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Industrial revolution 4.0 on big data adoption factors on social media users and popularity brands

Journal of Physics: Conference Series 2021年第1期1839卷

作者： W Sardjono G Rama Putra E Selviyanti A Cholidin G Salim Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia Health Department Politeknik Negeri Jember Jember Jawa Timur Indonesia 68124 Law Studi program Faculty of Law University of Muhammadiyah Jakarta Indonesia Post Graduate Program Faculty of Economic Science University of Trisakti Jakarta Indonesia

The purpose of writing this paper is to look at how factors of big data adoption affect the users of social media and brand popularity. The method used in the writing of this paper is by using path analysis and also by doing literature study to find reference material. The results of the analysis indicate that there is influence of big data adoption factors that affect the popularity of the brand. With this research, we get big data model that influence the brand popularity.

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Rubber Plant Disease Diagnostic System Using Technique for Order Preference by Similarity to Ideal Solution

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Procedia computer science 2019年 161卷 484-492页

作者： Ramadiani M. Syahrir Ramadhani Muhammad Labib Jundillah Azainil Faculty of Computer Science and Information Technology Mulawarman University Samrinda Indonesia Magister Program of Information System School of Post Graduate Studies Diponegoro University Semarang Indonesia Faculty of Teacher Training and Education Mulawarman University Samarinda Indonesia

Data from the Plantation Office of East Kalimantan Province, the area of rubber plantations has decreased every year. One of the factors that make productivity of rubber plants low is the presence of pests and diseases. The time limit of an expert is an obstacle in identifying rubber plantations. To overcome this problem, we need an expert system that can identify rubber plant diseases such as an expert. This system was developed to be able to provide solutions in diagnosing rubber plant diseases such as White Root Fungus (Rigidoporus micropus), Upas Mushroom Disease (Corticium salmonicolor), Antraknosa Disease (Colletorichum gloeosporoides), Skin Necrosis (Fusarium sp.), And Cancer Lines (Phytoptora palmivore). This study uses the TOPSIS method. There are four variables used as assessment criteria in this study, namely: the level of damage to the root, the level of damage to the stem, the level of damage to the leaves and the level of damage to the tapping path or the intensity of tapping, with preference values from 0 to 100; none, Very Light Intensity (1), Mild Intensity (3), Medium Intensity (5), Weight Intensity (7) and Very Heavy Intensity (9). Each weight value C1= 0.3; C2= 0.22; C3= 0.28; C4= 0.2. The results of this study compare manual calculations and calculations on the system obtained 99.99% accuracy. This system is expected to help facilitate rubber farmers in identifying diseases and can help experts.

关键词： Rubber Plant Disease East Kalimantan TOPSIS Expert System

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Developing self-adaptive microservice systems: Challenges and directions

arXiv

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arXiv 2019年

作者： Mendonça, Nabor C. Jamshidi, Pooyan Garlan, David Pahl, Claus Post Graduate Program in Applied Informatics University of Fortaleza FortalezaCE Brazil Computer Science and Engineering Department University of South Carolina ColumbiaSC United States School of Computer Science Carnegie Mellon University PittsburghPA United States Faculty of Computer Science Free University of Bozen-Bolzano Bozen-Bolzano Italy

A self-adaptive system can dynamically monitor and adapt its behavior to preserve or enhance its quality attributes under uncertain operating conditions. This article identifies key challenges for the development of microservice applications as self-adaptive systems, using a cloud-based intelligent video surveillance application as a motivating example. It also suggests potential new directions for addressing most of the identified challenges by leveraging existing microservice practices and technologies. Copyright © 2019, The Authors. All rights reserved.

关键词： Adaptive systems

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Improving Students Skills to Solve Elementary Equations in K-12 programs Using an Intelligent Tutoring System

Improving Students Skills to Solve Elementary Equations in K...

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Frontiers in Education (FIE) Conference

作者： Arcanjo Miguel Mota Lopes José Francisco de Magalhães Netto Ricardo A. L. de Souza Andreza Bastos Mourão Thais Oliveira Almeida Dhanielly P. R. de Lima Post-Graduate Program in Informatics (PPGI) Institute of Computing (IComp) Federal University of Amazonas (UFAM) Manaus AM Brazil Institute of Exact Sciences (ICE) Federal University of Amazonas (UFAM) Manaus AM Brazil University of State of Amazonas (UEA) Post-Graduate Program in Informatics (PPGI) Institute of Computing (IComp) Federal University of Amazonas (UFAM) Manaus AM Brazil Department of Science Computer Federal University of Roraima Boa Vista RR Brazil

ISBN: (数字)9781728117461

ISBN: (纸本)9781728117478

This full paper of research to practice category describes an experiment using an Intelligent Tutoring System to support teaching and learning that evolve solutions of first-degree equations. The difficulties encountered in solving algebra problems can make students consider math and related science a difficult task. We propose a Tutor to promote the learning of this class of problems. In this article, we describe the functioning and architecture of the tutor composed by the Interface, Student Model, Tutorial Strategies and Domain Model. Also, a Virtual Assistant was included to motivate students in the learning process. The tutoring strategies that comprise the tutor are projected from models found in the literature. To approximate the interactions of the tutor with the actions of the teachers, Lev Vygotsky's Concept of Zone Proximal Development was used. The methodology used in this project was the case study applied in a real-life context, obtaining a combination of quantitative and qualitative evidence about technical and pedagogical usability that show the degree of satisfaction of the students regarding the proposed approach.

