• Journal of Internet of Things and Convergence
• /
• v.8 no.3
• /
• pp.69-74
• /
• 2022

Big data related analysis techniques, the prescriptive analytics methodology improves the performance of passive learning models by ensuring that active learning secures high-quality learning data. Prescriptive analytics is a performance maximizing process by enhancing the machine learning models and optimizing systems through active learning to secure high-quality learning data. It is the best subscription value analysis that constructs the expensive category data efficiently. To expand the value of data by collecting research field, research propensity, and research activity information, customized researcher through prescriptive analysis such as predicting the situation at the time of execution after data pre-processing, deriving viable alternatives, and examining the validity of alternatives according to changes in the situation Provides research information service.

• Journal of applied mathematics & informatics
• /
• v.34 no.1_2
• /
• pp.75-84
• /
• 2016

The objective of this work is to perform a geometric analysis of the net present value (NPV) and Internal Rate of Return (IRR), defining analytics and in verifying the relationship between geometric properties of such functions. For this simulation, was used the values of the cash flows for each period identical and equal to US$ 200.00 cash, the initial investment US$ 1,000.00 and investments of each identical and equal to US$ 50.00 period. In addition, the discount rate and time were considered a maximum of 2 years (24 months) at a rate between 0 and 100%. The geometric analysis of the characteristics obtained from the expressions of the Net Present Value and Internal Rate of Return possible to observe that besides the analytical dependence between these quantities , the geometric relationships are relevant when studied in relation to the zero NPV and expressed a great contribution the sense of a broad vision for the administrator in the analysis of analytical variables that in uences the balance sheet of the company.

• International journal of advanced smart convergence
• /
• v.10 no.4
• /
• pp.72-83
• /
• 2021

The use of the predictive analytics (PA) powered by the artificial intelligence (AI) is more important in the movie sector during the COVID-19 pandemic, because Hollywood witnessed the impact of the 'Netflix Effect' and began to invest in data and AI. Our purpose is to discover a few cases of the AI centered PA in the movie industry value chain based on five objectives of PA: Compete, grow, enforce, improve, and satisfy. Even if movie companies' interest is to predict future success for competing with over-the-tops (OTTs) at a first glance, it is observed, once they start to use the PA with the AI, they try to utilize the enhanced PA platforms for remaining four objectives. As a result, ScriptBook, Vault, Pilot, Cinelytic and Merlin Video (Merlin) are use cases for the objective 'compete.' Movio of Vista Group International and Datorama of Salesforce are use cases for the objective 'grow.' Industrial Light & Magic (ILM) and Geena Davis Institute on Gender in Media (GDI) with Disney are use cases for the objective 'enforce.' Watson, Benjamin, and Greenlight Essential are use cases for the objective 'improve.' Disney Research (DR) with Simon Fraser University and California Institute of Technology is the use case for the objective 'satisfy.'

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.2
• /
• pp.93-102
• /
• 2022

The goal of this study was to see how big data analytics (BDA) affected external audit procedures in the Middle East. The measurement model and structural model of this investigation were evaluated using PLS-SEM (3.3.3). The study sample members were (361) auditors who work in auditing companies in Kuwait, Saudi Arabia, the United Arab Emirates, Jordan, Bahrain, Egypt, Lebanon, and Iraq. A questionnaire was chosen to the study sample members electronically, and the study sample members were (5093) auditors who work in auditing companies in Kuwait, Saudi Arabia, the United Arab Emirates, Jordan, Bahrain, Egypt, Lebanon, and Iraq. To choose the sample, the researchers used a stratified random sampling procedure. The findings show that BDA has an impact on audit procedures at all phases of the auditing process, where it contributes to information delivery that helps auditors understand the client's internal and external environments, which in turn influences the choice to accept the audit assignment. Furthermore, by providing essential information, BDA enables auditors to simply run analytical procedures, estimate client risks, and understand and evaluate the internal control system. As a result, auditors must develop their abilities in the BDA field, as it adds to the creation of additional value for both auditors and their clients.

• Journal of the Korea Computer Graphics Society
• /
• v.23 no.4
• /
• pp.21-29
• /
• 2017

Previous visual analytics researches has focused on reducing the uncertainty of predicted results using a variety of interactive visual data exploration techniques. The main purpose of the interactive search technique is to reduce the quality difference of the predicted results according to the level of the decision maker by understanding the relationship between the variables and choosing the appropriate model to predict the unknown variables. However, it is difficult to create a predictive model which forecast time series data whose overall trends is unknown such as youth physical growth data. In this paper, we pro pose a novel predictive analysis technique to forecast the physical growth value in small pieces of time series data with un certain trends. This model estimates the distribution of data at a particular point in time. We also propose a visual analytics system that minimizes the possible uncertainties in predictive modeling process.

• International Journal of Computer Science & Network Security
• /
• v.23 no.1
• /
• pp.33-40
• /
• 2023

Machine-learning techniques are discovering effective performance on data analytics. Classification and regression are supported for prediction on different kinds of data. There are various breeds of classification techniques are using based on nature of data. Threshold determination is essential to making better model for unlabelled data. In this paper, threshold value applied as range, based on min-max normalization technique for creating labels and multiclass classification performed on rainfall data. Binary classification is applied on autism data and classification techniques applied on child abuse data. Performance of each technique analysed with the evaluation metrics.

• Asia pacific journal of information systems
• /
• v.29 no.4
• /
• pp.673-689
• /
• 2019

The Internet enables businesses to acquire a great deal of information, including prices in the open markets. In this study, we investigate what the value of reference price information is to a company in the market and how the company can make use of such information. Using business analytics, we were able to estimate prices of used cars for a rent-a-car company. The results show that a smart pricing information system is useful for collecting online reference price information and for estimating future prices of used cars and rental prices.

• Journal of Digital Convergence
• /
• v.15 no.9
• /
• pp.167-178
• /
• 2017

Big Data is a key asset for the company and a key factor in boosting its competitiveness in the logistics sector. However, there is still a lack of research on how to collect, analyze and utilize Big Data in logistics. In this context, this study has developed a value model applicable to logistics companies based on the results of analysis and application of Big Data in the logistics of previous studies and DHL. The purpose of this study is to improve the operational efficiency and customer experience maximization level of logistics companies through utilization of big data analysis in logistics, to improve competitiveness of big data utilization and to develop new business opportunities. This study has a significance to newly create a value model for utilization of big data analysis in logistics sector and can provide implications for other industries as well as logistics sector in the future.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.15 no.1
• /
• pp.1-7
• /
• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• Asia pacific journal of information systems
• /
• v.32 no.4
• /
• pp.890-915
• /
• 2022

Although existing studies on e-health have usually focused on e-health services adoption intention, there is a dearth of studies on the barriers that affect e-health services retention intention especially in India. Additionally, although studies have mostly focused on utilizing expectation-confirmation model to understand innovation related barriers, innovation resistance theory (IRT) has been overlooked. As Indian e-health service providers face stiff challenges due to customer's unwillingness to continue using the service, there is a need to bridge the research gap that exists in this context. This mixed-method study, based on responses received from 289 participants and 1154 online negative reviews from e-Health providers in India, examines the barriers from the IRT stance. Results of this study reveal a notable negative association between tradition, value and financial barrier and intention to continue using e-health services. Additionally, continuance intention affects recommendation. The study concludes with various implications and scope for future research.