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检索条件"机构=Computer Science Postgraduate Program"

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Model Decision Support System for Diagnosis COVID-19 Using Forward Chaining: A Case in Indonesia 8

Model Decision Support System for Diagnosis COVID-19 Using F...

引用

8th International Conference on Cyber and IT Service Management, CITSM 2020

作者： Henderi Maulana, Miftah Warnars, Harco Leslie Hendrie S. Setiyadi, Didik Qurrohman, Taufik University of Raharja Department of Informatics Engineering Tangerang Indonesia Postgraduate of Information Engineering University of Raharja Tangerang Indonesia BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Bina Insani University Department of Informatics Engineering Bekasi Indonesia

ISBN: (纸本)9781728177014

The government in Indonesia and its staff work together to make tactical steps to prevent the spread of COVID-19 in the community. From the ministerial level to the heads of the provinces, regencies, and even the government. Therefore, this study aims to make a model decision support system to diagnose patients exposed to Covid-19, such as people in control, patients in oversight, and those who are positive for the Covid-19 Virus. Model decision support system development aims to provide information about the development of COVID- 19 and help the community in diagnosing themselves related to COVID-19 infection. In this study, the authors use the forward chaining method in application to get conclusions from the symptoms of the Covid-19. This research resulted in an application that patients exposed to the Covid-19, and it's also provided a solution for healing from patients. And this could be a reference for patients before consulting further with the doctor. © 2020 IEEE.

关键词： Decision support systems

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Expert System Application of Forward Chaining and Certainty Factors Method for the Decision of Contraception Tools 2

Expert System Application of Forward Chaining and Certainty ...

引用

2nd International Conference on Energy, Environmental and Information System, ICENIS 2017

作者： Prambudi, Dwi Arief Widodo, Catur Edi Widodo, Aris Puji Magister Program of Information System School of Postgraduate Studies Diponegoro University Semarang50242 Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang50275 Indonesia Department of Computer Science Faculty of Science and Mathematics Diponegoro University Semarang50275 Indonesia

The choice of contraceptive tools is not an easy thing because the risks or effects will give impact on the body that never using it previously. in the other side, there is no contraception always suit for everybody because the circumstances of each body is different, so the extensive knowledge must be needed to know the advantages and disadvantages of each contraceptive tools then adjusted to the user's *** expert system for contraceptive tools uses Forward Chaining search method combined with Certainty Factors Method. These method value the patient's indication. The Expert system gives the output data which define the kind of tool uses of the patient. the results obtained will be able to help people to find indications that lead to appropriate contraceptive tools and advice or suggestions about these tools. The success rate of the contraceptive tools decision experienced by experienced by the user by using forward chaining combined with the CF computation method is also influenced by the number of indication criteria selected by the user. Based on testing that has been done, expert system contraception tools has accuracy level equal to 75%. © 2018 The Authors, published by EDP sciences.

关键词： Expert systems

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Performance comparison of CATA's information retrieval system application vs WTS

Performance comparison of CATA's information retrieval syste...

引用

International Conference on Engineering, Technology and Innovative Researches 2019, ICETIR 2019

作者： Purnama, Jajang Jaya Rahayu, Sri Sfenrianto Nugraha, Fitra Septia Nurfalah, Ridan Nawawi, Hendri Mahmud Shidiq, Muhammad Ja'Far Ichsan, Nurul Fatah, Haerul Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Indonesia Information Systems Bina Sarana Informatika University Indonesia

Searching for data or documents that are always a necessity in the world of education, work, research an others requires convenience so that time efficiency occurs. This is supported by the emergence of various Information Retrieval system applications, one of which is cata, which is built on the Java programming language and applies the Generalized Vector Space Model method which can search based on similar keywords. Other facilities need to be developed, one of which is by applying the stemmer porter algorithm applied to the WTS (Web Tokenization Stemming) web which is built with the laravel framework that can search data or documents simply by typing the basic words so that searches are easier and faster. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Search engines

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Detection of non-conventional events on video scenes

Detection of non-conventional events on video scenes

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Andre G. Hochuli Alceu S. Britto Alessandro L. Koerich Postgraduate Program in Computer Science Pontifical Catholic University of Paraná Curitiba Parana Brazil

This article presents a novel approach for detection of non-conventional events in videos scenes. This novel approach consists in analyzing in real-time video from a security camera to detect, segment and tracking objects in movement to further classify its movement as conventional or non-conventional. From each tracked object in the scene features such as position, speed, changes in directions and in the bounding box sizes are extracted. These features make up a feature vector. At the classification step, feature vectors generated from objects in movement in the scene are matched almost in real-time against reference feature vectors previously labeled which are stored in a database and an algorithm based on the instance-based learning paradigm is used to classify the object movement as conventional or non-conventional. Experimental results on video clips from two databases (Parking Lot and CAVIAR) have shown that the proposed approach is able to detect non-conventional events with accuracies between 77% and 82%.

