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Augmented Reality in Chemistry Learning: A Systematic Literature Review 7

Augmented Reality in Chemistry Learning: A Systematic Litera...

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7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Ariessanti, Hani Dewi Prabowo, Harjanto Gaol, Ford Lumban Meyliana Bina Nusantara University Binus Graduate Program - Information System Jakarta11480 Indonesia Management Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

This study reviews factors affecting AR-based chemistry learning with the BIM model. Although there have been many kinds of research explaining the application of augmented reality (AR) and building information modeling (BIM) in learning, no research has been found that discusses the factors affecting the integration of BIM in AR-based learning. This study adopted the SLR method with the PRISMA protocol by scanning articles written in English or articles written in Indonesian from accredited online databases, and fully accessible by the authors. The articles reviewed were related to AR, BIM, Virtual Reality (VR), and chemistry learning. The predefined strings were used to extract the 156 articles. Only 41 articles met the inclusion criteria that were used as the reference for this study. Six factors were found that affect the AR-based chemistry learning with the BIM model. They are AR work performance, accessibility, user interaction with the system, presentation of material, understanding, and models. This study implies that the factors extracted can be considered as a model in developing learning media to improve chemistry learning. The limitation of this study is the absence of further analysis of which critical factors should be addressed. Researchers recommend further research by reviewing more literature. © 2022 IEEE.

关键词： Augmented reality

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Authorship Attribution in Bahasa Indonesia Using Twitter Dataset on Political Topic 4

Authorship Attribution in Bahasa Indonesia Using Twitter Dat...

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Muliono, Yohan Gaol, Ford Lumban Chowanda, Andry Budiharto, Widodo Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Fake news so called made-up news intended to cause misinformation is identified as Hoax. In Indonesia, hoaxes could not be ignored, fairly low literacy rate is the cause of hoaxes could spread quickly in Indonesia, to make it even worse, there are so many people would believe in hoaxes without any intention to make sure of the integrity of the news. even the media in Indonesia are competing with one another to provide content with provocative names in the hopes of increasing their rating and reaching as many people as possible. In the course of this research, a method for identifying authors on the basis of their writings will be developed to reduce the spread of hoaxes and encourage people to re-evaluate their decision to create harmful content and hoax news in the future. In this investigation, a transformer-based methodology focusing on IndoBERTbase, IndoBERTbase-uncased, and IndoBERTtweet will be employed in conjunction with the self-collected Indonesian tweet data that will be crawled from Indonesian Social Actor Focused on politicians in Twitter and will be combined with another topic in the future study. This research has shown a promising 98,93% in Training Accuracy using IndoBERTtweet. © 2023 IEEE.

关键词： Curricula

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Systematic Literature Review on IT Strategic Workspaces: Approach to Develop an Ideal Environment 9

Systematic Literature Review on IT Strategic Workspaces: App...

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Putra, Alden Ardiwinata Fusanto, Princessa Fortunata Valonika, Nebrisca Anggreainy, Maria Susan Kurniawan, Afdhal Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program Doctor of Computer Science Computer Science Department Bina Nusantara University Jakarta11530 Indonesia

ISBN: (纸本)9798350370126

Technology and information will always develop dynamically;this statement demands programmers to always be creative and keep up with the times. Despite this, their work ethic is always the same and tends to stagnate. programmers' perspectives on their workplace: this perspective is rarely seen as important and the opportunity for a comprehensive study is still widely open. This study aims to conduct a systematic literacy study to ascertain that the workplace has a crucial relationship with a programmer's performance. The focus of the study includes a discussion of how programmers relate to their workplace in a tech company, benchmarking between various office layouts, and criteria that can be derived from the literature review regarding a degree of whether such a workplace is good or bad. The proper base facts are obtained. Nevertheless, the two entities are proven to be interrelated to each other. Such correlations are derived into tangible metrics and parameters (e.g., human cognitive, cultural, physical, behavioral, etc.). Relating issues regarding these topics are also presented. © 2023 IEEE.

