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

作者： Syahputra, M.F. Angkasih, A.P. Purnamawati, S. Andayani, U. Abdullah, D. Sriadhi, S. Iskandar, A. Rosida, T.M. Fitriany, J. Sari, I.N. Utama, M.D. Nanuru, R.F. Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Pediatric Universitas Malikussaleh Aceh Utara Indonesia Departement of Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Social and Political Science Universitas Kristen Indonesia Maluku Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia

Autism Spectrum Disorder is a pervasive developmental disorder that will affect children in terms of interpersonal communication, social interaction, and imaginative levels in play. Many therapies to help the motor neuron performance is one of them Pretend Play. Pretend Play is a therapy that invites children in playing to demonstrate something else and tell how to use objects that are considered in the child's imagination. However, in the era of highly developed technology, many fields have used the Augmented Reality method as a visualization of various aspects. With this method researchers will present the therapeutic visualization of the block to 3D transportation tool that is useful for strengthening motor nerves and visual strength of the child. The system can run well during marker detection, marker movement, and 3D object display with the accuracy of precision angle and distance between virtual world with real world reach 100% with angle 0 at distance 31 cm and the maximum distance from the marker is 46 cm and the maximum angle is 30. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Augmented reality

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Exploration of technology Home-based Learning Guidance for Parents and Students during the Covid-19 Pandemic

Exploration of Technology Home-based Learning Guidance for P...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Suzanna Suzanna Sasmoko Sasmoko Ford Lumban Gaol Tanty Oktavia Tokuro Matsuo BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781728173986

With the sudden attack of the Corona Virus Disease 2019 (COVID-19), some 300 million children in the world have been forced to study at home because of the mass closure of schools that began on March 18, 2020. This has caused many obstacles in the teaching and learning process. Every effort is made to minimize the COVID-19 pandemic while ensuring the teaching and learning process is not interrupted. If the school closures too long and the child is trapped inside the house this will have a negative impact on the physical and mental health of the children. This situation makes parents become worried and look for alternative education in addition to formal schooling for their children. Of the various types of education offers that exist homeschooling or commonly known as home-based learning provides a way out for the current situation. Now children are quarantined in their homes and they will return to school once this epidemic fades. But with this disaster, parents' views on homeschooling or home-based learning can be different from before. They may still be marked if home-based learning can be a long-term education. With the existence of COVID-19, most parents might finally realize that education without formal schooling is not a crisis but an opportunity to take their children to a better future. This research was conducted by utilizing a descriptive qualitative method and within the descriptive qualitative method, the concept of document analysis would be utilized the most. It was expected that the results of this research would explore what type of technology parents could prepare for their children to use to initiate home-based learning.

关键词： COVID-19 Pediatrics Text analysis Pandemics Education Government Mental health

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Web Scraping Methods on Odoo Framework to Collect Rupiah Exchange Rate From Bank Indonesia Website

Web Scraping Methods on Odoo Framework to Collect Rupiah Exc...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Masmur Tarigan Ford Lumban Gaol Tukoro Matsuo Doctor of Computer Science Graduate Program Faculty of Computer Science Universitas Bina Nusantara Universitas Esa Unggul Jakarta Indonesia Doctor of Computer Science Universitas Bina Nusantara Jakarta Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Japan Asia University Taiwan

ISBN: (纸本)9781665424219

The foreign currency exchange rate against the rupiah in the Odoo ERP framework system accommodates multi-currencies. However, Odoo has not updated the rupiah exchange rate based on the value from Bank Indonesia regularly. The exchange rate is the price at which one country's currency can be exchanged for another country's currency. The rupiah exchange rate in business has an influence on the cost revenue as well as the profit of the Indonesian company. The problem is updating the rupiah exchange rate must be done manually by looking at the exchange rate on the Bank Indonesia website and entering it into the ERP system according to the current date. The Rupiah exchange rate in foreign currencies needs to be updated regularly by Bank Indonesia exchange rates. To collect rupiah exchange rate uses the Odoo Framework ERP system using the web scraping methods to extract data from Bank Indonesia exchange rates, the library used in scraping is Beautiful Soup. Beautiful Soup is a Python package for parsing HTML and XML. Is used to extract data from HTML, which is useful for web scraping. Rupiah exchange rate updates will be scheduled by the system every day at 12.30 p.m. GMT+07.

