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检索条件"机构=BINUS Graduate Program - Master of Computer Science Program"

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Snake and digital ladder applications involving the behavior of children applying the health protocols 2

Snake and digital ladder applications involving the behavior...

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2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Ariessanti, H.D. Gaol, F.L. Supangkat, S.H. Ranti, B. Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Esa Unggul University Jakarta11510 Indonesia

This study defines the problem of how understanding health protocols during a pandemic is correctly conveyed according to age levels. This problem for the Government to implement gamification by modifying game media through snake and ladder game that can socialize health protocols for pre-school. Measuring the acceptance of a snake and ladder game media can be considered as a learning medium from the Government which will refer to four components (game content, ease of play, appearance, and active player involvement). The purpose of this study was to modify online-based games as a learning media and to measure children's active interaction with parents in practicing health protocols during game play. This study will use a quantitative approach with data techniques through playing together experiments and filling in online research questionnaires from 115 samples as participants (7 Kindergartens). The results show that the snake and ladder digital game can have a significant effect on changes behavior in implementing health protocols. This research can provide a contribution that can be used as a reference for the Government to design a strategy for socialization through gamification. © Published under licence by IOP Publishing Ltd.

关键词： Health

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The Internet of Things: Real-Time Monitoring System for Production Machine 5

The Internet of Things: Real-Time Monitoring System for Prod...

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5th IEEE International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2021

作者： Tarigan, Masmur Heryadi, Yaya Lukas Wibowo, Antoni Suparta, Wayan Bina Nusantara University Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Department Jakarta Indonesia Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Faculty Of Computer Science Esa Unggul University Jakarta Indonesia

ISBN: (纸本)9781665401968

The importance of optimization in the manufacturing industry to achieve efficiency and effectiveness, especially in production machines. This research focuses on developing a real-time monitoring system based on the internet to monitor power consumption and production machines' speed accurately. The data taken by the real-time monitoring system is integrated into the ERP System, which is stored as time series data of power consumption and engine speed. The importance of making production cost estimates, especially on the power consumption of a production machine for the future, and functioning as a tool for real-time monitoring, the data obtained is processed by regression to get an estimate of the total power consumption for several expected outputs. The data is processed using a linear regression algorithm to predict power consumption at the desired speed on the intended production machine. To get a better tool than the one that existed before, the method in its development uses PIECES analysis. In its implementation, this real-time monitoring system runs according to the objectives, and the data obtained is as expected. This model was developed on production machines in the flexible packaging industry that uses rotogravure machines. It is possible that it can be used on production machines in other industries that use electrical power correlated with the speed measured based on the rotation of a motor. © 2021 IEEE.

关键词： Internet of things

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Identifying The Types and Platforms of the Metaverse – a Systematic Literature Review

Identifying The Types and Platforms of the Metaverse – a Sy...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Satrio Pradono Suryodiningrat Harjanto Prabowo Arief Ramadhan Harry Budi Santoso Computer Science BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Graduate Program Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia

Metaverse is gaining a lot of traction lately, especially after Mark Zuckerberg’s Facebook changed its name to Meta as a preparation to enter another universe called metaverse. The eXtended Reality (XR) technology is also rapidly growing since the birth of Virtual Reality (VR), followed by Augmented Reality (AR), and Mixed Reality is the latest development of XR technology. As the XR technology is the perfect companion to support the metaverse and the understanding of the metaverse is already clear but unfortunately, there is a lot of misconception about the types of the metaverse as well as the platform for each type. This paper aims to point out the types and platforms of the metaverse. 49 articles have been collected and reviewed carefully as a quality assessment process, and 45 articles have been selected for further review. This review informs everybody that there are many types and platforms of the metaverse nowadays.

关键词： Solid modeling Systematics Metaverse Extended reality Bibliographies Mixed reality Second Life

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Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter 6

Social Media Analysis using Sentiment Analysis on COVID-19 f...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Iqbal Maulana, Fairuz Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter. © 2022 IEEE.

关键词： COVID-19 python sentiment analysis social media twitter

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Optimizing Big Data Implementation to Create Business Value and Architecture Proposed in the Banking Industry: A Systematic Review

Optimizing Big Data Implementation to Create Business Value ...

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computer science, Information Technology and Engineering (ICCoSITE), International Conference on

作者： Idha Kristiana Meyliana Meyliana Achmad Nizar Hidayanto Harjanto Prabowo Computer Science Department Binus Graduate Program – Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia Management Departement BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

The exponential growth of data is compelling organizations to employ data in decision-making. As one of the businesses with an ecosystem that contributes to data growth, banks have challenges in generating insight. A high level of data security is frequently linked to a high level of data access difficulties. This poses a challenge to the implementation of data-driven business, where taking control of our data is one of the best ways to ensure that we not only own data but also have the ability to process and use data to extract business value. Through literature review, a number of challenges to optimizing the implementation of big data analytics in the banking industry were discovered. Data governance refers to the methods and procedures that assist banks in managing and securing data. A big data architecture is presented to address the highlighted issues, particularly with a multi-tiered approach to big data structures. With the adoption of this architecture, it will be simpler to generate business-value-generating insights for the banking industry using big data with accessibility and protection of data.

关键词： Industries Systematics Data security Bibliographies Process control computer architecture Banking

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Mobile application for paid road use for the reduction of traffic congestion 5

Mobile application for paid road use for the reduction of tr...

