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Implementation of online learning during the COVID-19 pandemic in primary schools

AIP Conference Proceedings 2023年第1期2594卷

作者： A. Anugrahana E. Liswantiani D. Sudigyo T. Suparyanto B. Pardamean Elementary School Teacher Education Study Program (PGSD) Faculty of Teacher Training and Education Sanata Dharma University Yogyakarta Indonesia 55281 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The COVID-19 pandemic requires face-to-face learning to shift to online or distance learning. Therefore, the elementary school, which is the most basic level of education affected by this phenomenon, where this research is carried out. This study aimed to analyze the process of implementing online learning, the supporting and inhibiting factors for teachers, students, and parents in implementing online learning during the COVID-19 pandemic. In addition, good practices for online learning were also analyzed in this study to understand these phenomena in elementary schools. The research method utilized descriptive qualitative research and was performed at a private primary school in Yogyakarta. The subjects consisted of teachers, students, and parents that were involved in the online learning process. Online questionnaires and interviews were used to collect data. The results of this study show the enormous impact of the COVID-19 pandemic on the learning process. Learning that is usually carried out face-to-face (conventional) has now been converted into online learning in elementary school.

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Next Generation Firewall for Improving Security in Company and IoT Network

Next Generation Firewall for Improving Security in Company a...

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2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019

作者： Soewito, Benfano Andhika, Charlie Erwin Bina Nusantara University Computer Science Department BINUS Graduate Program Computer Science Jakarta Indonesia

ISBN: (纸本)9781728137490

The goal of this research is to analyze of effectiveness the Next Generation Firewall that implemented to secure IoT in smart house and company network. The method used in this research is the method of comparison with a test of DDoS attacks, phishing and SQL Injection on both network, smart house network and company network. From the results of experiment, it can be concluded that the Next Generation Firewall has significantly better performance for protecting smart house and company network, it can increase security of data communication networks against threats from the Internet. © 2019 IEEE.

关键词： Network security

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Systematic literature review: Accelerate the rice production for global food security

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AIP Conference Proceedings 2023年第1期2594卷

作者： N. Dominic T. W. Cenggoro B. Pardamean Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

By 2050, about 70% of extra food production is needed to feed the world's population. As a majority staple food, the expansion of rice production should be accelerated. This systematic literature review aims to discover the factors that influence rice yields through a methodology that is partitioned into four main stages, i.e., query entry into multiple database sources, article title filtering, abstract filtering, and final article selection. The results show that genetics, irrigation system management, and farmers’ long-evolved local knowledge or experiences are the three big factors that elevate the rice production rates. Nevertheless, global warming is a serious challenge that should be deeply considered due to its great impact on reducing rice yields by up to 14.5%. Thus, the development of genetically modified rice varieties needs to be escalated while still maintaining other exogenous factors. This study contributes to providing a broader perspective for decision-makers and other relevant experts to accelerate rice production to achieve global food security.

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Low Resolution Face Recognition Using Generative Adversarial Network (GAN)

Research Square

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Research Square 2020年

作者： Martin, Howard Suharjito Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University - Anggrek Campus Jakarta11480 Indonesia Department Computer Science BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

Face recognition has a lot of use on smartphone authentication, finding people, etc. Nowadays, face recognition with a constrained environment has achieved very good performance on accuracy. However, the accuracy of existing face recognition methods will gradually decrease when using a dataset with an unconstrained environment. Face image with an unconstrained environment is usually taken from a surveillance camera. In general, surveillance cameras will be placed on the corner of a room or even on the street. So, the image resolution will be low. Low-resolution image will cause the face very hard to be recognized and the accuracy will eventually decrease. That is the main reason why increasing the accuracy of the Low-Resolution Face Recognition (LRFR) problem is still challenging. This research aimed to solve the Low-Resolution Face Recognition (LRFR) problem. The datasets are YouTube Faces Database (YTF) and Labelled Faces in The Wild (LFW). In this research, face image resolution would be decreased using bicubic linear and became the low-resolution image data. Then super resolution methods as the preprocessing step would increase the image resolution. Super resolution methods used in this research are Super resolution GAN (SRGAN) [1] and Enhanced Super resolution GAN (ESRGAN) [2]. These methods would be compared to reach a better accuracy on solving LRFR problem. After increased the image resolution, the image would be recognized using FaceNet. This research concluded that using super resolution as the preprocessing step for LRFR problem has achieved a higher accuracy compared to [3]. The highest accuracy achieved by using ESRGAN as the preprocessing and FaceNet for face recognition with accuracy of 98.96 % and Validation rate 96.757 %. © 2020, CC BY.

关键词： Face recognition

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AI-Based Ripeness Grading for Oil Palm Fresh Fruit Bunch in Smart Crane Grabber 3

AI-Based Ripeness Grading for Oil Palm Fresh Fruit Bunch in ...

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3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Harsawardana Rahutomo, Reza Mahesworo, Bharuno Cenggoro, Tjeng Wawan Budiarto, Arif Suparyanto, Teddy Surya Atmaja, Don Bosco Samoedro, Bayu Pardamean, Bens Institut Pertanian STIPER Yogyakarta55281 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mechatronics and AI Research and Development Center Biotechnic Innovation Yogyakarta55281 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Indonesia is one of the biggest palm oil exporters in the world. For Indonesia to stay competitive in thepalm oil industry, the harvesting and evacuating process in its oil palm plantation need to be optimized. This research introduces machinerycalled as Smart Crane Grabber. This machinery can be used for automatic harvesting and evacuation process of oil palm fresh fruit bunch. To enable automation, Smart Crane Grabber is equipped with an Artificial Intelligencesystem for automatic ripeness sorting. TheArtificial Intelligence system developed for Smart Crane Grabber achieves 71.34% accuracy by using only 400 images as preliminary training data. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Palm oil

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Jakarta Government Official Portal Acceptance Based On Technology Acceptance Model

Jakarta Government Official Portal Acceptance Based On Techn...

