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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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Leveraging Social Learning for Improved Cybersecurity Maturity: A Case Study Using the NIST Framework

Leveraging Social Learning for Improved Cybersecurity Maturi...

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Information Technology and Computing (ICITCOM), International Conference on

作者： Marcel Meyliana Harco Leslie Hendric Spits Warnars Tirta Nugraha Mursitama Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department Krida Wacana Christian University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Management Department BINUS Business School Doctor of Research in Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

This research shows that social learning can be used to increase an organization's cybersecurity maturity level. Using a literature study and case study approach. Literature studies are used to identify social learning's key success factors (KSF) and challenges in general. Then, the case study was performed in the context of assessing the maturity level of information security using the NIST Cybersecurity framework at ABC Software House, a small-scale software development company in Indonesia. Assessment activities are performed through FGDs which then also identify the most relevant social learning’ KSF to increase the organization's information security maturity level. Next, referring to the selected KSF, a process of identifying and mapping social learning’ challenges was carried out. The integration of social learning can help organizations gain better focus and understanding in nontechnical contexts to increase their maturity level. This research highlights that integrating social learning with the NIST cybersecurity framework can provide organizations with better focus and perspective for formulating non-technical solutions. This study also enriches the existing literature on social learning in cybersecurity and offers practical insights for organizations looking to improve their cybersecurity resilience.

关键词： Training Collaboration Information security NIST Software computer security Information technology Monitoring Software development management Resilience

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Automatic Heliostat Directing System Based On Microcontroller ESP32

Automatic Heliostat Directing System Based On Microcontrolle...

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International Conference on Electrical Engineering and Informatics, ICEEI

作者： Richard Medyanto Nicholas Sanjaya Suryadiputra Liawatimena Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta

Solar energy is one of the most abundant sources of renewable energy in Indonesia. Solar energy is now typically harnessed using solar panels, but the low efficiency of photovoltaic cells requires the development of other alternatives. The heliostat is a sunlight directing device with mirrors that can be used in a concentrated solar power system. Current heliostats require high capital investment due to their large frames and expensive components. This research was undertaken to develop a lower cost heliostat using a smaller frame, ESP32 microcontroller, servo motor and low-cost components. The position of the sun can be determined using an algorithm based on the National Oceanic and Atmospheric Administration (NOAA) solar calculator, and the mirror is moved to maintain the sun's reflection on a target. The result of this research is a set of heliostat prototypes consisting of the frame and control system. Tests were carried out to test the performance of the designed heliostat and it was found that the heliostat has an accuracy of about 60 cm and can raise temperatures up to 3.41°C. The conclusion is that the heliostat can be used in a concentrated solar power system to heat boilers in solar power towers.

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Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device

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Procedia computer science 2023年 227卷 1153-1162页

作者： Jason A. Wijaya Pauw D. Andersen Nico Surantha Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Electrical Electronic and Communication Engineering Tokyo City University Japan

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method.

关键词： sleep sleep quality actigraphy artificial intelligences fuzzy logic

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Artificial Intelligence-Driven Conceptual Framework to Generate Value from the Data in the Banking Industry: A Systematic Review

Artificial Intelligence-Driven Conceptual Framework to Gener...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Idha Kristiana Benny Ranti Ford Lumban Gaol Suhono Harso Supangkat Computer Science Department Doctor of Computer Science Binus University Jakarta Indonesia Computer Science Department Faculty of Computer Science Indonesia University Depok Indonesia Faculty of Digital Communications and Hotel & Tourism Institute of Technology Bandung Bandung Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

This paper presents a comprehensive analysis of an artificial intelligence-driven (AI-driven) conceptual framework to generate value from the data in the banking industry. The study provides a literature review to investigate the challenges of an AI-driven conceptual framework in the banking industry. Data quality management, data privacy and security, infrastructure capability, data governance and regulatory compliance, and talent and expertise have been identified as challenges. Based on a systematic review of the literature, this paper proposes Exploration, Classification, Protection, and Value (ECPV) and Explore, Understand, Act, and Engage (EUAE) as key parts of a conceptual framework driven by artificial intelligence to get value from data in the banking industry. The ECPV and EUAE address the identified challenges and offer a structured methodology for managing an AI-driven conceptual framework in the banking industry. It emphasizes the exploration of data sources, classification based on sensitivity and relevance, implementation of comprehensive data protection and privacy measures, and value extraction from data using artificial intelligence approaches. By using an AI-driven conceptual framework called Explore, Understand, Act, and Engage (EUAE) for customer-centric analytics, we give customers a full picture of their bank account activity and more control over how they manage their money. This improves customer engagement by giving customers insights and suggestions.

关键词： