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检索条件"丛书名=Information Systems Engineering and Management"

共 176 条记录，以下是81-90 订阅

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Comparison of the Use of Bigrams and Stopword Removal for Classification Using Naive Bayes (Case Study on Sentiment Analysis of By.U Internet Users) 7

Comparison of the Use of Bigrams and Stopword Removal for Cl...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Hidayat, Manaarul Hidayat, Rahmat Otik Kurniawati, Dwi Uin Sunan Kalijaga Yogyakarta Department of Informatics Indonesia

ISBN: (纸本)9781665414074

With the rapid growth of the number of youth, several providers have launched digital service provider innovations. By.U as a pioneer has been serving this segment for the past year, and its presence has received various responses from netizens. This response, if researched, can improve services and lead to other innovations. However, no research addresses this. Therefore, a final project was written regarding Sentiment Analysis on the provider by.U. In this reearch, a classification model was made with 3804 data using Naive Bayes Classifier and TF-IDF with Bi-Grams. The comparison was made by eliminating one of the preprocessing steps: stopword removal. The comparison found that TF-IDF and Bi-Grams without the application of stopword removal had the best performance values. The best performance value is obtained in the split validation scenario 90:10 with accuracy 86.88%, Precision 88.24%, recall 83.33%, and f1-score 85.71%. © 2021 IEEE.

关键词： Sentiment analysis

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Accuracy and performance analysis for classification algorithms based on biomedical datasets 7

Accuracy and performance analysis for classification algorit...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Al-Hameli, Bassam Abdo Alsewari, AbdulRahman A. Khubrani, Mousa Fakhreldin, Mohammoud Universiti Malaysia Pahang Faculty of Computing Pahang Pekan26600 Malaysia Universiti Malaysia Pahang Centre for Software Development and Integrated Computing Faculty of Computing Pahang Pekan26600 Malaysia Jazan University Computer Science and Information Technology Jazan Saudi Arabia

ISBN: (纸本)9781665414074

Diseases chronic, including heart disease, cancer, diabetes, and obesity, are the main causes of mortality in the United States and accounting for and consuming the majority of the country's healthcare expenditure. As indicated by recent researches. The main reason for the emergence of these diseases prominently is their relationship to each other, where diabetes is one of the causes of cancer and heart disease, hepatitis also is associated with diabetes, and heart disease. This paper focuses on data mining and machine learning techniques in healthcare classification and prediction of diseases and rebuild disease detection systems (DDS). The study suggests finding a classifier among the most common kinds of classification algorithms within a combined approach represent in Bayesian, Trees, Rules, Function, and lazy algorithms to automate a better performance of early detection of diseases from the medical datasets. This paper presents and analyzes five different machine learning (ML) algorithms: Function-based Neural Network (MLP) algorithm. Trees based Decision Tree (ID3) algorithm, Bayesian Theorem based Hidden Naïve Bayes (HNB) algorithm. Lazy based k-nearest neighbors (IBK) algorithm, and Rules-based OneR algorithm. The analysis is based on four benchmark datasets in the healthcare sector, including the Pima Indian Diabetes PID, the Breast Cancer, Heart Cleveland, and Hepatitis Datasets, which were obtained from several ML repositories. The results show that the HNB predicts the best result with a relatively higher Precision, AUROC Statistic, highest accuracy, and performance when compared to MLP, IBK, OneR, ID3 algorithms. © 2021 IEEE.

关键词： Diseases

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Video Transmission in IEEE 802.15.4 Wireless Sensor Network Using Asynchronous TDMA 7

Video Transmission in IEEE 802.15.4 Wireless Sensor Network ...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Ismail, Nor-Syahidatul N Abdullah Asuhaimi, Fauzun Ariffin, Sharifah. H.S. Binti Yunus, Farizah Pahang Malaysia Pahang Malaysia Johor Bahru Malaysia Terengganu Malaysia

ISBN: (纸本)9781665414074

Nowadays, the Wireless Sensor Network (WSN) technology is extensively used in a large variety of applications. WSN has engaged humans and computers in many applications such as health monitoring and security. IEEE 802.15.4 wireless standard is the current demand on WSN which is used to transmit video or real-time data at low data rates. Reliable data transmission for video applications is a critical issue in low data rate transmissions due to the high collision from conventional protocol, which is Carrier Sense Multiple Access (CSMA). Therefore, a MAC layer with token approach protocol called MAC-TA protocol is proposed to solve this issue. In this protocol, the only node that holds the token can transmit the data. If other nodes intent to do the transmission, they have to wait for the token before sending the data. Token Holding Time (THT) is a duration time set at the node that holds the token, and the token is pass to the next node when the THT is finished. This paper is focusing on the development of the MAC-TA protocol onto test-bed TelG motes. Three types of MPEG-4 video samples have been tested which are Akiyo, Foreman, and Mobile both in Quarter Common Intermediate Format (QCIF) and Common Intermediate Format (CIF) format. The proposed protocol is compared with the existing CSMA protocol in IEEE 802.15.4 standard. The experimental results present that the MAC-TA protocol has improved the packet delivery ratio by 70%. Moreover, the results prove that MAC-TA provides good reliability of multimedia data and makes it possible to send over IEEE 802.15.4 environment. © 2021 IEEE.

