dynamic, trend topic, co-occurrence network, thematic map and thematic evolution. This study also provides a review of the literature related to the theme of TSR to be developed in future research. This study is the first comprehensive study that discusses the mapping development of trends in the TSR literature published in various scientific journals.

Enhancing BIM-BEM integration: solutions for efficient data exchange and energy performance assessment

ABSTRACT This paper explores the efficiency of exporting data from Building Information Modeling (BIM) to Building Energy Modeling (BEM) and proposes solutions to encountered problems. The study considers both detached and attached buildings, analyzing the impacts of resolution parameters, and evaluating energy performance based on BIM model. A case-study approach is employed using a residential apartment building, with data exported from Autodesk Revit and imported into DesignBuilder. The results demonstrate the significance of adjusting resolution parameters (the primary parameters that influence the energy analytical model's accuracy and processing time) for efficient data export. Exploring different values leads to improvements in resolving unclosed spaces and enhancing the geometrical model of building elements. Challenges persist in allocating material finishes to walls. By improving and integrating energy performance evaluation through enhanced accuracy and efficiency of data exchange, the findings have significant impacts on stakeholders involved in building design, construction, and operation. Additionally, this process can optimize energy consumption in buildings. Further research is needed to address remaining challenges and improve BIM to BEM systems compatibility including the development of smart mechanisms for energy model creation and resolution parameters refinement. Case studies on different building types and long-term performance monitoring are recommended. This research contributes to the efficiency of exporting data from BIM to BEM interfaces, offering insights for practitioners and guiding future research in BIM-BEM tools integration.

GMOCU: Digital Documentation, Management, and Biological Risk Assessment of Genetic Parts.

The continuous evolution of molecular biology and gene synthesis methods paired with an ever-increasing potential of synthetic biology approaches and genome engineering toolkits enables the rapid design of genetic bioparts and genetically modified organisms. Although various software solutions assist with specific design tasks and challenges, lab internal documentation and ensuring compliance with governmental regulations on biosafety assessment of the generated organisms remain the responsibility of individual academic researchers. This results in inconsistent and redundant documentation regimes and a significant time and labor burden. GMOCU (GMO documentation) is a standardized semi-automatic user-oriented software approach -written in Python and freely available- that unifies lab internal data documentation on genetic parts and genetically modified organisms (GMOs). It automatizes biological risk evaluations and maintains a shared up-to-date inventory of bioparts for team-wide data navigation and sharing. GMOCU further enables data export into customizable formats suitable for scientific publications, official biosafety documents, and the research community.

Đánh giá tác động của biện pháp kỹ thuật đến xuất khẩu thủy sản tươi sống và chế biến của Việt Nam

Global free trade movement has emphasized on the role of technical measures as the primary tool to regulate trade. The number of research both theoretically and empirically on this field has expanded significantly, however the results derived are often inconsistent about the magnitude as well as the direction of impact that technical measures impose on trade. This paper aims at contributing to the understading related to the dynamic of technical measures’ impact on trade. Using gravity model and the export data of Vietnam’s fresh and processed seafood, the results of this paper has shown that, SPS measures have positive impact on Vietnam’s fresh seafood trade, however, this impact on Vietnam’s processed seafood is mixed. TBT measures fail to show statistically significant impact on fresh seafood trade volume, however, have a negative impact on processed export. Based on these results, this paper also suggests adequate solutions for Vietnam’s seafood exporter with the aim of promoting trade volume.

Strategi Optimalisasi Perdagangan Ekspor Kopi Di Indonesia Melalui Situs Trademap

Export trade of coffee in Indonesia plays a crucial role in the country's economy; however, challenges and dynamics in the global market demand the development of an optimal strategy to enhance the competitiveness of Indonesian coffee products. This research aims to formulate an optimization strategy for coffee export trade by leveraging information provided by the Trademap website. The research method involves analyzing Indonesian coffee export data from the Trademap site, identifying global market trends, and evaluating relevant trade policies and regulations. The results of this analysis will form the basis for designing a strategy to increase market share and the export value of Indonesian coffee. The proposed strategy includes strengthening product branding, diversifying target export markets, improving the quality and innovation of products, and optimizing the supply chain to enhance logistic efficiency. Additionally, the integration of information technology and communication in trade management is incorporated to expedite information access and minimize business risks. The implementation of this strategy is expected to make a positive contribution to the growth of Indonesia's coffee exports, opening opportunities for access to new markets, and increasing the value-added of products. By tapping into the information potential of the Trademap site and developing adaptive strategies, Indonesia can effectively navigate the dynamics of the global market, strengthen its position as a leading coffee producer, and enhance the well-being of business actors in the coffee sector.

Economic Complexity and Regional Growth in Turkey: Implications for East-West Disparity

ABSTRACT Economic complexity has significant implications for regional imbalances in Turkey, given the pronounced economic differences between its eastern and western provinces. This study aims to provide evidence to support the hypothesis that economic complexity has a significant positive effect on regional growth and long-standing regional imbalances in Turkey prevent the eastern region from benefiting equally from the economic gains of rising complexity. Using annual export data from 2007 to 2020 we calculated economic fitness and economic complexity indexes for the provinces of Turkey. We demonstrate that both economic fitness and economic complexity indexes are important determinants of regional growth in Turkey.

Automated Data Transformation and Feature Extraction for Oxygenation-Sensitive Cardiovascular Magnetic Resonance Images.

Oxygenation-sensitive cardiovascular magnetic resonance (OS-CMR) is a novel, powerful tool for assessing coronary function in vivo. The data extraction and analysis however are labor-intensive. The objective of this study was to provide an automated approach for the extraction, visualization, and biomarker selection of OS-CMR images. We created a Python-based tool to automate extraction and export of raw patient data, featuring 3336 attributes per participant, into a template compatible with common data analytics frameworks, including the functionality to select predictive features for the given disease state. Each analysis was completed in about 2min. The features selected by both ANOVA and MIC significantly outperformed (p < 0.001) the null set and complete set of features in two datasets, with mean AUROC scores of 0.89eatures f 0.94lete set of features in two datasets, with mean AUROC scores that our tool is suitable for automated data extraction and analysis of OS-CMR images.

Prediksi Ekspor Migas Indonesia Dengan Double Exponential Smoothing

In Indonesia, there are several forms of exports, one of which is oil and gas exports. The Double Exponential Smoothing method is a forecasting method that can be used to forecast oil and gas export data. This method uses two smoothing parameters, namely the average smoothing parameter alpha (α), the trend smoothing parameter beta (β). In this study, the population used is data on oil and gas exports in Indonesia. And the sample used is Indonesia's oil and gas export data from January 2020 to October 2021, we get 22 data sourced from the Central Statistics Agency (BPS). The Double Exponential Smoothing method is used because the data to be processed has a trend, both an up and a down trend and gas exports in Indonesia have an up and down pattern. The Double Exponential Smoothing method can also predict the prediction of oil and gas exports in Indonesia in the next months, November 2021 to February 2022. To process the data, the researcher used the Holt Double Exponential Smoothing method .