关键词： Software engineering

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An Analysis of Hate Speech Detection Techniques 4

An Analysis of Hate Speech Detection Techniques

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Krisdianto, Ricky Apriani, Ivana Halim, Peter Miracle Anggreainy, Maria Susan Kurniawan, Afdhal School of Computer Science Bina Nusantara University Computer Science Departement Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Departement Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Hate speech is any act of provoking or insulting another person or group based on their ethnicity, religion, race, gender, sexual orientation, physical ability, or other characteristics. This can be done in a variety of ways. Because of this, a study was conducted that focused on ascertaining the most effective technique for identifying hate speech. It was discovered that LSTM, a form of recurrent neural network (RNN) that is particularly good at modeling sequential data, is the most successful technique to apply. Many natural language processing (NLP) activities may be performed with it, including hate speech detection, which makes LSTM have advantages over other techniques, both in terms of long-term memory mechanisms. LSTM, also able to handle long and complex text sequences, capable of recognizing more complex patterns, able to understand and consider the context in the text, to recognize the meaning of a word or phrase in a broader context. Then, based on the dataset obtained from the Kaggle website with a total of 24783 data, then the dataset is divided into training data and validation data, with a ratio of training data to validation data. of 80%: 20%. Then, the testing step results in an accuracy value of 87.10%. © 2023 IEEE.

关键词： Speech recognition

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Survey of Online Exam Proctoring Model to Detect Cheating Behavior based on Face Recognition 8

Survey of Online Exam Proctoring Model to Detect Cheating Be...

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8th International Conference on Systems and Informatics, ICSAI 2022

作者： Rabiha, Sucianna Ghadati Kartowisastro, Iman Herwidiana Setiawan, Reina Budiharto, Widodo Bina Nusantara University Binus Graduate Program - Computer Science. Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Computer Science Department Binus Graduate Program - Computer Science Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665474481

Exams are an important component of any educational program, including online education. In any test, there is a possibility of cheating, so its detection and prevention is important. This study aims to conduct an in-depth study of the online exam monitoring model approach based on facial recognition used to detect cheating. Based on the inclusion and exclusion criteria designed, 13 selected studies were obtained. From these studies, we conducted further analysis regarding the Face Detection Method, Face Recognition Method, Initial Feature, Behavior Analysis and Evaluation Metrics used in each study so as to provide answers to research questions. the most frequently used Face detection method was Viola-Jones with a presentation of 20%, then CNN and MTCNN with a total presentation of 21%. The most widely used face recognition method in selected studies is CNN and metrics Accuracy is one of the most frequently used evaluations with a percentage of 33%. While the features that are usually used to detect cheating during online exams include facial motion and head pose which occupies the first position. The second is eye movement, then multiple faces gaze estimation and facial expression is in third place. Other features that also play a role in analyzing cheating behavior are mouth detection, facial vector, landmark location, gesture and posture. © 2022 IEEE.

关键词： Face recognition

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Air Pollution Level Prediction in Jakarta Using Artificial Neural Network 4

Air Pollution Level Prediction in Jakarta Using Artificial N...

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Ferdinan, Roger Margareta, Krestella Christyan, Stevan Anggreainy, Maria Susan Kurniawan, Afdhal School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11530 Indonesia

ISBN: (纸本)9798350318432

Air pollution has emerged as a critical issue in several major urban areas, including Jakarta. To address this problem, the study explores the utilization of the Artificial Neural Network (ANN) method. Three distinct approaches are investigated in this research: the Support Vector Classifier (SVC), Deep Artificial Neural Network (Deep ANN), and Long Short-Term Memory (LSTM). The available Air Quality data were utilized to train and assess the performance of the proposed ANN models. The research findings reveal that the Deep ANN model surpasses the other methods, achieving an impressive accuracy of approximately 96.57% and a cross-entropy value of 0.1103. In predicting air quality in Jakarta, Deep ANN has demonstrated superior performance when compared to SVC and LSTM. These results highlight the significant potential of deploying Deep Artificial Neural Network (ANN) methodologies for air quality prediction. Such an approach could play a pivotal role in the development of monitoring and early warning systems aimed at effectively addressing air quality issues in the Jakarta region. © 2023 IEEE.

关键词： Long short-term memory

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A literature review of crowd-counting system on convolutional neural network 2

A literature review of crowd-counting system on convolutiona...