关键词： Time division multiple access

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Serious Games and Preventive Self-Care for Diabetes: A Conceptual Framework 7

Serious Games and Preventive Self-Care for Diabetes: A Conce...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Ihsan, Siti Normaziah Kadir, Tuty Asmawaty Abd Abdullah, Abdul Rafiq Universiti Malaysia Pahang Faculty of Computing College of Computing and Applied Science Pekan Pahang26600 Malaysia

ISBN: (纸本)9781665414074

The types of diseases that diabetes causes include cardiovascular disease, renal disease, visual impairment, peripheral arterial disease, peripheral neuropathy, and cognitive impairment. According to WHO statistics, there are 422 million adults with diabetes. Diabetes and high blood glucose contribute to 3.7 million deaths, while diabetes causes 1.5 million deaths. Diabetes risk factors include genetics, age, family history, and behaviours such as unhealthy diets and physical inactivity. Reducing early behavioural risk factors, such as educating people about appropriate dietary habits for diabetics, is also possible. To overcome this challenge, a unique approach to education is needed, and maintaining a healthy diet is essential. Main objective of this research is to propose a conceptual framework for serious games to educate on awareness in healthcare. The prototypes games namely as Grab2BeHealthy has been developed as a teaching tool, as well as a prevention tool, using the proposed framework to proof the concept. This game will educate player about the types of foods that lead to diabetes. Players must get a healthy food with a game and diabetes-related facts. To test and learn about a game engine, 50 people of different genders and ages from diverse backgrounds took part in an evaluation study. Thus, in this study, we mapped the characteristics of the prototype games with the framework for increasing healthy food understanding in order to decrease the occurrence of diabetes. © 2021 IEEE.

关键词： Serious games

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Antecedents the use of Social Commerce in Small Medium Enterprise: A Conceptual Framework 7

Antecedents the use of Social Commerce in Small Medium Enter...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Sutomo, Erwin Abdul Rahman, Nur Shamsiah Binti Binti Romli, Awanis University Malaysia Pahang Faculty of Computing Malaysia

ISBN: (纸本)9781665414074

SMEs need to pay attention to several factors so that customers and SMEs can continue to use S-Commerce. The obstacle faced by SMEs is that they cannot consistently use S-Commerce. This study aims to produce a proposed conceptual framework to see the relationship between factors for using S-Commerce in SMEs. The proposed framework has developed through the literature related to using social commerce in SMEs, including the relationship between determinant factors using S-Commerce in SMEs. The reviews are viewing from technological, organizational, social factors, including customer and competitor factors. The results of this study indicate that 11 factors determine the use of S-Commerce in SMEs. The social connectedness and trust factors are some of the determining factors in using S-Commerce. The resulting proposed conceptual framework contributes to a better understanding of the considerations for using S-Commerce in SMEs, especially for SME business owners. © 2021 IEEE.

关键词： Commerce

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The Impact of Exponent Variable on the Performance and Effectiveness of FCM Algorithm for Ontology Construction in Structured Knowledge management 7

The Impact of Exponent Variable on the Performance and Effec...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Mahmood, Khalid Rahmah, M. Fauziah, Z. Azhar, A. Nor Noraziah, A. Norshita, M.N. Universiti Malaysia Pahang Faculty of Computing College of Computing and Applied Sciences Pahang Pekan26600 Malaysia Universiti Kebangsaan Malaysia Institute Ip 4.0 Malaysia

ISBN: (纸本)9781665414074

Data Clustering is an effective mechanism for the clustering of similar data objects. Fuzzy logic based or soft data clustering technique is very suitable for the formation of data clusters semantically when a data object is the member of more than one clusters unlike hard data clustering techniques. Fuzzy exponent variable is one of the most important variable in fuzzy logic based clustering technique. This variable has significant impact on the performance and effectiveness of the clustering results. An experimental evaluation is performed to analyze the impact of fuzzy exponent variable in this study. The experiments are performed on textual web document dataset through Fuzzy C-Means soft clustering technique. The results retrieved with various values of fuzzy exponent variable, are analyzed and presented to represent the performance and effectiveness. © 2021 IEEE.

关键词： Fuzzy logic

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COVID-19 Analysis and Predictions Evaluation for KSA Using Machine Learning 7

COVID-19 Analysis and Predictions Evaluation for KSA Using M...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Elarabi, Rawia Alqahtani, Fatimah Balobaid, Awatef Zain, Halah Babiker, Najla Jazan University Computer Science Department Jazan Saudi Arabia Jazan University Information Technology Department Jazan Saudi Arabia

