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Application internet of things in healthcare Covid-19: A systematic review

AIP Conference Proceedings 2023年第1期2594卷

作者： H. Citrawati G. P. L. Barnabas T. A. Santoso Suharjito Computer Science Department BINUS Graduate Program -Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480

Coronavirus, or Covid-19, is a new virus first discovered in Wuhan, China, at the end of 2019. This virus attacks the human respiratory area, which can cause respiratory problems and even loss of life. Covid-19 virus transmission is also high-speed and very easy; it is transmitted through airborne and human droplets. Therefore, to reduce the transmission rate of this virus, several researchers revealed that social distancing is one way to suppress the transmission of the Covid-19 virus. In the era of technology, The Internet of Things (IoT) is one of the systems that can help to solve this problem. The Internet of Things (IoT) cancan use one or more devices connected to the network, and it can exchange data and information effectively and efficiently. In this study, the researchers review several IoT technologies that can be used to detect COVID-19 symptoms and implement social distancing rules based on the latest literature. The review results show that IoT technology has been used to monitor the progress of COVID-19 patients in real-time with various sensors connected to geographic positioning systems, mobile devices, and cloud computing. Several research proposals for the development of IoT technology have been identified, such as the detection of COVID-19 patients in crowds, prediction of the spread of the virus in an area, and implementation of health protocols in various crowded locations.

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RepositORE: A Learning Objects Repository for Educational Robotics

RepositORE: A Learning Objects Repository for Educational Ro...

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IEEE Latin American Robotics Symposium, LARS

作者： Kefton David Nunes De Melo Cleyton Carlos Santos Costa Thalia Katiane Sampaio Gurgel Sebastião Emidio Alves Filho Computer Science Course State University of Rio Grande do Norte Mossoró RN Brazil Master's Course in Computer Science Rio Grande do Norte State University (UERN) and Federal University of the Semi-Arid Region (UFERSA) Mossoró RN Brazil Postgraduate Program in Computer Science - PPgCC UERN/UFERSA Rio Grande do Norte State University (UERN) and Federal University of the Semi-Arid Region (UFERSA) Mossoró RN Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

Education is a motivating area for the use of technologies because the learning process can become more dynamic and interesting. Among the technological resources used in education, Educational Robotics stands out by enabling the development of technological projects that can involve techniques of construction and manipulation of robots and enable the development of the creative process, logical reasoning, and interdisciplinarity. However, acquiring knowledge in this area can be a complex task since the learning objects are spread due to the increase in content production brought by the massive use of the Internet. Thus, the present work has as a general objective present RepositORE, a repository where these objects of Educational Robotics can be stored and searched by users who need to acquire specific abilities. For Educational Robotics objects to be found faster and achieve their technical and pedagogical goals, the system uses metadata for the correct description of stored objects based on the Dublin Core Metadata standard. To improve and simplify the search for objects, an adaptation and extension of the Dublin Core standard was made to represent the specific information for Educational Robotics. RepositORE allows users to insert new content and collaborate through complementing information from objects registered by other users.

关键词： Conferences Education Production Metadata Search problems Cognition Internet

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Song Recommendation System Using Collaborative Filtering Methods 19

Song Recommendation System Using Collaborative Filtering Met...

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Proceedings of the 3rd International Conference on Digital Technology in Education

作者： Abba Suganda Girsang Antoni Wibowo Edwin Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450372206

Currently, digital online music increase significantly, both in terms of content and users. Increasing the number of digital music content every month conduce a lot of song catalog data and becoming unstructured and making it difficult for users to choose the songs they want to listen to. To make it easier for users to optimize a large number of subscribed music catalogs, a user-centric music recommendation system is needed that allows users to be able to manage catalogs of digital music content according to their needs. This study examines how to implement song recommendation system using collaborative filtering method in digital online music. This study uses 20,000 users, 6,000 songs and 470,000 transactions rating. Through those research, it is discovered that user-based collaborative technique that could make one system for clients will gather those playlist they really want to hear.

关键词： digital music recommendation playlist generation Collaborative filtering

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The Use of Book Store GIS Data Warehouse in Implementing the Analysis of Most Book Selling 7

The Use of Book Store GIS Data Warehouse in Implementing the...

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

作者： Harvy, Ikrar Matitaputty, Gilbert Alessandro Girsang, Abba Suganda Michael, Steve Isa, Sani Muhamad BINUS Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781728129099

Data is the part that represents the evidence in presenting the state of the surrounding environment, obtained through research in the form of numbers, sources or scales. with data, conditions can be measured to produce the best solution. GIS Bookstore is one company that needs data every month to be analyzed. However, GIS Bookstore has constraints in processing large data with increasing time. for example GIS bookstore has problems in analyzing bestsellers because of the increasing number of authors and book publishers who work together. In this study, GIS Bookstore found a solution by implementing business intelligence that plays a role in the processing of raw data in large amounts of data into well-structured data information, the results are collected and processed in a data warehouse scheme. Targets stored in the data warehouse are data that will be processed based on the model design method (ERD) and star schema. This paper discusses the GIS Bookstore data warehouse with the aim of analyzing the sales of most books based on a certain time period. The method used in retrieving data uses Pentaho data integration tools, MySQL workbench, report designer, bi server and workbench schema. © 2019 IEEE.

关键词： Data warehouses

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Clustering Steam User Behavior Data using K-Prototypes Algorithm

Clustering Steam User Behavior Data using K-Prototypes Algor...