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

作者： Chrysler, A. Gunarso, R. Puteri, T. Warnars, H.L.H.S. Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

With the proliferation usage of video surveillance for safety, traffic control, and privacy purposes and with the constant growth of population, it is important to keep monitoring using Closed-Circuit Television (CCTV). With new upcoming developed technologies, new systems and algorithms are introduced and implemented to the crowd counting system today retrieving live video surveillance from the CCTV. However, recent studies show that there are some challenges still faced regarding the crowd counting system which uses the density estimation. The problems that occurred have resulted from the inaccuracy of the system that is caused by several factors. Factors such as the perspective distortion which is caused by the lack of data training and the method such as face detection is an ineffective method to determine the population density. Studies proposed have projected the idea of developing a more robust crowd counting methodology by implementing crowd counting by detection, clustering, and regression. Implementing these methods using the Convolutional Neural Network (CNN) will better the result of the detection since in CNN the image can be inputted and it will undergo several layers which will result in the system being able to differentiate one image from the other. With CNN the process of crowd counting will be able to be more advanced. © Published under licence by IOP Publishing Ltd.

关键词： Face recognition

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Building Damage Assessment Using Deep Learning: Bibliometric Analysis 7

Building Damage Assessment Using Deep Learning: Bibliometric...

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7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Sidharta, Sidharta Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Soewito, Benfano Binus Graduated Program - Doctor of Computer Science Computer Science Department Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Natural catastrophes have become one of the hottest subjects as a result of the harm they have caused to human structures. In recent years, research pertaining to the discipline of building damage assessment (BDA), which seeks to study the effect of damage on structures, has grown substantially. This bibliometric study seeks to determine the state of the art in the subject of Building Damage Assessment Using Deep Learning by examining several papers. The method used (Donthu et al., 202) divides the steps of bibliometric analysis into four parts: identifying the field of research to be analyzed, identifying the methods used in bibliometric analysis, collecting research data with similar fields, and executing and analyzing the results of bibliometric analysis on the collected data. In the data collecting and analysis portion (Garza-Reyes, 2015), the identification of data search keywords, the execution of data searches, the enhancement of search results, statistical data processing, and data analysis are carried out. Several research questions pertaining to trends, influences, themes, authors, and other crucial components of doing research in the area of building damage assessment are answered using these techniques. The outcome is the mapping and resolution of all research problems, as well as the acquisition of bibliometric analysis-related data. The provided findings have been mapped into several types of visualization, including network % clustering graphs, overlay graphs, and density graphs, as well as other forms of visualization that will aid researchers in comprehending the study circumstances in the field. It is envisaged that this bibliometric study would make it simpler for scholars to do research in related topics. © 2022 IEEE.

关键词： Damage detection

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Foreign Exchange Prediction Using Machine Learning Approach: A Pilot Study 4

Foreign Exchange Prediction Using Machine Learning Approach:...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Sudimanto Heryadi, Yaya Lukas Wibowo, Antoni Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

ISBN: (纸本)9781665433945

Foreign Exchange or FOREX trading is not only done on foreign currencies but, FOREX also can be done on several commodities such as Gold, Silver, Oil. Gold is one of the most valuable commodities in the world. Investors began to offer gold as a trading material against foreign currencies. Machine Learning (ML) in the FOREX trading world is usually used to predict future FOREX values. This pilot study aims to see a model from machine learning that has a fairly high level of accuracy in making FOREX predictions. This pilot study using historical data taken from the *** database where the FOREX data taken is FOREX XAU/USD data, with a period year from 2019 until 2021, and the indicator used is Moving Average Convergence/Divergence (MACD) technical analysis. The average accuracy obtained after training on the Tree model is 86.3%, the Support Vector Machine (SVM) model is 86.6% and the Ensemble model is 86.55%. Testing conducted using machine learning models for Tree, SVM and Ensemble models have the same level of accuracy, which is 88.3%. © 2021 IEEE

关键词： Forecasting

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The Implementation of Isolated Geothermal Grid on the Community Cuisine Learning in Rural Area in North Sumatera 7

The Implementation of Isolated Geothermal Grid on the Commun...

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Gaol, Ford Lumban Meyliana Winanti Prabowo, Harjanto Hutagalung, Fonny Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Jalan Universiti Kuala Lumpur Wilayah Persekutuan50603 Malaysia

ISBN: (纸本)9781665404228

Hutajulu is a village of 450 households with a minigrid supplied solely by a 45kW geothermal system. The problems that happened is the very low performance of the grid interactions between energy use and grid operating practices when the areas are in the dry season. We also found that the weak. We use the approached with the Design Research that will adopt for modelling approached of the experiment on the Grid performance. The experiment results are shown that to reduce the consumption of the firewood for eight households, we adopt four types of electric cookstove that use the geothermal. We also investigate the interaction between the electric cookstove and the power system. We also found that The effects of the power system and the electric stoves on the cooking preferences is also revealed. © 2020 IEEE.

关键词： Electric stoves

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