ISBN: (纸本)9781665414074

The unprecedented rise in the number of new coronavirus infections worldwide has prompted many researchers to use mathematical and machine-learning-based prediction models to predict future epidemic patterns that will help governments, health service providers, and society understand how to deal with this situation. Using different machine learning methodologies helps researchers to understand the trend curve clearly. These may lead to a better and more effective fight against the epidemic and reduce or end preventive measures, allowing people to return to their everyday lives. This study is based on an analysis of COVID-19 data of KSA. Also, it demonstrates the prediction of the new confirmed cases and death of COVID-19 in the next ten days from 8th July in KSA, which is considered the period of the performing Hajj in 2021. It uses machine learning models such as Support Vector Machine (SVM), Bayesian Edge (BR), Linear Regression (LR), and Moving Average (MA). Each model provides two types of predictions: the number of newly infected cases and deaths over the next 10 days. The results indicate that SVM and MA forecasts have high accuracy, followed by LR which performs well. The BR performs poorly in forecast scenarios when applied with the available data set in forecasting new confirmed cases. All models were accurate in predicting mortality, with the best performing model being SVM, followed by MA, LR, and BR. It also expects an increase in confirmed cases under the SVM model scenario to 511, 257 on 17th July from 496, 516 on 7th July in the actual daily cumulative cases. The number of deaths will rise to 8, 113 on 17th July from 7, 921 on 7th July in actual cumulative daily data. © 2021 IEEE.

关键词： Coronavirus

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C Programming Skill Levels Determination Using Fuzzy Logic 7

C Programming Skill Levels Determination Using Fuzzy Logic

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Aiman Al-Falah Muhd Yazid, Muhammad Azida Sahabudin, Noor Farihan Mat Raffei, Anis Akmal Remli, Muhammad Universiti Malaysia Pahang Faculty of Computing Pahang Pekan Malaysia Universiti Malaysia Kelantan Department of Data Science Kota Bahru Kelantan Malaysia

ISBN: (纸本)9781665414074

Programming language is known among computer science students. One should know at least one programming language throughout their studies. However, mastering one programming language is challenging. Most of the new student find challenging to learn and understand the language as they are not familiar with it. This can cause a problem throughout their studies or even in future jobs. Thus, implementing artificial intelligence to identify students' understandability level towards programming skills is expected to improve their knowledge and weakness about that programming language. This paper presents proposed work for designing the level of programming knowledge for new computer science student. The level of programming knowledge is identified and analyzed based on the student input. The fuzzy logic approach is employed in this study to obtain the target result based on several criterion. Several tools are used to develop the platform for collecting user input data. The output of this work shows that the student can identify their element on each spoke and the programming language level with a short description by displaying data visualization as the output to user in the radar chart. © 2021 IEEE.

关键词： Membership functions

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A Conceptual Review on Integration of Cognitive Load Theory and Human-Computer Interaction 7

A Conceptual Review on Integration of Cognitive Load Theory ...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Banu, R. Al Siyabi, Wedad Salim All Al Minje, Yusra Muscat College Department of Business and Accounting Muscat Oman Muscat College Language Center Muscat Oman

ISBN: (纸本)9781665414074

During the era of technological advancement and usage of the e-learning environment, it is vital to examine the integration between the human-computer interaction (HCI) and the theory of cognitive load. A systematic review of the literature was conducted by searching studies associated with cognitive load theory and human-computer interaction concepts. Around 47 published papers were reviewed, and the analyses indicated that the cognitive load theory (CLT) is explicit in the context of HCI since the idea of relevant intellectual burden can be clarified and it minimizes the disadvantage of externalizing data on the interface and also supports to diminish memory load. Henceforth, it can be implied that cognitive load theory and human-computer integration approaches and ideas, enable users to learn the device based on the informative program and/or frameworks. Based on a review of the literature, a conceptual framework is proposed, which can be empirically tested in future studies. The researchers suggested that with the increase in an e-learning environment, there is a need for the study to understand and examine the integration between the HCI and CLT aspects, this will support the system developers to provide appropriate guidelines based on the user and task. © 2021 IEEE.

关键词： Human computer interaction

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A Proposed Requirements Prioritization Model Based on Cost-Value Approach with Collaboration Perspective 7

A Proposed Requirements Prioritization Model Based on Cost-V...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Amelia, Tan Mohamed, Rozlina Binti Universiti Malaysia Pahang Faculty of Computing Pahang Malaysia Department of Information System Universitas Dinamika Surabaya Indonesia

ISBN: (纸本)9781665414074

Criteria analysis in requirement prioritization should always be transparent and holistic to increase the stakeholder's satisfaction. Different stakeholders have their views on the same criteria, making it challenging to agree on a specific set of criterion weights. In software development, collaboration between client and developer is needed for requirements to be achieved. The cost-value approach to determining priority requirements requires a client perspective to determine the value and developer's concept to ascertain costs, then form a cost-value diagram for analysis. Therefore, the research conducted has not been detailed using a cost-value approach involving a client perspective and a developer concept. Usually, the criteria and alternatives weighted by the decision-maker are vague, uncertain, and subjective. Furthermore, using fuzzy numbers help solve different types of uncertainty and conflicting requirements to produce reliable work. This study proposes increasing the weighting of criteria in the requirements prioritization technique, based on cost-value, by doing a collaboration perspective through Fuzzy AHP and TOPSIS using linguistic terms by presenting a proposed model. © 2021 IEEE.

关键词： Linguistics

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