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Information technology (ACIT)

作者： Bambang Dwi Wijanarko Bachtiar Rosilah Binti Hassan Dina Fitria Murad Ridho Bramulya Ihsan Yaya Heryadi Engkos Achmad Kuncoro Eka Julianti Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Master of English Education Graduate School Universitas Terbuka Jakarta Indonesia Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor Malaysia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Manajemen Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Information System Department Universitas Terbuka Jakarta Indonesia

This research is ongoing research into the student learning process which aims to develop artificial intelligence-based technology to calculate essay exam scores automatically, based on the textual proximity of students' answers to the answer key. This research uses an approach based on natural language processing (NLP) and text analysis. Feature extraction was carried out using the BERT model and similarity comparison using the Cosine distance method. Model evaluation was carried out using sensitivity and specificity tests. The model evaluation results show a sensitivity of 98.21%, which means this assessment model is able to detect positive cases well.

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Manual Test Metrics in Genetic Algorithm 3

Manual Test Metrics in Genetic Algorithm

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3rd International Conference on Computing and Applied Informatics 2018, ICCAI 2018

作者： Bahar, Emirul Nasution, Sawaluddin Dewi, Agushinta R. Wahyuni, Rossi S. Industrial Engineering Faculty of Industrial Technology Gunadarma University Indonesia Department of Mathematics Universitas Sumatera Utara Indonesia Information System Faculty of Computer Science and Information Technology Gunadarma University Indonesia

Software testing is a significant activity of the Software Development Life Cycle (SDLC) that can overcome possibility of error in every single development step. Software testing is most often used technique for verifying and validating the quality of software. Software testing that concern with the internal mechanism of a systems and mainly focus on control flow or data flow a program is called White box testing. White box testing is classified into static and structural testing. Type of white box testing that is used in this paper is structural testing. Path coverage and code complexity is a sub testing within the scope of structural testing. Path coverage split a program into a number of distinct paths. In this paper, structural graph and data flow graph is used to ease the tester to find path in a program by mapping out the program and software testing metrics is used to describe the effectiveness and quality of that processes that produce the software product. This paper did manual testing for genetic algorithm program, such as mapping the genetic algorithm program into the control flow graph, create test cases to provide some possibility inputs that can be handled by program, execute test cases, analyze, and calculate the software manual test process metrics. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Software testing

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Correction: Explainable lung cancer classification with ensemble transfer learning of VGG16, Resnet50 and InceptionV3 using grad-cam

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BMC medical imaging 2024年第1期24卷 195页

作者： Yogesh Kumaran S J Jospin Jeya Mahesh T R Surbhi Bhatia Khan Saeed Alzahrani Mohammed Alojail Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru 562112 India. Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India. Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru 562112 India. trmahesh.1978@***. School of science engineering and environment University of Salford Manchester UK. Management Information System Department College of Business Administration King Saud University Riyadh Saudi Arabia.

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Document Classification using Naïve Bayes for Indonesian Translation of the Quran 7

Document Classification using Naïve Bayes for Indonesian Tr...

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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Putra, Syopiansyah Jaya Sugiarti, Yuni Dimas, Galuh Nur Gunawan, Muhamad Sutabri, Tata Suryatno, Agung Syarif Hidayatullah State Islamic University Information System Department Faculty of Science and Technology Indonesia Faculty of Information Technology University of Respati Indonesia Indonesia Faculty of Computer University of MH. Thamrin Jakarta Indonesia

ISBN: (纸本)9781728129099

Classification for Indonesian language documents was increased. But the application of classification for question and answer system needs is still few. The purpose of this paper is to maximize the classification of Indonesian documents especially the Qur'an translation to support the question and answer system. In the process of creating a question and answer system that is still ongoing, testing the Naïve Bayes algorithm becomes very important besides other algorithms. The Naïve Bayes method is the first choice in this test as it has practicality in calculating. The result of this study is the classification of ITQ documents with 4 categories: Morality, faith, knowledge, and Muamalah. The average accuracy rate of 90.5% indicates that the Naïve Bayes method is still relevant for use. © 2019 IEEE.

关键词： Text processing

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Development of heterogeneous database synchronization algorithm based on entity relationship model approach

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AIP Conference Proceedings 2023年第1期2484卷

作者： Ayu Helinda Zuhar Musliyana Teuku Yuliar Arif Zalfie Ardian Zuriana Abu Bakar Zulaida Rahmi Mutiawati 1Informatic Engineering Department Faculty of Computer Science Ubudiyah Indonesia University Indonesia 2Information System Department Faculty of Computer Science Ubudiyah Indonesia University Indonesia 3Electrical and Computer Engineering Department Faculty of Engineering Syiah Kuala University Indonesia 4Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia 5Faculty of Education Science Ubudiyah Indonesia University Indonesia

