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International Conference on ICT for Smart Society (ICISS) on Innovation Toward Smart Society and Society 5.0

作者： Irzavika, Nindy Supangkat, Suhono Harso Inst Teknol Bandung Sch Elect Engn & Informat Bandung Indonesia

ISBN: (纸本)9781538665893

Data is new gold which became one of important property because data can give information, knowledge and can be used as a strategic guide that helps executives to know patterns they may not have noticed before. The amount of data on local government income (PAD) generated by each transaction creates a large amount of data, so that appropriate mechanisms and technologies are needed to obtain appropriate information and knowledge. Therefore, descriptive analytics is conducted to give exposure to decision makers about phenomena that occur on PAD in order to become new information for decision makers and as a material consideration in the decision-making process to increase PAD. In this research descriptive analytics is done using data visualization to conduct historical analysis, and to know and understand the current condition. The result of descriptive analytics are able to provide a knowledge of PAD, so it can be used by decision-makers to increase PAD and know the potential PAD.

关键词： descriptive analytics data visualization PAD data analytics

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Developing an edge computing platform for real-time descriptive analytics 5

Developing an edge computing platform for real-time descript...

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IEEE International Conference on Big Data (IEEE Big Data)

作者： Cao, Hung Wachowicz, Monica Cha, Sangwhan Univ New Brunswick People Mot Lab 15 Dineen Dr Fredericton NB E3B 5A3 Canada

ISBN: (纸本)9781538627150

The Internet of Mobile Things encompasses stream data being generated by sensors, network communications that pull and push these data streams, as well as running processing and analytics that can effectively leverage actionable information for transportation planning, management, and business advantage. Edge computing emerges as a new paradigm that decentralizes the communication, computation, control and storage resources from the cloud to the edge of the network. This paper proposes an edge computing platform where mobile edge nodes are physical devices deployed on a transit bus where descriptive analytics is used to uncover meaningful patterns from real-time transit data streams. An application experiment is used to evaluate the advantages and disadvantages of our proposed platform to support descriptive analytics at a mobile edge node and generate actionable information to transit managers.

关键词： Edge computing real-time transit data streams fog computing descriptive analytics Internet of Mobile Things

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A descriptive analytics Tool for Improving Project Human Resource Management: The Importance of Discerning a Project Team Member's Sentiments

A Descriptive Analytics Tool for Improving Project Human Res...

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IEEE AFRICON Conference - Science, Technology and Innovation for Africa

作者： Hans, Robert T. Mnkandla, Ernest Tshwane Univ Technol Dept Comp Sci Pretoria South Africa Univ South Africa Sch Comp Florida South Africa

ISBN: (纸本)9781538627754

Recent research studies indicate a gap in research regarding descriptive and diagnostic analytics across project management knowledge areas. As a result there is mismatch between the information needed by project managers for good decision making and what the current tools provide. This research study purports that a project management intelligence (PMInt) tool which is aimed at assisting project manager to make informed decisions attempts to close this gap. Furthermore, the research proposes additional functional capabilities for the PMInt tool which enables it to fully provide project managers with insightful information (such as trends and patterns of sentiments over time, duration of expressed sentiments) and not just inform managers about sentiment polarity, namely, positive or negative or neutral. The proposed improvements have been incorporated in the prototype of the PMInt tool. The preliminary test results obtained from testing the prototype indicate that the tool will provide project managers with insightful information which will assist project managers to arrive at informed decisions regarding project team members' concerns and views and hence help in stabilizing project teams.

关键词： descriptive analytics Sentiments Software project PMInt Project management

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Etiology of emergency department overcrowding: descriptive analytics of inappropriate accesses at Salerno hospital in Italy

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Journal of Data, Information and Management 2020年第3期2卷 111-120页

作者： Andretta, Vincenzo Fenza, Giuseppe Gallo, Mariacristina Loia, Vincenzo U.O.C. Programmazione Controllo di Gestione e Valutazione Azienda Ospedaliera Universitaria San Giovanni di Dio e Ruggi D’Aragona Salerno 84124 Italy Dipartimento di Scienze Aziendali - Management Innovation Systems University of Salerno SA Fisciano 84084 Italy

Emergency Department (ED) overcrowding is a worldwide problem (Morley et al. 2018). Always, people who present to EDs are required to wait too much. This problem compromises the health management efficacy, the satisfaction of the patients, the quality of the public offered service, also impacting on the indicators of the quality of life. The reasons are different, and there is no all-inclusive solution. This research work is aimed to study the etiology of this problem, providing some evidence useful to support the health management board and to increase the awareness of the citizens. The main contribution is about the analysis of access to an Italian hospital during a timespan of one year. The paper shows the results of descriptive analytics by pointing out some aspects that may mitigate the problem of EDs overcrowding. Among others, one of the most important outcomes of this study is about the rate of appropriateness and inappropriateness of the accesses to the ED, where the meaning of inappropriate access is essentially a situation tractable outside the ED. These results could increase awareness, emphasizing the impact of the number of improper accesses. © Springer Nature Switzerland AG 2020.