关键词： Education Mathematical model Informatics Abstract algebra Cognition

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A Many-Objective Estimation Distributed Algorithm Applied to Search Based Software Refactoring

A Many-Objective Estimation Distributed Algorithm Applied to...

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Congress on Evolutionary Computation

作者： Glauber Botelho Leonardo Bezerra André Britto Leila Silva Post-Graduate Program on Computer Science Federal University of Sergipe Sergipe Brazil Department of Computing Federal University of Sergipe Sergipe Brazil

Refactoring is a modification in the internal structure of software, in order to improve quality, understandability and maintainability, without changing its observable behavior. Search Based Software Refactoring (SBSR) deals with automatic software refactoring processes using optimization algorithms. In this context, here we investigate the problem of finding a sequence of refactorings that provides code improvement, according to software quality attributes, expressed by a combination of software metrics. There are multiple criteria to define the quality of a solution, therefore this problem is defined as a Many-Objective Combinatorial Optimization Problem. There is a lack of works that focus on Many-Objective Discrete Problems in SBSR. In this direction, this work proposes a Many-Objective Estimation Distributed Algorithm to find a sequence of refactorings on an object-oriented software. The algorithm explores archiving methods and probabilistic models. A set of experiments is performed, with the aim of investigating which is the best algorithm configuration, regarding the probabilistic model and selection procedure.

关键词： Software Optimization Linear programming Software algorithms Object oriented modeling Measurement Probabilistic logic

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Critical success factor measurement model implementation of natural disaster mitigation knowledge management systems

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AIP Conference Proceedings 2020年第1期2245卷

作者： Wahyu Sardjono Harisno Widhilaga Gia Perdana Tri Pujadi Karto Iskandar 1Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management BINA NUSANTARA University Jakarta INDONESIA 11480 2Post Graduate Program School of Environmental Science University of Infonesia Jakarta INDONESIA 3School of Information Systems BINA NUSANTARA University Jakarta INDONESIA 11480 4School of Computer Science BINA NUSANTARA University Jakarta INDONESIA 11480

In Law Number 24 Year 2007 concerning Disaster Management, it is stated that the central government and regional governments are responsible for implementing disaster management, with an emphasis on preparedness and mitigation in dealing with natural disasters, but the socialization of these two matters is not regulated in the law exist, so that the planning and implementation of the socialization and internalization program must be carried out by the community itself. Exposure in this paper aims to provide an overview of how socialization of mitigation in dealing with natural disasters carried out by the use of information systems and technology can be successful with reference to the theory of SECI (Socialization, Externalization, Combination, and Internalization), knowledge development with data formed based on the perspective of the community. Factor analysis method is used to look for the success factors of mitigation socialization in the face of natural disasters. Furthermore, from the new factors that are formed, further analysis is carried out with a regression analysis method to develop a successful model of disaster mitigation socialization *** results of the study provide a number of new factors that can be represented as variables of community awareness of natural disasters, mitigation socialization processes in the face of natural disasters, availability of systems and information technology, and knowledge management governance on natural disaster mitigation. The conclusion obtained from this study is that the momentum of the industrial revolution era 4.0 can be utilized to support the socialization process of natural disaster mitigation independently measured based on the local wisdom of the local community.

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Test case generation from BPMN models for automated testing of Web-based BPM applications 17

Test case generation from BPMN models for automated testing ...

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17th International Conference on Computational science and Its Applications, ICCSA 2017

作者： De Moura, Jéssica Lasch Charão, Andrea Schwertner Lima, João Carlos Damasceno De Oliveira Stein, Benhur Post-Graduate Program in Computer Science Universidade Federal de Santa Maria Santa Maria RS Brazil

ISBN: (纸本)9781538638934

This article proposes an approach to generate test cases from BPMN models, for automated testing of Web applications implemented with the support of BPM suites. The work is primarily focused on functional testing and has the following objectives: (i) identify execution paths from the flow analysis in the BPMN model and (ii) generate the initial code of test scripts to be run on a given Web application testing tool. Throughout the article, we describe the design and implementation of a solution to achieve these goals, targeting automated tests using Selenium and Cucumber as tools. The approach was applied to processes from a public repository and was able to generate test scenarios from different BPMN models. © 2017 IEEE.