Nowadays, database technology keeps evolving and available on various platforms. However, the use of heterogeneous database had a limitation because each database only provides a synchronization method for similar types of databases. Therefore, the utilization of various types of databases becoming a problem since the entire data among the databases need to be integrated. Previous research had examined heterogeneous database synchronization algorithms on mobile devices using message digest. Nevertheless, this algorithm requires a longer synchronization time because necessity to check the hash value of each data record. Thus, this study investigates the development of a multi-platform database synchronization algorithm using the Entity Relationship (ER) model. This model is based on the data relationships in each table. ER model implementation is executed by creating a temporary table that stores the primary key of each data record in a table that has changed or consist new data. The synchronization process flow is determined based on the type of transaction by selecting data from the source table based on the relationship from the temporary table data to the destination database. The results of this study indicates that the proposed ER model could be a new method in the heterogeneous database synchronization process and is able to shorten the synchronization process time.

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Narrowband-internet of things (NB-IoT) system for elderly healthcare services 5

Narrowband-internet of things (NB-IoT) system for elderly he...

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5th International Conference on Engineering, Applied Sciences and technology, ICEAST 2019

作者： Manatarinat, Wiraphon Poomrittigul, Suvit Tantatsanawong, Panjai Electrical Engineering Department Faculty of Engineering Pathumwan Institute of Technology Bangkok Thailand Software Engineering and Information System Department Faculty of Science and Technology Pathumwan Institute of Technology Bangkok Thailand Computer Technology Department Faculty of Science Silpakorn University Bangkok Thailand

ISBN: (纸本)9781728100678

3G and 4G wireless communication technology, which requires broad network resources and large amounts of available electricity, was designed for high-speed Internet usage. Most narrowband-Internet of Things (NB-IoT) devices do not require high-speed Internet because most IoTs work by sending commands to and receiving commands from a server only. NB-IoT is a low-power wide area (LPWA) technology that was developed to accommodate a broad variety of new IoT devices. A low-power wide area network (LPWAN) uses narrow frequencies that support the use of devices in the 900 MHz frequency range that are inexpensive and that can be used in both buildings and wide areas. NB-IoT devices can also be used to assist medical patients, the elderly, and disabled people that are susceptible to falling. Our newly developed monitoring system has the ability to immediately recognize a fall, and then automatically alert up to 4 contacts via the LINE application. If dispatch of a medical unit is required, the patient's location is automatically available without the need for voice contact by the patient. © 2019 IEEE.

关键词： Internet of things

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Notes on the Architecture, League Training and PFSP in AlphaStar

Notes on the Architecture, League Training and PFSP in Alpha...

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International Conference on Intelligent system and Knowledge Engineering, ISKE

作者： Jianyang Zhao Ningning Zhou Long Hong Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huaian China Research Center for logic and Intelligent Computation National-Local Joint Engineering Lab of System Credibility Automatic Verification Huaian China Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781665405546

AlphaStar, a multi-agent intelligence program, is a new member of Alpha’s gamer software. Rated at Grandmaster level in the empirical evaluation shows that AlphaStar has been a great success in engineering, which is another milestone in AI history. After a brief introduction to AlphaStar, we discussed its computational architecture, league training, PFSP, and proposed an interesting topic direction on the basis of our suggestions, which was how to combine the capacities of diverse ANNs that successful completed learning. Additionally, we proposed the viewpoint that is big data— space, intelligence— man’ world, parallel computing—time.

关键词： Training Knowledge engineering computer architecture Software History Intelligent systems

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Modeling of rainfall time series using NAR and ARIMA model over western Himalaya, India

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Arabian Journal of Geosciences 2022年第23期15卷 1-26页

作者： Rawat, Deepa Mishra, Pradeep Ray, Soumik Warnakulasooriya, Himasha Harshani Fernando Sati, Sarswati Prakash Mishra, Gaurav Alkattan, Hussein Abotaleb, Mostafa College of Forestry VCSG Uttarakhand University of Horticulture and Forestry Tehri Garhwal India College of Agriculture Rewa India Centurion University of Technology and Management Paralakhemundi India Department of Statistics & Computer Science Faculty of Science University of Kelaniya Kelaniya Sri Lanka Centre of Excellence on Sustainable Land Management Indian Council of Forestry Research and Education (MoEF & CC Govt. of India) Dehradun India Department of System Programming South Ural State University Chelyabinsk Russia

The high Himalayas in northern India are an essential source of climate generation and maintenance over the entire northern belt of the Indian subcontinent. It also affects extreme weather phenomena such as western disturbances in the region during winter. The work presented here describes the trends in 117-year precipitation changes and their impact on the western Himalayas and suggests some possible explanations in the context of changing rainfall patterns. Under the investigation, the forecasting efficiency and the prediction pattern of artificial neural network (ANN) and seasonal autoregressive integrated moving average (SARIMA) models for rainfall series in the western Himalayan states of India have been assessed. The results revealed significant changes in the monthly, seasonal, and annual rainfall series data for the three states of the Western Himalayan regions from the years 1900 to 2017. The study also concludes that the nonlinear autoregressive neural network (NARNN) models can be used to forecast the western Himalayan region data series well. According to the result interpretation, the highest rainfall may be estimated in August, 1632.63 mm (2023), whereas the lowest rainfall can be obtained in October (0.43 mm) during 2023. The model predicted a gradual decrease in annual rainfall trends in Uttarakhand and Himachal Pradesh from 2018 to 2023 despite heavy rainfall prediction in the monsoon season, whereas Jammu and Kashmir increase in annual rainfall has been predicted from 2018 to 2023. Possible explanations for the change in precipitation over the western Himalayas have also been proposed and explained.