关键词： Manufacturing industries Exchange rates Schedules Supply chain management XML Libraries Data mining

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Hybrid descriptor definition for content based image classification using fusion of handcrafted features to convolutional neural network features

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International Journal of Information technology (Singapore) 2021年第4期13卷 1365-1374页

作者： Das, Rik Kumari, Khusbu De, Sourav Manjhi, P.K. Thepade, Sudeep Department of Post Graduate Program in Information Technology Xavier Institute of Social Service Ranchi Jharkhand India Department of Computer Applications Yogoda Satsanga Mahavidyalaya Ranchi Jharkhand India Department of Computer Science & Engineering Cooch Behar Government Engineering College Cooch Behar India Department of Mathematics Vinoba Bhave University Hazaribag Jharkhand India Department of Computer Engineering Pimpri Chinchwad College of Engineering Pune India

The efficacy of content-based image classification is dependent on the richness of the feature vectors extracted from the image data. Traditional feature extraction techniques highlight single low level image characteristics like shape, size, texture, color etc. for feature generation. The process often fails to extract meaningful descriptors since considering a single image characteristic will ignore other rich properties of image contents. Mass adoption of Convolutional Neural Network (CNN) has significantly improved classification performances for content-based image data. Recent literature has documented high level of precision for image classification by carrying out transfer learning with open source pre trained Convolutional Neural Network (CNN). However, the concept of transfer learning experiences major setback in case of limited training data due to overfitting of training instances during finetuning. This work has identified this challenge and has attempted to capture probability distribution of input images to a pre trained Convolution Neural Network by utilizing it as a fixed weight feature extractor. The proposed approach has addressed the overfitting problem by removing the finetuning step involved in transfer learning. Further investigation on robust descriptor definition is carried out by concatenating the pre-trained CNN features to handcrafted features. The hybrid architecture has encouraging outcomes that have outclassed the classification accuracies of state-of-the-art handcrafted techniques. © 2021, Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Augmented feature learning Feature fusion Handcrafted features Image classification Pre trained Convolutional Neural Network (CNN) Representation learning

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Warding off the plagiarism with the applications (Case study at Bina Nusantara University student and faculty member) 1

Warding off the plagiarism with the applications (Case study...

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1st International Conference on Information and Communications technology, ICOIACT 2018

作者： Surjandy Suparta, Wayan Trisetyarso, Agung Kang, Chul Ho Abbas, Bahtiar Saleh Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Audit Program Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Civil Engineering Department University of Technology Yogyakarta Yogyakarta Indonesia Department of Electronics and Communication Engineering Kwangwoon University Korea Republic of Department of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

Plagiarism in the education sector is as serious issues. In 2015 Indonesia ministry of research, technology and higher education stated to eradicate the plagiarism, and after 2 years the similar statement by Indonesia ministry of research, technology, and higher education. The plagiarism becomes the serious program by the ministry. The plagiarism in higher education happened, the faculty member or even a professor found did the plagiarism. Therefore, this paper research conducted using descriptive analysis methodology to elaborate on deep the correlation plagiarism variables. Hence, warding off the plagiarism might possible to perform using the applications. The aim of this research to find the correlation variables that might use to ward off the plagiarism in the future. The very interesting result from 15 questioners and the report shows there are several significant correlation variables of the plagiarism. © 2018 IEEE.

关键词： Intellectual property

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space

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Procedia computer science 2023年 227卷 1046-1053页

作者： Fergianto E. Gunawan Arief S. Budiman Bens Pardamean Endang Juana Sugiarto Romeli Tjeng W. Cenggoro Kartika Purwandari Alam A. Hidayat Anak. A.N.P. Redi Muhammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta 11440 Indonesia PT Impack Pratama Industri Jakarta 14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99.

关键词： closed space deep learning humity prediction indoor temperature prediction

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Human Touch Behavior Classification to Therapy Robot using SOM

Human Touch Behavior Classification to Therapy Robot using S...

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Annual Conference of the IEEE industrial Electronics Society

作者： Koji Makino Wasantha Samarathunga Hubais Abdelrahman Jin-Hua She Yasuhiro Ohyama Hiroshi Hashimoto Graduate school of medicine and Engineering University of Yamanashi School of Computer Science Tokyo University of Technology Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology

ISBN: (纸本)9781479902255

In this research, a classification method for human touching behaviors to haptic therapy robot is proposed. It is difficult to apply explicit discrete representation for human touch behaviors such as "slap", "pat" due to the existence of intermediate touch behavioral patterns. Therefore a new classification approach for human touch behaviors using Self Organizing Map (SOM) is proposed, using its ability to classify the nearby data in to a group. Further in this research the axis of out put maps are defined to be meaningful by specifying the initial placement of the input data during the training process.