关键词： (In) appropriateness of access descriptive analytics Emergency department Health management

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descriptive analytics and Interactive Visualizations for Performance Monitoring of Extension Services Programs, Projects, and Activities

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2023年第1期14卷 660-668页

作者： De Jesus, Noelyn M. Buenas, Lorissa Joana E. Batangas State Univ ARASOF Nasugbu Coll Informat & Comp Sci Batangas Philippines Batangas State Univ ARASOF Nasugbu Batangas Philippines

Providing universities with high technology enabled automation tools to support the administrative decision making processes will enable them to achieve their objectives. For an institution to succeed in its everyday tasks, it should come up with the emerging and modernized management services constituted, among others, by cloud, mobile, and business analytics technology. With this, the institution's operations and management efficiency are ensured. This study aims to develop a system with descriptive analytics named as MET Online Services that will automate and optimize the monitoring of extension services key performance indicators (KPIs) in order to help the institution in making better, data-driven decisions. The dashboards and interactive visualizations of the developed system will provide quick access to real-time progress of the extension services programs, projects, and activities. Results interpretation depicted that the developed system is indeed feasible for implementation, proven to be fully-functional and passed the quality software standards of a Certified Software Quality Assurance Specialist. As the developed system satisfied the users' expectations and requirements, it would be an effective tool for the institution, extension services unit, and community, to make better strategic decisions and continuously deliver quality services to the community.

关键词： Business analytics descriptive analytics dashboards interactive visualizations extension services monitoring key performance indicators KPIs community

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Combining Ad Hoc Text Mining and descriptive analytics to Investigate Public EV Charging Prices in the United States

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ENERGIES 2021年第17期14卷 5240页

作者： Trinko, David Porter, Emily Dunckley, Jamie Bradley, Thomas Coburn, Timothy Colorado State Univ Dept Syst Engn Ft Collins CO 80523 USA Elect Power Res Inst Palo Alto CA 94304 USA

Electric vehicle (EV) charging infrastructure is present all over the United States, but charging prices vary greatly, both in amount and in the methods by which they are assessed. For this paper, we interpret and analyze charging price information from PlugShare, a crowd-sourced EV charging data platform. Because prices in these data exist in a semi-structured textual format, an ad hoc text mining approach is used to extract quantitative price information. descriptive analytics of the processed dataset demonstrate how the prices of EV charging vary with charging level (Direct Current Fast Charging versus Level 2), geographic location, network provider, and location type. Our research indicates that a great deal of diversity and flexibility exists in structuring the prices of EV charging to enable incentives for shaping charging behaviors, but that it has yet to be widely standardized or utilized. Comparisons with estimates of the levelized cost of EV charging illustrate some of the challenges associated with operating and using these stations.

关键词： ad hoc text mining descriptive analytics data wrangling EV charging cost level 2 charging DC fast charging spatial variation

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Developing a Patient Information and descriptive analytics System for Data Actors of University of Bohol Medical and Rehabilitation Center: Towards Policy Making

Developing a Patient Information and Descriptive Analytics S...

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作者： Norma J.Apao Larmie S.Feliscuzo Cherry Lyn C.Sta.Romana College of Computer Studies Cebu Institute of Technology-University

In today’s modern age where the computer has become a way of life, the old method of managing records manually is no longer practical. As the trend towards the utilization of information technology permeates workspaces, the need for accuracy, speed,and high memory data storage is a must. Presented in this paper is the development and deployment of the patient information and descriptive analytics system to provide users with easy access to information critical to the operation of the University of Bohol Medical and Rehabilitation Center. This study is inspired and motivated by the Sustainable Development Goals（SDGs） declared by the United Nations in 2015 and Philippine Health Agenda for 2016-2022. The study desires to help achieve the ongoing Health Agenda of the Philippines focusing on information that is identified as one of the building blocks of health. The study utilized the Structured Analysis and Design Techniques（SADT） to structure,plan and manage the process of developing the system. This study delved into the data management system of the University of Bohol Medical and Rehabilitation Center that uses the manual data processing method. Potential users and data players which include the physiatrist, physical therapists, occupational therapists, staff,and interns of the medical rehabilitation center were interviewed,and the flow of processes in the center was observed to gather relevant data needed in the design and development of the *** descriptive health analytics is developed to help the data players of the university’s health care facility make informed decisions and improve patient health outcomes. The system evaluation results revealed that the system conforms to standards obtaining a score of 3.53 or a descriptive value of Strongly Agree using the ISO 9126 model scored on a four-point Likert scale. This study concluded that the results of the study directly gives an advantage to the management of patient records that enables the data actors to