关键词： Event detection Layout Hidden Markov models Feature extraction Cameras Histograms Security Object detection Tracking Spatial databases

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Accuracy for Sentiment Analysis of Twitter Students on ELearning in Indonesia using Naive Bayes Algorithm Based on Particle Swarm Optimization 1

Accuracy for Sentiment Analysis of Twitter Students on ELear...

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1st International Conference on computer, science, Engineering and Technology, ICComSET 2018

作者： Kartiko, Mohamad Sfenrianto Master of Computer Science Postgraduate Programs STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Universitas Bina Nusantara Jakarta Indonesia

Students can use social media such as Twitter for online learning (E-Learning). This study aims to analyse an accuracy for the sentiments of students about E-Learning who use Indonesian on Twitter social media both positive and negative opinions. The algorithms used are Naive Bayes (NB). Then to optimize the accuracy of the calculation results, the Particle Swarm Optimization (NB-PSO) approach is used. In order to optimize accurate results, this study uses three experimental sequences (scenario 1, scenario 2, and scenario 2) for both NB and NB-PSO algorithms. Each scenario uses different positive and negative comments. The results of the experiment show that in scenario 1 an increase in accuracy is 10.00% for NB-PSO. Scenario 2 there is an increase in accuracy of 13.33% on NB-PSO. Meanwhile, in scenario 3 an increase in accuracy is 27.22% for NB-PSO. These results prove that the accuracy of NB-PSO is better than NB for all scenarios. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Students

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7th International Conference of computer and Informatics Engineering, IC2IE 2024

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798331505530

Full-marathon and Half-marathon distances are categorized as road running. Full-marathon running is becoming increasingly popular, and Half-marathon is increasing worldwide in both sexes and all age groups. Some aspects might relate to Full-marathon and Half-marathon running performance during training and races. Technology also plays an essential role in supporting runners and running races. Technology like artificial intelligence (AI) now supports the running athlete, not only predicting performance and results. It can also be used later to help the coach generate training programs for the athlete. This research aimed to find many aspects of marathons and performance and analyze them to see if artificial intelligence could later support them. It used secondary data and a systematic literature review proposed by Kitchenham. Out of the 58 articles, 21 of them (36.21%) received a score of 1 from Q1. Additionally, 19 articles (32.76%) received a score of 1 from both Q2 and Q3. Among the 58 articles, 9 (15.52%) received a total score of 3, with all three Q1, Q2, and Q3 scores being 1. This indicates that artificial intelligence will likely support the content of these nine articles. Several factors were also discovered to be connected to marathons and athletic performance. These findings suggested that additional investigation into marathons and performance, later backed by artificial intelligence, remained pertinent and essential. © 2024 IEEE.

关键词： artificial intelligence aspects marathon performance

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The influence of human capabilities in effort estimation of business processes modeling projects

The influence of human capabilities in effort estimation of ...

引用

5th International Conference on Research and Practical Issues of Enterprise Information Systems, CONFENIS 2011

作者： Dutra, José Roberto De Barros, Márcio O. Santoro, Flávia Maria Magdaleno, Andréa M. Cappelli, Claudia Nunes, Vanessa Klussman, Felipe Postgraduate Information Systems Program UNIRIO Brazil NP2Tec Research and Practice Group in Information Technology UNIRIO Rio de Janeiro RJ Brazil COPPE UFRJ Systems Engineering and Computer Science Program Rio de Janeiro RJ Brazil

ISBN: (纸本)9780415631310

Business processes modeling projects are increasingly widespread in organizations, which usually invest much in hiring expert consultants to do such job. These consultants come from various organizations, and have different experiences on how to perform the same activity. This paper analyzes how human-related capabilities influence the effort required to conduct a business process modeling project and discusses the results obtained from about 50 projects executed in a large Brazilian company. © 2012 Taylor & Francis Group, London.

关键词： Systems engineering

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Air Particulate Matters Auto-Rule-Based Labeling to Support Long-Distance Run Environment Data Classification 13

Air Particulate Matters Auto-Rule-Based Labeling to Support ...

