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Comparative analysis of deep learning models for detecting face mask

Procedia computer science 2023年 216卷 48-56页

作者： M Vickya Ramadhan Kahlil Muchtar Yudha Nurdin Maulisa Oktiana Maya Fitria Novi Maulina Gregorius Natanael Elwirehardja Bens Pardamean Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia. Telematics Research Center (TRC) Universitas Syiah Kuala Banda Aceh 23111 Indonesia. Microbiology Department School of Medicine Universitas Syiah Kuala Banda Aceh 23111 Indonesia. Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia. Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia.

The spread of Corona Virus Disease 19 (COVID-19) in Indonesia is still relatively high and has not shown a significant decrease. One of the main reasons is due to the lack of supervision on the implementation of health protocols such as wearing masks in daily activities. Recently, state-of-the-art algorithms were introduced to automate face mask detection. To be more specific, the researchers developed various kinds of architectures for the detection of masks based on computer vision methods. This paper aims to evaluate well-known architectures, namely the ResNet50, VGG11, InceptionV3, EfficientNetB4, and YOLO (You Only Look Once) to recommend the best approach in this specific field. By using the MaskedFace-Net dataset, the experimental results showed that the EfficientNetB4 architecture has better accuracy at 95.77% compared to the YOLOv4 architecture of 93.40%, InceptionV3 of 87.30%, YOLOv3 of 86.35%, ResNet50 of 84.41%, VGG11 of 84.38%, and YOLOv2 of 78.75%, respectively. It should be noted that particularly for YOLO, the model was trained using a collection of MaskedFace-Net images that had been pre-processed and labelled for the task. The model was initially able to train faster with pre-trained weights from the COCO dataset thanks to transfer learning, resulting in a robust set of features expected for face mask detection and classification.

关键词： Binary Classification Deep Learning Face mask detection

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Smart Campus and Education: The Study of Individual Performance in E-Learning Environments

Smart Campus and Education: The Study of Individual Performa...

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International Conference on ICT For Smart Society (ICISS)

作者： Doni Purnama Alamsyah Doni Morika Boby Siswanto Norfaridatul Akmaliah Othman Entrepreneurship Department BINUS Business School Bina Nusantara University Jakarta Indonesia Design Interior Study Program School of Design Bina Nusantara University Jakarta Indonesia Computer Science Study Program School of Computer Science Bina Nusantara University Jakarta Indonesia Department of Technology Management Faculty of Technology Management and Technopreneurship Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

The Learning Management System (LMS) is a component of the Smart Campus and is implemented with e-learning. E-learning can be effective if it gives satisfaction to the user and improves academic performance. Therefore, it is important to evaluate online learning users to support learning outcomes. The purpose of this study is to examine the relationship model of individual performance with support for user satisfaction and flexibility in an e-learning environment. This study was carried out using a survey to 615 e-learning users. Users are among the universities students in the city of Bandung (Indonesia). Data were collected quantitatively through questionnaires distributed online. Data processing is done with SmartPLS, where there are two model tests, namely the PLS Algorithm and Bootstrapping. Results of this study model test found that user satisfaction can be increased by information quality from e-learning. Online learning has perceived flexibility that is assessed by users and can increase user satisfaction and individual performance. It was found that user satisfaction was able to support the individual performance achievements of students as e-learning users. The results from this study provide valuable insights into the role of user satisfaction as a mediator in controlling individual student performance, highlighting the significance of integrating Smart Campus solutions.

关键词： Surveys Learning management systems Electronic learning Urban areas Education Distributed databases Data processing Data models Information integrity

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Development of Portable Temperature and Air Quality Detector for Preventing Covid-19 1

Development of Portable Temperature and Air Quality Detector...

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1st International Conference on computer science and Artificial Intelligence, ICCSAI 2021

作者： Budiharto, Widodo Irwansyah, Edy Dewanti, Retno Santoso Gunawan, Alexander Agung Widhyatmoko, Danu Sembodo, Jarot Soeroso Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Business School Management Department Jakarta Indonesia Bina Nusantara University School of Design Dept. of Visual Communication Design Jakarta Indonesia Bina Nusantara University Master of Information System Program BINUS Graduate Program Jakarta Indonesia

ISBN: (纸本)9781728133331

Due to Covid-19, body temperature measurement is mandatory and become an important consideration in determining whether an individual is healthy or not. This paper presents the development of portable temperature and air quality detector to prevent suspect of Covid-19 with the main symptom is the body of temperature above 38° Celsius. We propose an algorithm and architecture used for temperature detector with maximum distance 80cm and CO2 and Volatile Organic Compounds (VOC) measurement are as indicator of good air quality. Based on experiment, we can detect temperature accurately until 0.3° Celsius using digital temperature sensor MLX90614 comparing with commercial one, furthermore the system able to give information about the quality of air, allowing/not allowing someone to enter a room with accuracy 92.5%. © 2021 IEEE.