关键词： Patient Information System Electronic Health Records descriptive analytics Health analytics

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A descriptive analytics of the COVID-19 pandemic in a middle-income country with forward-looking insights

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Healthcare analytics 2024年 5卷 100320-100320页

作者： Bansilan, Norvin P. Rabajante, Jomar F. Institute of Mathematical Sciences and Physics University of the Philippines Los Baños College Laguna 4031 Philippines

The outbreak of COVID-19 unleashed an unprecedented global pandemic, profoundly impacting lives and economies worldwide. Recognizing its severity, the World Health Organization (WHO) swiftly declared it a public health emergency of international concern. In response to this crisis, collaborative efforts have been underway to control the disease and minimize its health and socio-economic impacts worldwide. The COVID-19 epidemic curve holds vital insights into the history of exposure, transmission, testing, tracing, social distancing measures, community lockdowns, quarantine, isolation, and treatment, offering a comprehensive perspective on the nation's response. One approach to gaining crucial insights is through meticulous analysis of available datasets, empowering us to effectively inform future strategies and responses. This study aims to provide descriptive data analytics of the COVID-19 pandemic in the Philippines, summarizing the country's fight by visualizing epidemiological and mobility datasets, revisiting scientific papers and news articles, and creating a timeline of the critical issues faced during the pandemic. By leveraging these multifaceted analyses, policymakers and health authorities can make informed decisions to enhance preparedness, expand inter-agency cooperation, and effectively combat future public health crises. This study seeks to serve as a valuable resource, guiding nations worldwide in comprehending and responding to the challenges posed by COVID-19 and beyond. © 2024 The Authors

关键词： COVID-19 descriptive analytics Epidemic curve Philippines Timeline Visualization

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Applying descriptive and Predictive analytics on Academic Dataset

Applying Descriptive and Predictive Analytics on Academic Da...

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International Conference on Recent Innovations in Electrical, Electronics and Communication Engineering (ICRIEECE)

作者： Phutela, Aanchal Kaur, Harkiran Thapar Inst Engn & Technol Dept Comp Sci & Engn Patiala Punjab India

ISBN: (纸本)9781538659953

Data analytics play an important role in any organization, based on relevant facts that will allows making a better decision. Progression of students greatly affects the organization's future. Analysis of the academic dataset could reveal important insights, which if properly used can help students for their progression. In this paper, the authors have applied descriptive and Predictive analytics on the Academic dataset of students. Mainly the authors have focused on the progression of the student's by using cube technology and cluster analysis approach. For this work, the authors have done the cube designing and fabricate 3 clusters by using k-means algorithms. These clusters placed the similar attribute in one class, on which various models have been applied for making prediction. The deep learning model has given the highest accuracy that is 99.02% in comparison to all other models such as Naive Bayes, Decision Tree and Linear Discriminant Analysis (LDA)

关键词： descriptive analytics Predictive analytics Data Warehouse Online Analytical Processing (OLAP) Visualization

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COMMENTARY UPON descriptive DATA analytics 2

COMMENTARY UPON DESCRIPTIVE DATA ANALYTICS

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2nd International Conference on Inventive Systems and Control (ICISC)

作者： Kaur, Harkiran Phutela, Aanchal Deemed Univ Thapar Inst Engn & Technol Dept Comp Sci & Engn Patiala Punjab India

ISBN: (纸本)9781538608074

Big data analytics assist the organizations and business managers to make decision more efficient by analyzing given data and applying some algorithms upon it. Data analytics is the process in which, we find patterns and draw conclusions about the information with the help of raw data. Mainly, three kinds of analytical approaches are existent for analysis of dataset, including descriptive analytics, predictive analytics and prescriptive analytics. In this paper, authors' focused on comparative analysis of descriptive analytical algorithms, along with their different approaches and applications in different areas. In addition to this, various types of data analytics have also been elaborated, in this paper.

关键词： data analytics descriptive analytics business intelligence

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