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International Conference on Information Technology Systems and Innovation (ICITSI)

作者： Cahyono Budy Santoso Wayan Suparta Edi Abdurachman Agung Trisetyarso BINUS Graduate Program-Doctor of Computer Science Bina Nusantara Unversity Jakarta Indonesia

ISBN: (数字)9781728181967

ISBN: (纸本)9781728181974

The continuity of the quality of the official portal of DKI Jakarta province in terms of information, relevance and population must be maintained, evaluated and can be developed so that the public can get significant benefits. The purpose of this study was to determine the level of public acceptance of the portal site using the Technology Acceptance Model (TAM) approach. The methodology of this research is to make a survey of the public as users of the portal site, with the objectives based on perceived ease of use, perceived usefulness, behavioral intention to use, attitude toward using technology and actual system use of the portal site. This research is a quantitative research based on data through a questionnaire with a likert scale conducted for users of the Jakarta portal. This study uses a Structural Equation Modeling (SEM) analysis method based on the Partial Least Square (PLS) variant..There are 6 hypotheses proposed in this study, from the test results found 4 acceptable hypotheses. The hypothesis shows that the actual system usage factor is influenced by the Behavioral Intention to use factor of 48.9%. While the Behavioral Intention to use factor is influenced by the Perceived Usefulness factor of 43.9%.

关键词： Portals Government Load modeling Technology acceptance model Information technology computer science Biological system modeling

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Implementation TDOA and FDOA Algorithms for Satellite Geolocation Interference Finder in Indonesia

Implementation TDOA and FDOA Algorithms for Satellite Geoloc...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Ilvico Sonata Agung Trisetyarso Wayan Suparta Edi Abdurachman BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

The following topics are dealt with: antenna radiation patterns; 5G mobile communication; antenna feeds; MIMO communication; Internet of Things; UHF antennas; Internet; cellular radio; microstrip antennas; wireless ch... 详细信息

ISBN: (数字)9780738125176

ISBN: (纸本)9781665418614

关键词： Satellites Interference Mathematical model computer science Geology Urban areas Conferences

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GIS-Based MCDM for Central Business Suitability in a Small City

GIS-Based MCDM for Central Business Suitability in a Small C...

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International Conference on Informatics and Computing (ICIC)

作者： Herlawati Herlawati Edi Abdurachman Yaya Heryadi Haryono Soeparno BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728180472

ISBN: (纸本)9781728180489

Extended urbanization phenomenon in smaller-sized cities in Java should be considered by the government. However, the local governments can only use the plans from the central government. The negative effects of this, among others, are improper land use allocation, lack of facilities, and crimes that are difficult to handle. This study proposes a geographic information system (GIS)-based method to analyze the proper central business district in Karawang, a small district in Java, Indonesia. Multi-criteria analysis of factors affecting the candidate locations was used through a weighted sum method in a model. The spatial data were retrieved and analyzed using a GIS tool to classify region into urban, peri-urban, and rural. Some central business locations have been found after reclassification which is located near the toll gates. Two locations in the north of Karawang were classified have the potential to become the new central business locations.

关键词： Java Urban areas Tools Spatial databases Sustainable development Business Geographic information systems

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Correction to: Special section editorial: The frontiers of augmented and mixed reality in all levels of education

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Education and Information Technologies 2023年第3期29卷 3757-3757页

作者： Gaol, Ford Lumban Prasolova-Førland, Ekaterina Department of Doctor of Computer Science BINUS Graduate Program Binus University Jakarta Indonesia Department of Education and Lifelong Learning Faculty of Social and Educational Sciences Norwegian University of Science and Technology Trondheim Norway

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Latent Regression and Ordination Risk of Infectious Disease and Climate

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Procedia computer science 2021年 179卷 25-32页

作者： Rezzy Eko Caraka Rung Ching Chen Youngjo Lee Prana Ugiana Gio Arif Budiarto Bens Pardamean College of Informatics Chaoyang University of Technology 168 Jifong East Road Wufong Dist. Taichung City 41349 Taiwan (R.O.C.). Department of Statistics College of Natural Science Seoul National University Gwanak-gu Seoul 08826 Korea Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Mathematics Universitas Sumatera Utara Medan 20222 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Indonesia.

Global warming arising from climate change can increase the spread of deadly diseases. Effort is needed to develop a set of policies for the government to stem or reduce health risks from global warming. The purpose of this paper is to examine more detail and comprehensively about the relationship among climate and event disease count in Taiwan using the partial least square latent regression model. The results obtained that of the 17 types of diseases in Taiwan, that has the most significant loading factor is Amoebiasis, Malaria and Chikungunya. At the same time, climate variables that have the biggest most significant factor are Number day with max temp more than 30, Number day Temp more than 25, and Rainfall PH. Cronbach’s Alpha infectious disease 0.9696 and climate 0.2813. At the same time, the value of Dillon Goldstein’s rho infectious disease 0.974 and climate 0.6404, respectively.

关键词： Disease Counts Climate Latent PLS Regression

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