关键词： Air quality

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Modified TF-Assoc Term Weighting Method for Text Classification on News Dataset from Twitter

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2021年第1期48卷

作者： Izzah, Imroatul Khuluqi Girsang, Abba Suganda Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Text classification is a process of locating text documents automatically into categories based on the text content. In-text classification, there is a stage that has an important role in giving the value of importance to each document, that is term weighting. In the researchers’ previous study, a new supervised term weighting (TF-Assoc) was introduced with the concept of association to optimize term weighting distribution in a case of multiclass classification. To improve the performance of text categorization, this paper proposes a term weighting scheme with a modified association concept, that is mTF-IDF-Assoc. The proposed term weighting scheme considered Document Length (DL). DL was used to normalize the term frequency by dividing it by the length of the document's vector and then formulting IDF and Assoc in calculating the weight of each word. The results showed that mTF-IDF-Assoc implemented with SVM classifier and 10-fold cross-validation technique could outperform the TF-IDF, TF-ICF, and TF-Assoc weighting scheme with an average accuracy of 82.322%. © 2021, IAENG International Journal of computer science All Rights Reserved.

关键词： Classification (of information)

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Strategic Planning and Knowledge Management Approaches as input to remote area strategic plans: A Case study in Aru Islands Regency Maluku Province 8

Strategic Planning and Knowledge Management Approaches as in...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Irena Gutandjala, Ilona Harso Supangkat, Suhono Lumban Gaol, Ford Rianti, Benny Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta11480 Indonesia Bandung Institute of Technology Smart City and Community Innovation Center School of Electrical and Informatics Engineering Bandung Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781665416979

Knowledge is an important asset in an organization. Aru Islands District is one of the districts in Maluku Province. The Government of Aru Islands District Maluku has a vision and mission as outlined in the Regional Strategic Plan or commonly referred to as RENSTRA. This vision and mission are an activity that requires a policy direction that is planned and integrated with the strategic environment of all related aspects. The strategic plan is then realized with the implementation of the government with regional autonomy which is the modern governance in realizing quality public services, fast, easy, fair and unlimited for the welfare and progress of the region. In this research will be used a strategic approach as input from the analysis with knowledge management and assessment of the condition of Aru district. © 2021 IEEE.

关键词： Strategic planning

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Study of runway crosswind and tailwind potential for airport sustainability: A study of Soekarno Hatta airport, Cengkareng, Indonesia 2

Study of runway crosswind and tailwind potential for airport...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Sardjono, W. Zulkarnain Kusnoputranto, H. Soesilo, T.E.B. Utama, D.N. Sudirwan, J. Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management BINA NUSANTARA University Jakarta11480 Indonesia Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Faculty of Public Health University of Infonesia Jakarta Indonesia Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

Airport runway designs must consider wind climatology to reduce the potential for crosswind and tailwind events that can cause accidents and aircraft delays. The large potential of crosswind and tailwind on a runway at the airport is very detrimental to aircraft passengers and airlines. Therefore, it is necessary to know the potential of crosswind and tailwind on the runway of Soekarno Hatta Airport and find the right parameters for the approximate direction and speed of the wind on the airport runway. Analysis was carried out using the direction and wind speed data from the Soekarno Hatta meteorological station in 2007-2017 to determine the potential for crosswind and tailwind on the runway of Soekarno Hatta airport and run a Weather Research and Forecasting (WRF) weather model to determine the parameterization of the right weather model for wind forecast at Soekarno Hatta airport. The highest maximum crosswind component in the 2007-2017 period occurred in August 30.53 knots, while the highest maximum tailwind of 25 knots occurred in January for a 250-degree runway and 24 knots occurred in August for a 070-degree runway. The potential for crosswind and tailwind is different every month. The scheme produces forecasts of wind direction and speed with a strong level of correlation with observations of wind direction and speed from the Soekarno Hatta meteorological station, the correlation value is 0.61. The most significant social impact of plane delays is time loss for passengers. While the economic impact on one of the crosswind events at Soekarno Hatta airport was an economic loss for one airline of US $ 43,392. © Published under licence by IOP Publishing Ltd.

