scholarly journals PROBLEMS OF APPLICATION OF DECISION-MAKING MODELS IN THE REGIONAL ECONOMY UNDER CONDITIONS OF PARTIALLY RELIABLE INFORMATION

2021 ◽  
Vol 10 (06) ◽  
pp. 70-79
Author(s):  
Vidadi Akhundov Vidadi Akhundov
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Content Analysis ◽  
Data Analysis ◽  
Industry 4.0 ◽  
Value Added ◽  
High Tech ◽  
Clustering Method ◽  
Process Data ◽  
The World

In this study, attention is drawn to the under-explored area of strategic content analysis and the development of strategic vision for managers, with the supporting role of interpreting visualized big data to apply appropriate knowledge management strategies in regional companies. The study suggests improved models that can be used to process data and apply solutions to Big Data. The paper proposes a model of business processes in the region in the context of information clusters, which become the object of analysis in the conditions of active accumulation of big data about the external and internal environment. Research has shown that traditional econometric and data collection techniques cannot be directly applied to Big Data analysis due to computational volatility or computational complexity. The paper provides a brief description of the essence of the methods of associative and causal data analysis and the problems that complicate its application in Big Data. The scheme of accelerated search for a set of causal relationships is described. The use of semantically structured models, cause-effect models and the K-clustering method for decision making in big data is practical and ensures the adequacy of the results. The article explains the stages of applying these models in practice. In the course of the study, content analysis was carried out using the main methods of processing structured data on the example of the countries of the world using synthetic indicators showing the trends of Industry 4.0. When assessing Industry 4.0 technologies by region, the diversity of country grouping attributes should be considered. Therefore, during the analysis, the countries of the world were compared in two groups. The first group - the results for developed countries are presented in tabular form. For the second group, the results are presented in an explanatory form. In the process of assessing industrial 4.0 technologies, statistical indicators were used: "The share of medium and high-tech activities", "Competitiveness indicators", "Results in the field of knowledge and technology", "The share of medium and high-tech production in the total value added in the manufacturing industry", “Industrial Competitiveness Index (CIP score)”. As a result, the rating of the countries was determined based on the analysis of these indicators. . The reasons for the difficulties of calculations when processing Big Data are given in the concluding part of the article. Keywords: K - clustering method, causal links, data point, Euclidean distance

scholarly journals Big Data-Driven Macroeconomic Forecasting Model and Psychological Decision Behavior Analysis for Industry 4.0

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jie Liu
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Behavior Analysis ◽  
Industry 4.0 ◽  
Value Added ◽  
Complete Information ◽  
Data Driven ◽  
Macroeconomic Forecasting ◽  
The Government ◽  
Decision Making Behavior

With the advent of Industry 4.0, economic development has become a rapid information age. The content of macroeconomic forecast is very extensive, and the existence of big data technology can provide the government with multilevel, diversified, and complete information and comprehensively process, integrate, summarize, and classify these pieces of information. This paper forecasts the CPI value in the next 12 months according to the CPI in China in the recent 20 years. Compared with the traditional forecasting methods, the forecasting results have higher accuracy and timeliness. At the same time, the trend of growth rate of industrial value-added is analyzed, and the experiments on MAE and RMSE show that the method proposed in this paper has obvious advantages. It also analyzes the disadvantages of traditional psychological decision-making behavior analysis, introduces the development status and advantages of big data-driven psychological decision-making behavior analysis, and opens up new research ideas for psychological decision-making analysis.

scholarly journals Implementasi Big Data Analytical Untuk Perguruan Tinggi Menggunakan Machine Learning

2021 ◽  
Vol 2 (1) ◽  
pp. 77-88
Author(s):  
Rakhmat Purnomo ◽  
Wowon Priatna ◽  
Tri Dharma Putra
Keyword(s):  
Higher Education ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Student Performance ◽  
Big Data Analytics ◽  
Big Data Analysis ◽  
Process Data ◽  
Grouping Students

The dynamics of higher education are changing and emphasize the need to adapt quickly. Higher education is under the supervision of accreditation agencies, governments and other stakeholders to seek new ways to improve and monitor student success and other institutional policies. Many agencies fail to make efficient use of the large amounts of available data. With the use of big data analytics in higher education, it can be obtained more insight into students, academics, and the process in higher education so that it supports predictive analysis and improves decision making. The purpose of this research is to implement big data analytical to increase the decision making of the competent party. This research begins with the identification of process data based on analytical learning, academic and process in the campus environment. The data used in this study is a public dataset from UCI machine learning, from the 33 available varibales, 4 varibales are used to measure student performance. Big data analysis in this study uses spark apace as a library to operate pyspark so that python can process big data analysis. The data already in the master slave is grouped using k-mean clustering to get the best performing student group. The results of this study succeeded in grouping students into 5 clusters, cluster 1 including the best student performance and cluster 5 including the lowest student performance

