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Systematic literature review on physical distancing policy for mass gathering events

AIP Conference Proceedings 2022年第1期2472卷

作者： Asmahany Ramely Mohd Kamal Mohd Nawawi Ruzelan Khalid Antoni Wibowo Amalia Zahra 1School of Tourism Hospitality and Event Management Universiti Utara Malaysia 06010 UUM Sintok Kedah Malaysia 2Institute of Strategic Industrial Decision Modeling School of Quantitative Sciences Universiti Utara Malaysia 06010 UUM Sintok Kedah Malaysia 3Computer Science Department Binus Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The explosive spread of Corona Virus Disease-19 (COVID-19) in late December 2019, requires the health authorities worldwide to enforced stricter standard operating procedures (SOP) for mass gathering events, which eventually caused postponement and cancellation. This has led to a great loss and bankruptcy for most event organizers. As an effort to offer solution to this matter, a professional touch producing “soft landing” such as “Mathematical Modelling of Physical Distancing Policy for Mass Gathering Event Organizer” was proposed. Therefore, a holistic understanding about the issues related to physical distancing in mass gathering event is required. This systematic review paper summarizes current practice of physical distancing among mass gathering event organizers. This study reviewed thirteen articles using two leading databases namely Scopus and Google Scholar. Based on thematic analysis, this review finalized four themes: 1) physical distancing method; 2) the importance of physical distancing; 3) challenges in physical distancing enforcement and 4) approach to monitor the compliance of physical distancing.

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An Improved Version of Texture-based Foreground Segmentation: Block-based Adaptive Segmenter 3

An Improved Version of Texture-based Foreground Segmentation...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Muchtar, Kahlil Rahman, Faris Cenggoro, Tjeng Wawan Budiarto, Arif Pardamean, Bens Nodeflux Inc. Jakarta Indonesia Syiah Kuala University Aceh Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Foreground segmentation is one of moving object detection techniques of computer vision applications. To date, modern moving object detection methods require complex background modeling and thresholds tuning to confront illumination changes. This paper proposes an adaptive approach based on non-overlapping block texture representation. It aims to design a computationally light and efficient solution to improve the robustness of detection. We evaluate our proposed method on internal and public sequences and provide the quantitative and qualitative measurements. Experimental results show that the proposed method can improve the results of previous method and suitable for real-time challenges. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Textures

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Questions Classification in Online Discussion Towards Smart Learning Management System 3

Questions Classification in Online Discussion Towards Smart ...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Wijanarko, Bambang Dwi Murad, Dina Fitria Heryadi, Yaya Lukas Toba, Hapnes Budiharto, Widodo Computer Science Department Doctor of Computer Science Computer Science Department BINUS Online Learning Bina Nusantara University BINUS Graduate Program Jakarta11480 Indonesia Information Systems Department Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University BINUS Online Learning Jakarta11480 Indonesia Jakarta12930 Indonesia

ISBN: (纸本)9781538658215

The widespread interest toward online learning at higher education worldwide brings about necessity toward an smart Learning Management System (LMS), LMS with analytic functionalities, to increase learning outcome of the students. In an effort to develop a smart LMS which is able to both guiding students on learning process and giving automated feedback on online learning delivery to online learning management, this paper presents a preliminary and exploratory results toward textual documents from learning material repository and online discussion forum. The dataset for this study obtained from bina nusantara Online Learning repository. The study found interesting finding namely: There is a significant discrepancy between cognitive domain Taxonomy level between question raised in discussion forum and its respective level of learning outcomes. This findings were confirmed using Anova with P-value © 2018 IEEE.

关键词： Social networking (online)

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Development of Smart Trolley System Based on Android Smartphone Sensors

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Procedia computer science 2019年 157卷 629-637页

作者： Alexander A S Gunawan Valdi Stevanus Albertus Farley Heri Ngarianto Widodo Budiharto Herman Tolle Muhammad Attamimi Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Media Game and Mobile Technologies Research Group Master of Computer Science Brawijaya University Malang Indonesia Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

In supermarkets, a shopping trolley or a shopping cart is the necessary tools for purchasing. Traditionally, it is used by customers inside the store to transport goods to the cashier during shopping and designed not to leave the store. It is an inconvenience and time wasted for customers who want to find the desired product in the store by using the traditional shopping trolley. Our goal is to develop an automatic moving trolley with smart shopping devices to solve the problem. Our smart shopping trolley is based on a two-wheeled mobile robot, developed in our previous research. This paper presents the hardware and software design of a smart trolley system. Our smart trolley used IOIO microcontroller and Android smartphone as sensors and controller. The trolley is modeled as a two-wheeled mobile robot. Android smartphone will control the robot by sending a signal to IOIO microcontroller paired with a robot’s actuator and monitor the situation using the smartphone camera. Furthermore, we exploited the smartphone compass for robot navigation. This system is also equipped with the indoor positioning system to detect user position using Navisens which based on gyroscope and accelerometer in the smartphone. Finally, the results of the testing on robot navigation are presented. The result is our smart trolley system based on Navisens framework can move and show its location to the user.