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5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021

作者： Harliano, Muhammad Rizqiko Afif, Mohammad Ramadhani, Hafiz Iwan, Tanto Harsono Koswara, Rian Warnars, Hareo Leslie Hendrie Spits School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665412728

Technology has evolved a lot in the last few years. E-toll becomes the only payment method available for highway roads, especially in Indonesia. This system of payment is expected to enhance the efficiency of payment from using the previous payment method. However, there are still some weaknesses addressed by the implementation of e-toll. It still takes time because the car's owner should tap the card first, and the sequence time between each person to tap is different. Thus, the queue results still long, and the traffic congestion on the highway road is not fully solved. This paper aims to address a better solution by adding a more efficient option of payment. So, traffic congestion is reduced and leads to better operation in toll gates. This research work has proposed a mobile application and route prediction model based on the Dijkstra Algorithm, where the price will be decided on which type of car will be passed by the gate, and the algorithm predicts the best possible routes based on the number of cars on the highway. Payment is conducted on the application using the balance from the application. This application eliminates time consumed during toll payment at any toll gate. © 2021 IEEE.

关键词： Smart city

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Using IT Balance Scorecard Analysis to Evaluate the Performance of Human Resource Information Systems in Corporation

Using IT Balance Scorecard Analysis to Evaluate the Performa...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Wahyu Sardjono Widhilaga Gia Perdana Erma Lusia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Postgraduate Program of Management Science State University of Jakarta Jakarta Indonesia Tourism Department Faculty of Economics & Communication Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

It is impossible to overestimate the critical significance that Human Resource Information Systems (HRIS) play in enabling Human Resource Management (HRM) operations using information technology to manage human resources within a business. This study uses the Exploratory Factor Analysis (EFA) methodology to evaluate the effectiveness of an HRIS in an Indonesian manufacturing organization. The IT Balanced Scorecard and HRM features are used in the research as essential tools. A survey was carried out with 185 employees who were using the HRIS program. The results identify four factors-poor information quality, information systems integration, application usability, and IT division support-that have a major impact on HRIS performance. Notably, the application system's usability turns out to be a significant factor influencing HRIS performance, yet the current HRIS application is widely criticized for its inadequate information quality. The results of this study contribute to the body of knowledge by indicating the possible efficacy of HRIS in industrial organizations under ideal circumstances. Moreover, the parameters that have been found can provide significant insights for enhancing HRIS effectiveness in future scenarios.

关键词： Surveys System performance Multimedia systems Human-robot interaction Organizations Manufacturing Usability Information technology Information systems Information integrity

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Aggregating Structural Features for Computational Analysis of Mutations in BRCT Domains of BRCA1 Protein

Aggregating Structural Features for Computational Analysis o...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Isnan, Mahmud Trinugroho, Joko Pebrianto Pardamean, Bens Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Binus Graduate Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Understanding the mechanistic interpretability of mutation effects in a protein can help predict the clinical implications of the genetic variants. Hence, computational variant effect predictions that involve protein structural features of the protein mutations might be suitable in this case. In this work, we focus on BRCT domains of BRCA1 gene that is widely studied in breast cancer studies. We retrieved 88 selected missense variants found in BRCT domains annotated in both ClinVar and gnomAD databases. To computationally characterize the pathogenic property of the mutations we used two types of features extracted from protein structures: a change in free Gibbs energy and a set of features derived from molecular dynamics simulations of each mutant. Using a dimensional reduction and Gaussian mixture model (GMM)-based clustering we demonstrate that the variants are segregated into two regions that may correspond to their pathogenic status. This method can be a potential computational pipeline for providing the preliminary mechanistic interpretation of mutation effects in terms of their thermodynamic and structural features. © 2023 IEEE.

关键词： Proteins

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Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems

Implementation of Face Patterns and Smile Recognition for In...

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International Conference of computer and Informatics Engineering (IC2IE)

作者： Miftakhurrokhmat Teddy Suparyanto Gregorius Natanael Elwirehardja Shofiyati Nur Karimah Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Students “attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students” attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification.

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Data Mining and Bioinformatics Approaches to Elucidate Bacterial Communities in the Extreme Environment

Data Mining and Bioinformatics Approaches to Elucidate Bacte...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Nirwantono, Rudi Asadi, Faisal Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Bacteria are microscopic organisms that can be found in many environments. They are abundant and have many roles in our life. Studying bacteria is essential so that we can identify the bacteria that are needed for many industrial applications. However, the main problem is that majority of the bacteria are unculturable, hampering the exploration of bacteria from different environments. Metagenomics approach which employs Next Generation Sequencing technology could help study bacteria by utilizing 16S rRNA marker gene. This study aims to demonstrate data mining and bioinformatics approaches to analyze 16S rRNA sequencing data. The raw sequencing data of 16S rRNA was collected from biological database. Then, the data were trimmed, denoised, and clustered to generate Amplicon Sequence Variants (ASVs). Diversity (alpha and beta) and taxonomic analyses were then conducted to elucidate the bacterial diversity and taxonomic profile of ASVs. The results of this work showed that Shannon and PD indices in China's hot spring were higher than Singapore and the USA. Furthermore, a significant difference was observed in the PD index. The unweighted UniFrac distance also showed there was a significant difference of the bacterial communities between the three locations. In addition, the taxonomic investigation unveiled prevalent bacterial groups in the ecosystem, namely Proteobacteria, Chloroflexi, Cyanobacteria, and Crenarchaeota. The research outcomes have the potential to serve as a foundational resource for subsequent bacterial metagenomic research, particularly the hot spring environment. © 2023 IEEE.

关键词： Bacteria

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