Medical Diagnosis from a Clinician’s Point of View

1978 ◽  
Vol 17 (01) ◽  
pp. 28-35
Author(s):  
F. T. De Dombal
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Computer Science ◽  
Medical Diagnosis ◽  
Information Science ◽  
Point Of View ◽  
Joint Research ◽  
The World

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.

scholarly journals Sharia Philosophy Correlation and the Islamic Economic Philosophy

2021 ◽  
Vol 1 (1) ◽  
pp. 12-20
Author(s):  
Hendrianto Hendrianto ◽  
Juhaya S. Praja ◽  
Nurrahman
Keyword(s):  
Content Analysis ◽  
Data Analysis ◽  
Philosophical Foundation ◽  
Islamic Philosophy ◽  
Library Research ◽  
The World ◽  
Economic Philosophy ◽  
Islamic Economic ◽  
The Relationship ◽  
Economic Studies

This study aims to reveal the relationship between Islamic philosophy and Islamic economic philosophy, both in terms of foundation, operation, and objectives. This library research (Library Research) uses documentation data collection techniques with data analysis, namely content analysis. The results showed that the relationship between sharia philosophy and sharia economic philosophy is that there is a philosophical foundation based on al-qur'am, hadith, ijma 'and qiyas, as well as operational principles, observations are made, take generalization conclusions and serve as theory, while the goal is both want to get happiness in the world and the hereafter, but what distinguishes the two lies in the broader study of sharia philosophy and complexity, while Islamic economic philosophy specializes in sharia economic studies. But for sharia economic philosophy discusses tauhid, caliphate, tazkiyah, and masuliyya. Operational principles, observing, drawing conclusions and making theory. The goal of obtaining falah, namely survival, freedom of desire, and strength and honor.

scholarly journals Idea Management Systems as a Tool for Goals’ Setting & Achieving and Decision Making: Global Research Results

2021 ◽  
Vol 129 ◽  
pp. 05008
Author(s):  
Elina Mikelsone ◽  
Tatjana Volkova ◽  
Aivars Spilbergs ◽  
Elita Liela
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Collection ◽  
Idea Generation ◽  
Value Added ◽  
Scientific Data ◽  
Web Based ◽  
Ongoing Research ◽  
Research Results ◽  
Idea Management

Research background: the authors have explored that there are different idea management system (IMS) application types that could be used both locally and globally for diverse reasons and expected outcomes. There is ongoing research on how IMS could be applied for manageable idea management process. But there is a question – how do these IMS types help to set and achieve goals, and improve decision making? Purpose of the article: The article aims to clarify how an external and mixed web-based IMS could be used during COVID19 time for distance idea generation sessions, as well as, to solve complex issues such as decision making, goals’ setting and reaching them based on different idea generation sources and critical reflection on those ideas of evaluators. Methods: Literature review (data collection: systematic data collection from scientific data bases; data analysis: content analysis). The survey of n>400 enterprises with web-based IMS experience globally (data collection: a survey; data analysis: statistics). Findings & Value added: this paper explores how different types of web-based IMS could be applied as a tool and support system for decision making processes in general, decisions towards goal setting and its outreach. The research results provide also a practical contribution - it could help to choose the most appropriate IMS application type to reach estimated goals and to empower decision making.

Through the Time Barrier: Art and Design in the Digital Age

APRIA Journal ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 35-50
Author(s):  
Marijke Goeting
Keyword(s):  
Big Data ◽  
Fundamental Problem ◽  
Digital Age ◽  
Fast Computation ◽  
Process Data ◽  
Art And Design ◽  
The Past ◽  
Works Of Art ◽  
The World ◽  
Time Frames

During the past decade, computers have broken through the barrier of human time. Today, computers can process data in milli-, micro- and even nanoseconds and can (inter) act autonomously in time frames that exceed our capacity to perceive and respond to. This produces a fundamental problem – a gap between human time and the time of computers – and raises important questions: how do big data and fast computation affect our experience and understanding of time? If a computer is able to deal with the world faster than we can, are we doomed to live forever in the past, however near the present? Or are we dealing with a technological extension of the present, and how might we be able to understand and experience this? By analysing theory and works of art, this text examines how to deal with the shock produced by microtemporal technologies.

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