关键词： Mobile Robot IOIO Android Robot Navigation Indoor Positioning System Navisens

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Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network 3

Deep Learning for Imbalance Data Classification using Class ...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Fanny Cenggoro, Tjeng Wawan Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Without any specific way for imbalance data classification, artificial intelligence algorithm cannot recognize data from minority classes easily. In general, modifying the existing algorithm by assuming that the training data is imbalanced, is the only way to handle imbalance data. However, for a normal data handling, this way mostly produces a deficient result. In this research, we propose a class expert generative adversarial network (CE-GAN) as the solution for imbalance data classification. CE-GAN is a modification in deep learning algorithm architecture that does not have an assumption that the training data is imbalance data. Moreover, CE-GAN is designed to identify more detail about the character of each class before classification step. CE-GAN has been proved in this research to give a good performance for imbalance data classification. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Generative adversarial networks

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Design a website to measure ASEAN entrepreneurship profiling

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： Sasmoko H Saroso H Hartono F Purnomo Y Indrianti M K bin Ramly N Artha Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Entrepreneurship Department Podomoro University Jakarta Indonesia 11470 Research Interest Group in Educational Technology Bina Nusantara University Jakarta Indonesia 11480 Business Administration Department Universiti Teknologi Malaysia Malaysia

ASEAN Entrepreneurship Profiling is one of the initial efforts to bring together profiles among ASEAN countries and to find the most powerful determining factor for entrepreneurs in ASEAN, developed using the Neuroresearch and Waterfall Model research methods. This research aims to identify the design of ASEAN Entrepreneurship Profiling website design to collect data online by using Neuroresearch and Waterfall Model research methods. The result shows that this profiling is expected to be able to contribute to novice entrepreneurs to explore gaps, take advantage of opportunities, prepare for their capacity, and build their potential. It is also easier for business actors when visiting the website as it displays self-profiling and recommendations for themselves.

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Analysis of delay factors on drilling projects on PT China Oilfields Services Limited

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： W Sardjono W G Perdana R Ansori D N Utama Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management BINA NUSANTARA University Jakarta Indonesia 11480 Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Graduate Program Master of Business Administration Faculty of Economic and Business University of Gadjahmada Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In carrying out drilling projects at PT China Oilfields Services Limited ( COSL) Indo, especially Project 1 to Project 4, there were a mismatch between the initial plan of the project and the actualisation in the field because there were inhibiting factors in implementing the project. The purpose of the research was to look the factors that caused for the additional time in well drilling project at PT. COSL Indo, to build a relationship model of these factors, and formulate a strategy for the company to be able to overcome the occurrence of additional time in the future project. Data analysis was conducted by using a factor analysis method and the location of the research was carried out in just one company with 102 valid respondents. The results of the research indicate that there are four factors that influence the time gap, namely Project Management Activities, Risk Analysis and Procurement, Manage Stairs, and Project Planning Development. By knowing the causes of the delay, companies can find the best solutions for future learning and the impact on environmental, social and economic problems can also be anticipated so that sustainable development occurs in the context of petroleum management.

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Android-based member card 'DigiCard' storage application

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IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： K Agusrianto T Chandra A T Wijono A C Sari Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The purpose of this research is to develop mobile application that can store cards to digital form base on Android, that being used by user which have member card as a media to getting rid from the card being damaged or stolen. In the making of this application, literature review and questionaire are being used as data colletion methodology and extreme programming is being used as research methodology. The goals in making this application is the application can store a physical card into digital form, scan barcode from member card, show realtime promo, online registration, and showing nearest retail location using Android Studio with Java programming language. The conclusion of this research is, this application can help the user as media to avoid careless user in using the card in physical form.

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Mining Association rule with Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) data mining technique 2

Mining Association rule with Attribute Oriented Induction Hi...

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2nd International Conference on Inventive Communication and Computational Technologies, ICICCT 2018

作者： Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Heryadi, Yaya Trisetyarso, Agung Sanchez, Horacio Emilio Perez Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Guadalupe30107 Spain

ISBN: (纸本)9781538619742

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as proposed new data mining technique has been success to mine frequent and similar patterns. Moreover, the AOI-HEP data mining technique has been improved with confidence mining pattern into two terms, where firstly give confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern. Secondly, give confidence for each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence for each AOI-HEP pattern will show how interested each of AOI-HEP pattern between frequent and similar pattern, whilst confidence per dataset will show how interested each dataset between frequent and similar pattern. In this paper the mining of AOI-HEP has been extended to mine AOI-HEP association rules using the current AOI-HEP frequent pattern, since association rule deal with frequent pattern. Based from previous experiments upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS, there are 9 finding AOI-HEP frequent patterns where 8 from adult and breast cancer datasets respectively. Finally, there are 2 and 1 AOI-HEP association rules from adult and breast cancer datasets respectively. © 2018 IEEE.

关键词： Association rules

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Ecological Show Cave and Wild Cave: Negative Binomial Gllvm's Arthropod Community Modelling 3

Ecological Show Cave and Wild Cave: Negative Binomial Gllvm'...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Caraka, Rezzy Eko Shohaimi, Shamarina Kurniawan, Isma Dwi Herliansyah, Riki Budiarto, Arif Sari, Shinta Purnama Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia Department of Statistics Padjadjaran University Indonesia Department of Biology UIN Sunan Gunung Djati Bandung Indonesia Kalimantan Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Ecology is a branch of biology that studies the interaction and relationship between organisms and their environment. Abundance, distribution of organisms and patterns of biodiversity are great interests for many ecologists. One of interesting ecosystems to be studied is a cave. A cave has a typical environment character with a vulnerable ecosystem. Many caves in Indonesia, particularly in Gunungsewu karst area have been developed into tourist objects (show caves) and managed imprudently. Such cave management has potential to harm the environment and leads to ecosystem destruction. Arthropods are the most abundance fauna in cave that play critical roles in maintaining cave ecosystems equilibrium. In the heart of statistical ecology, we need to analyze the differences on Arthropods community and abiotic (climatic-edaphic) parameters among show caves and wild caves. Statistical techniques are needed for the extraction of such information. GLLVM is one method that is able to explain spatial-based information and is particularly suitable for ecology. In this paper, we use negative binomial models to see the differences on spatial patterns of predator and decomposer Arthropods, also characteristic of edaphic and climatic in each cave. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Caves

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