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

作者： Ranti, Kiefer Stefano Salim, Kelvin Girsang, Abba Suganda Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

The use of user telemetry to gather player behavioral data on video games can be very beneficial to game developers with a certain business model. With the help of user telemetry in game development, it can provide access to data on user behavior from installed game clients platform such as Steam. These behavioral data can be used to find out the Steam user behavioral patterns on playtime distributions that can be studied by developers in order to have a deeper understanding of the behaviors of their players. In this study, the data are clustered using the k-prototypes algorithm, a combination of k-means and k-modes algorithm that can be used to cluster mixed attributes. The result shows that the clusters represent the types and preferences of the players. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Software design

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A Review of Implementation and Obstacles in Predictive Machine Learning Model at Educational Institutions 2

A Review of Implementation and Obstacles in Predictive Machi...

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2nd International Conference on computer, science, Engineering, and Technology, ICComSET 2019

作者： Ranggadara, Indra Sari, Yunita Sartika Dwiasnati, Saruni Prihandi, Ifan Sfenrianto Computer Science Department Mercu Buana University Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Machine learning is a system that can learn by itself by using training data and testing data testing. In a variety of machine learning research has various obstacles in implementation especially in education institution, in its application, many things need to considered for more information to enrich research in the area of machine learning by way of comparing various obstacles in implementation in similar research. So that in this study is to find similarities and anticipations made in the initial stages of pre-processing to visualisation, as well as the contribution that can give in this study explains the best alternative for researching following the experience of several researchers in conducting machine learning research. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Machine learning

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Virtual Plant of Basil (Ocimum Basillicum) by Using Functional-Structural Plant Model

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Ditdit Nugeraha Utama Heraldo Y Purwantono Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Indonesia is one of the most populated and large country in south-east Asia. Its abundance of natural resources was well known. Supported by its tropical climate, made Indonesia is also among the largest tropical country in the world. However, according to the data, arable land in Indonesia has drastically decreased over the years in line with the rising demand for residency areas. This statistic shows a rather concerning fact that it is possible that even though Indonesia with this richness of natural resources one day would not fulfil its own domestic food needs. Moreover, competitions and hindrances that experienced by the Indonesian farmers might also worsen this limited food supply. In this research, the computational plant model (called virtual model) of the above-land Basil plant (Ocimum Basillicum P.) was proposed. The Basil plant that is taken as a research object is specific. It is a plant growing in a hydroponic environment. By using structural and functional plant model (FSPM) and simple mathematical and statistical methods, the constructed model was able to portray the growth pattern of each plant organ morphologically and biologically. The development and growth patterns of each plant organ (i.e., stem, petiole, leaves, etc.) are also depicted in detail and precisely. The model was quite novel. It practically can be exploited by agronomists and researchers to see the potential effort in optimizing the plant's yield.

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Virtual Plant Computational Model of Green-Leaf Vegetable Plant Bok Choy (Brassica chinensis L.) for Investment Decision

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： D. N. Utama A. Wibowo Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Plant computational modelling is a part of ecological informatics. It is a research domain that model the plant/s and is correlated to an environmental issue. A vegetable is one imperative plant. It has an important role in aspects of health, the environment, and also the economy. The study was performed to make a plant computational model of the green-leaf vegetable plant Bok Choy that can suggest the environment-oriented decision in agriculture investment. Two methods functional structural plant modelling (FSPM) and simple mathematics are operated respectively to model the Bok Choy plant morphologically and the decision recommendation. The study produced the morphological 3-dimension (3D) model of the forty-fve-day-age plant Bok Choy and investment decision to plant Bok Choy in a hydroponic system.

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Count time series modelling of Twitter data topic modelling: A case of Indonesia flood events

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AIP Conference Proceedings 2023年第1期2594卷

作者： A. A. Hidayat B Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Twitter data provide rich and powerful information to leverage the dynamics of public perception to establish situational awareness and disaster mitigation strategies during critical times. In this paper, we perform topic modeling via Latent Dirichlet Allocation to extract topics from a collection of tweets related to Indonesia flood events in February 2021 with the query: “banjir”. The extracted topics are used as one of the features to build a generalized linear count time series model with Negative Binomial distribution. We find seven major topics from the model in which tweets containing a topic about the government’s role in handling the situation dominate the conversation. Taking into account a simple intervention analysis, we demonstrate a statistically significant change in the users’ behavior before and after the severe Jakarta flood on 20 February 2021. Moreover, a metric evaluation demonstrates that a covariate that describes the turning point of the Jakarta flood event is convenient to build a more accurate count time series model of the tweets.

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The Performance Investigation of Smart Diagnosis for Bearings Using Mixed Chaotic Features with Fractional Order

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Sensors 2023年第8期23卷 3801-3801页

作者： Li, Shih-Yu Tam, Lap-Mou Wu, Shih-Ping Tsai, Wei-Lin Hu, Chia-Wen Cheng, Li-Yang Xu, Yu-Xuan Cheng, Shyi-Chyi Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei10608 Taiwan Institute for the Development and Quality 999078 China Department of Electromechanical Engineering Faculty of Science and Technology University of Macau 999078 China Master Program Graduate Institute of Mechatronic Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Mechanical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Keelung City202301 Taiwan

This article presents a performance investigation of a fault detection approach for bearings using different chaotic features with fractional order, where the five different chaotic features and three combinations are clearly described, and the detection achievement is organized. In the architecture of the method, a fractional order chaotic system is first applied to produce a chaotic map of the original vibration signal in the chaotic domain, where small changes in the signal with different bearing statuses might be present;then, a 3D feature map can be obtained. Second, five different features, combination methods, and corresponding extraction functions are introduced. In the third action, the correlation functions of extension theory used to construct the classical domain and joint fields are applied to further define the ranges belonging to different bearing statuses. Finally, testing data are fed into the detection system to verify the performance. The experimental results show that the proposed different chaotic features perform well in the detection of bearings with 7 and 21 mil diameters, and an average accuracy rate of 94.4% was achieved in all cases. © 2023 by the authors.

关键词： Fault detection

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