关键词： Software testing

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Real-time optimization using gradient adaptive selection and classification from infrared sensors measurement for esterification oleic acid with glycerol

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International Journal of Intelligent Computing and Cybernetics 2017年第2期10卷 130-144页

作者： Iwan Aang Soenandi Taufik Djatna Ani Suryani Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural UniversityBogorIndonesia and Faculty of Engineering and Computer ScienceKrida Wacana Christian UniversityJakartaIndonesia Post Graduate Program of Agro-industrial Technology Bogor Agricultural UniversityBogorIndonesia Department of Physics Faculty of Mathematics and Natural SciencesBogor Agricultural UniversityBogorIndonesia

Purpose-The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process *** accurate monitoring and controlling of the process can improve production yield and *** purpose of this paper is to propose a real-time optimization(RTO)using gradient adaptive selection and classification from infrared sensor measurement to cover various disturbances and uncertainties in the ***/methodology/approach-The integration of the esterification process optimization using self-optimization(SO)was developed with classification process was combined with necessary condition optimum(NCO)as gradient adaptive selection,supported with laboratory scaled medium wavelength infrared(mid-IR)sensors,and measured the proposed optimization system indicator in the batch *** Process Modeling and Notation(BPMN 2.0)was built to describe the tasks of SO workflow in collaboration with NCO as an abstraction for the conceptual ***,Stateflow modeling was deployed to simulate the three states of gradient-based adaptive control combined with support vector machine(SVM)classification and Arduino microcontroller for ***-This new method shows that the real-time optimization responsiveness of control increased product yield up to 13 percent,lower error measurement with percentage error 1.11 percent,reduced the process duration up to 22 minutes,with an effective range of stirrer rotation set between 300 and 400 rpm and final temperature between 200 and 210℃ which was more efficient,as it consumed less *** limitations/implications-In this research the authors just have an experiment for the esterification process using glycerol,but as a development concept of RTO,it would be possible to apply for another chemical reaction or *** implications-This research introduces new development of an RTO approach to optimal con

关键词： Gradient technique Infrared sensor Real-time optimization Simulation and modelling Support vector machine

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Identifying irregularity electricity usage of customer behaviors using logistic regression and linear discriminant analysis 3

Identifying irregularity electricity usage of customer behav...

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3rd International Conference on science in Information Technology, ICSITech 2017

作者： Lawi, Armin Wungo, Supriyadi La Manjang, Salama Department of Computer Science Post-graduate Program of Electrical Engineering Dept. Electrical Engineering Universitas Hasanuddin Makassar Indonesia

ISBN: (纸本)9781509058662

This study aims to implement a machine learning technique in identifying the irregularities of customer behavior on the use of prepaid electricity pulses. The methods used are Linear Discriminant Analysis and Logistic Regression. The performance of the classification system will be evaluated using the 10-fold cross-validation technique. Validation results are measured using accuracy, precision and recall values. In this research shows that the use of machine learning technique has a good performance in classification of electrical consumption behavior. Experimental results with the different amount of data testing indicate that Logistic Regression method has high accuracy, precision, and recall value when compared with Linear Discriminant Analysis that is 100%. This is due to Logistic Regression method can predict irregularities accurately because the addition of the amount of data does not affect the performance of the method. © 2017 IEEE.

关键词： Regression analysis

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Smart sensor based distillation for fractionating citronella oil: current research challenges

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IOP Conference Series: Earth and Environmental science 2020年第1期472卷

作者： D Wahyudi E Noor D Setyaningsih T Djatna Irmansyah Post Graduate Program of Agroindustrial Technology Bogor Agricultural University Bogor Department of Agroindustrial Technology Bogor Agricultural University Bogor Indonesia. Department of Physics Bogor Agricultural University Bogor Indonesia. of Computer Science Faculty of Mathematics and Natural Science IPB University (Bogor Agricultural University) Medan Agricultural Development Polytechnic Medan Indonesia.

Citronella oil is one of the essential oils derived from the leaves and stem of lemongrass (Cymbopogon nardus). At present, most of the lemongrass oil industry in Indonesia is still in the form of upstream industries which only provide crude purified oils with low purity for export with a fairly low sales value. Technology in improving the purity of citronella oil needs innovation in following the development of the industrial revolution 4.0. This article presents an overview of the research opportunities in the development of distillation for fractionating citronella oil referring to automation of optimization processes in the vacuum fractional distillation accompanied by inspection of the quality of essential oil isolation run in the line process based on smart sensors integrated in a computer program. The combination technique of quality control of essential oils in line process system combined with the optimization technique of the vacuum fractional distillation process has not been studied by advanced researchers. Therefore, this study has a state of the art process engineering and smart sensor-based quality control systems that can be developed for strengthening the Indonesian citronella oil industry.

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