关键词： Touch self-organising feature maps GRHL3 gene Classification Methods incoming data Robot Axis Human maps Medicine

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Recommending mobile content using content diffusion and user preference transition

Recommending mobile content using content diffusion and user...

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2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008

作者： Lee, Tong Queue Lee, Eunchang Park, Young Park, Yongtae Department of Mobile Internet Dongyang Technical College Seoul Korea Republic of Graduate Program in Technology and Management Seoul National University Seoul Korea Republic of Department of Computer Science and Information Systems Bradley University Peoria IL United States Department of Industrial Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)1601320639

Recommendation accuracy is especially important in mobile e-commerce environments due to the limited screen size of mobile devices and relatively expensive connection costs. Mobile content tends to be fashionable and are geared for young users. This paper presents a novel method of building a more accurate recommender system for mobile content in a mobile ecommerce environment. The method is based on collaborative filtering, and models content diffusion and user preference transition and incorporates them in constructing pseudo ratings from implicit feedback data. In a variety of experiments, recommender systems based on the method showed significantly better recommendation accuracy than a pure collaborative filtering-based recommender system.

关键词： Collaborative filtering

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An Augmented Reality Game's User Experience and Its Effect on Immersion Leading to Intention

An Augmented Reality Game's User Experience and Its Effect o...

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International Conference on ICT For Smart Society (ICISS)

作者： Tanty Oktavia Kawang Utomo Ford Lumban Gaol Takaaki Hosoda Information Systems Management Department BINUS Graduate Program - Master of Information System Management Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Since the emergence of Pokémon Go in 2016, the world has been introduced to Augmented Reality (AR) games. Many IT companies have begun developing augmented reality (AR) games due to the great commercial potential in this industry. Certain products may have managed to remain viable in the market, while others were forced to close due to one or two factors. Since the emergence of Pokémon Go, no other game has managed to surpass its unprecedented success. The company responsible for developing Pokémon Go has decided to shut down one of their games due to a lack of consumer interest. The technology of augmented reality (AR) is consistently associated with the concept of immersion. Immersion is a key aspect of the game that allows users to deeply engage and feel fully involved in the experience. This study will employ a quantitative methodology, utilising a questionnaire that will be distributed to and completed by those who have engaged in augmented reality (AR) games. The data will be analysed using Smart PLS to examine the impact of user experience on immersion, which in turn influences intention. After gathering over 200 participants by spreading google form questionnaires and doing data analysis, the findings indicate that only a few aspects of user experience, namely Brand Experience and User Need Experience, have an impact on reasons. Niantic, the developer of Pokémon Go, was unable to replicate their success with a similar augmented reality game called Harry Potter: Wizards Unite. The initial release occurred on June 21, 2019, and the shutdown took place on December 21, 2021. In the beginning, they shown a profound enthusiasm for the game but were unable to sustain it, much as Pokémon Go. According to Niantic CEO John Hanke, the primary reason for the game's shutdown was its immersion. Immersion has a notable impact on User Confirmation, which in turn has a notable impact on Satisfaction, and Satisfaction has a notable impact on Intention. Moreover, there have be

关键词： Surveys Industries Data analysis Games Companies User experience Software Hardware Internet Augmented reality

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Experimental selection and verification of maximum-heart-rate formulas for use with karvonen formula

Experimental selection and verification of maximum-heart-rat...

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10th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2013

作者： She, Jinhua Nakamura, Hitoshi Makino, Koji Ohyama, Yasuhiro Hashimoto, Hiroshi Wu, Min Graduate School of Bionics Computer and Media Sciences Tokyo University of Technology 1404-1 Katakura Hachioji Tokyo 192-0982 Japan Interdisciplinary Graduate School of Medical and Engineering University of Yamanashi 4-3-11 Takeda Kofu 400-8511 Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology Shinagawa Tokyo 140-0011 Japan School of Information Science and Engineering Central South University Changsha 410083 China

ISBN: (纸本)9789898565716

Maximum heart rate (MHR) is commonly used to estimate exercise intensity with the Karvonen formula, and there are several methods of calculating it. In this study, we used pedaling experiments on a cycle ergometer to evaluate methods of determining MHR in order to select the ones most suitable for the Karvonen formula. In the experiments, 43 subjects rode an aerobike. The results show that, for people in their 20s, two methods are suitable for estimating exercise intensity with the Karvonen formula. The main physical parameters affecting exercise intensity were also extracted, based on the experimental results.

关键词： Heart

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