引用

13th IEEE Symposium on computer Applications and Industrial Electronics, ISCAIE 2023

ISBN: (纸本)9798350347319

Sports science is an interdisciplinary and multidisciplinary science that strives to increase athletic performance and endurance. Sport science recognizes and prevents injuries. Sensors and statistics formalize Sports science. Runners need coaches and teams to support them before, during, and after the run race. Coaches generate running training plans to boost performance. Running race performances may be impacted by air pollution exposure while training, so coaches should consider limiting air pollution exposure when training. One of the external factors is Particulate Matter (PM2.5 and PM10). Sensors connecting to the Internet can record external factors and produce csv data. The foundation of supervised machine learning is the labeling process. Labeling a set of data is one of the laborious and time-consuming phases in every machine-learning application because it requires verifying the accuracy of the labels and making any necessary revisions. This research aimed to find a solution to automatically label numerous air particulate matter raw data using a rule based on parameters to reduce manual work, human errors and faster processes. This labeled data will later be used for supervised machine learning classification to support the coach in generating training programs for the runners in a Sports Information System. Based on Indonesia Air Quality index rule-based approach, labeled text data in csv has been generated and tested with PM2.5 and PM10 parameters in three scenarios with a 100% success rate. It was possible to automate the labeling process, and it explained how automation results in fast and accurate results. © 2023 IEEE.

关键词： Classification (of information)

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A Monsoon Onset and Offset Prediction Model Using Backpropagation and Moron Method: A Case in Drought Region

A Monsoon Onset and Offset Prediction Model Using Backpropag...

引用

International Conference on Advanced computer science and Information Systems

作者： Syeiva Nurul Desylvia Taufik Djatna Agus Buono Department of Computer Science Bogor Agricultural University Bogor Indonesia Postgraduate Program of Agroindustrial Technology and Graduate Program of Computer Science Bogor Agricultural University Bogor Indonesia

ISBN: (纸本)9781509003648

First day (onset) and last day (offset) of monsoon are nature phenomena which are important elements at cultivation stages in agriculture. These 2 sets of time value influent harvest performance but it is difficult to predict onset and offset at drought region. One of technique that can be used to solve mentioned problem is prediction technique which is one of data mining task. In this research, Feed Forward Backpropagation (BPNN) were combined with Moron method to predict onset and offset at drought region. Data used were daily rainfall data from 1983 to 2013. This experiment used 2 kind of BPNN models and they used 5 different values for learning rate (alpha) from range 0.01 to 0.2. Root Mean Square Error (RMSE) is used to evaluate resulted prediction models along with correlation value and standard deviation of error for better understanding. For BPNN onset model, lowest RMSE value at alpha 0.15 is 32,0546 and lowest RMSE value for BPNN offset is 26,6977 at alpha 0.05. Developed model has been able to use for prediction, but the result was still not close enough to actual data. In order to achieve a better model with lower RMSE, it is neccesary to improve model architecture and to specify some methods to obtain certain number of input layer based on Southern Oscillation Index (SOI) data.

关键词： Rainfall Backpropagation Prediction Moron method

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The importance of mobile applications for companies' brand image: A study using structural equations 9th

The importance of mobile applications for companies' brand i...

引用

9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Mariano, Ari Melo Silva, Marcel Carneiro Mello, Tarcilla Mariano Santos, Maíra Rocha Department of Production Engineering University of Brasília Brazil Department of Computer Science University of Brasilia Brazil Postgraduate Program in Communication University of Brasília Brazil Center for Advanced Multidisciplinary Studies University of Brasilia Brazil

Because of the advancement of new technologies and the popularity of mobile devices, this study was designed to identify whether apps have a representative influence on companies' brand image. To fulfill this objective, descriptive research based on the structural equation model was carried out with the help of the statistical software Adanco. The study was conducted in Brasilia and applied in a virtual environment in the Google forms platform. The link was made available and disseminated to students of one university and through the WhatsApp and Facebook social networks, having 350 mobile device users as participants. The questionnaire was validated with α=0.81. The results of this research suggest that applications can influence 30.5% of a brand's image, thus raising the discussion that mobile applications will soon have equal or even greater importance than a website and social networks, tools that were once trends and are now essential requirements for organizations. Thus, for a company to be successful, it must not only be seen as a company with high performance and quality standards, but it must also represent a solid brand with a good reputation in the market and create and cultivate an image that connects emotionally with its consumer public. © 2022 The Authors. Published by Elsevier B.V.

关键词： Social networking (online)

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