关键词： Losses

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Web Development of Direct-to-consumer Genetics Testing

Web Development of Direct-to-consumer Genetics Testing

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Kians Azizatikarna Deby Erina Parung Dian Amirullah Alam Ahmad Hidayat Tjeng Wawan Cenggoro Arif Budiarto Simon Bens Pardamean Genetics Indonesia Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

As the cost of genetic testing becomes more affordable each year, direct-to-customer (DTC) genetic testing services witness rapid market growth. This has encouraged the development of an easy-to-use website application to optimize potential customers to obtain informed choice regarding the offered DTC genetic testing as well as purchasing information. We present a wireframing process as a part of the agile software development process to build a web portal prototype for an Indonesia-based genetic testing service called DNAku. The approach in building the prototype used in this case is a part of the Agile Software Development Method. In brief, the wireframing stage resulted in this work consists of three main important outcomes. The first one is the use case diagram as a blueprint of this web-based system. A site map is then proposed as an extended version of the use case diagram which visualizes the whole pages with the links. Finally, based on this site map a series of page mock-ups are designed using Hyper Text Marking Language (HTML) and Cascading Style Sheets (CSS). The result of the prototype can be used as the basis for the next development stage, which is the coding stage based on the collected feedback from users. Considering the continuous application development via the wireframing method by taking into account the cycle of feedbacks from involved parties, this approach can strengthen the infrastructure to sustain DTC genetic business model, which has a niche market in Indonesia.

关键词： Visualization Costs Buildings Prototypes Agile software development Genetics Encoding

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Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter

Social Media Analysis using Sentiment Analysis on COVID-19 f...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Fairuz Iqbal Maulana Yaya Heryadi Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter.

关键词： COVID-19 Sentiment analysis Analytical models Data analysis Social networking (online) Blogs Data visualization

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Disaster recovery plan implementation evaluation model at the corporation

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Procedia computer science 2024年 234卷 1658-1663页

作者： Wahyu Sardjono Widhilaga Gia Perdana Gustian Rama Putra Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta 13220 Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

The application of information technology in addition to making internal business processes more effective and efficient, is also to improve customer service. This role is important for companies to maintain the sustainability of information systems as a strategic tool for competitive advantage so system availability is absolutely essential. Research related to the Disaster Recovery Plan (DRP) needs to be carried out to see the readiness of a corporation to build a backup system in different places and locations. By using the method of factor analysis and regression analysis to form an evaluation model, it will obtain an overview of what factors must be considered and what the current conditions are. The results of the study show that there are Core Technical DRP, Organizational Preparation, and Costing factors which are the main variables in supporting DRP readiness. The conclusion from this study, through these three new factors a mathematical model can be built as a reference for improving DRP implementation in corporations.

关键词： disaster recovery planning factor analysis corporation evaluation model

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Database management system design for COVID-19 symptom analysis 6

Database management system design for COVID-19 symptom analy...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Rahutomo, Reza Darmalim, Ferdinan Cen, Andrew Brilianto, Jayaku Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia PT. Mega Medica Pharmaceuticals IT Department Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Faculty of Technology and Design Bunda Mulia University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Applying a digital strategy is proven to be one way to reduce the infection rate of COVID-19. As a fundamental part of it, database is capable to create a data repository to predict uncertain impacts of the pandemic. The research proposed a database design for project C-Beta that emphasized on creating an ideal system to record and monitor the daily health condition of people with COVID-19. Mainly, the research adopted Connolly and Begg principles of Database Software Development Life Cycle. As a result, the database design activities produced blueprints in the forms of data dictionary, ERD, and user views. The database design delivered in the research included with several features namely user verification, restricted research membership, and flexibility in survey creation. Based on analysis and design phase, C-Beta provides a method to collect data for COVID-19 clinical study. Researchers who utilize C-Beta is able to manage multiple surveys and extract all collected records at the same time. © 2021 IEEE.

关键词： COVID-19

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