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Unified resilience model using deep learning for assessing power system performance

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Heliyon 2025年第4期11卷 e42802页

作者： Artemchuk, Volodymyr Garbuz, Iurii Jamil Alsayaydeh, Jamil Abedalrahim Shkarupylo, Vadym Oliinyk, Andrii Bin Yusof, Mohd Faizal Herawan, Safarudin Gazali Department of Mathematical and Econometric Modelling G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine Kyiv Ukraine Department of Environmental Protection Technologies and Radiation Safety Center for Information-analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine Kyiv Ukraine Department of Іnformation Systems in Economics Kyiv National Economic University Named After Vadym Hetman Kyiv Ukraine Department of Computerized Control System National Aviation University Kyiv Ukraine Department of Engineering Technology Fakulti Teknologi Dan Kejuruteraan Elektronik Dan Komputer (FTKEK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka 76100 Malaysia Department of Computer Systems Networks and Cybersecurity of the National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Tools Faculty of Computer Science and Technology Zaporizhzhia Polytechnic National University Zaporizhzhia Ukraine Research Section Faculty of Resilience Rabdan Academy Abu Dhabi United Arab Emirates Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta 11480 Indonesia

Energy resilience in renewable energy sources dissemination components such as batteries and inverters is crucial for achieving high operational fidelity. Resilience factors play a vital role in determining the performance of power systems, regardless of their operating environment and interruptions. This article introduces a Unified Resilience Model (URM) using Deep Learning (DL) to enhance power system performance. The proposed model analyzes environmental factors impacting the resilience of batteries and energy storage devices. This deep learning approach trains performance-impacting factors using previously known low resilience drain data. The learning output is utilized to augment various strengthening factors, thereby improving resilience. Drain mitigation and performance improvements are combined for direct impact verification. This process validates the model's fidelity in enhancing power system performance, with a specific focus on the impact of weather factors. © 2025 The Authors

关键词： Deep learning Energy resilience Fidelity Weather impact

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Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar

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Smart Health 2024年 34卷

作者： Chokphukhiao, Chaturapron Pattaranit, Pattrawan Tun, Wonn Shweyi Thet Masa, Sakaowrat Leemananil, Rattikorn Natteerapong, Nuttaphorn Phetcharaburanin, Jutarop Boonlue, Sophon Sunat, Khamron Patramanon, Rina Information Technology International Program College of Computing Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Digital Innovation Faculty of Education Khon Kaen University Khon Kaen 40002 Thailand Integrative Biomedical Informatics and Computational Imaging Center I-BIC Faculty of Associated Medical Science Khon Kaen University Khon Kaen 40002 Thailand Department of System Biosciences and Computational Medicine Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Khon Kaen University National Phenome Institute Khon Kaen University Khon Kaen 40002 Thailand Department of Biochemistry Faculty of Science. Khon Kaen University Khon Kaen 40002 Thailand Department of Microbiology Faculty of Science Khon Kaen University Khon Kaen 40002 Thailand Department of Computer Science College of Computing Khon Kaen University 40002 Thailand

Introduction: The use of modern technologies has become crucial for enhancing people's awareness of health problems. By early health risk detection, there will be better treatment outcomes, the severity of illness will decrease, and costs for treatment will also reduce. Performing routine checkups could help patients feel less anxious about their health in the future. In this study, the innovation of “Digital Health Avatar” enables users to monitor physical changes, raise awareness of medical conditions, and encourage healthy behaviors by visualizing health status as a 3D figure. Methods: Health data were collected using medical devices like blood test strips, body composition meters, and automatic blood pressure monitors. API technology and cloud computing systems were used to process these collected data and produced a three-dimensional avatar that indicated the user's health status. User satisfaction survey on using the health avatar system was assessed through a survey of 61 participants. Results: Health avatar system successfully generate the data and display the measurement results on the health report page of the system. Users can easily check and record their physiological conditions through the avatar. Moreover, users showed satisfaction on the use of the health avatar system and its effectiveness in health check-ups in the survey. Conclusions: The ‘Digital Health Avatar’ has the potential to significantly promote individual well-being and health awareness. Its development will be improved by user feedback and continued study, ensuring it becomes an efficient tool for promoting healthier lifestyles. © 2024 The Authors

关键词： Digital health avatar Health sensors Healthcare Three-dimensional model

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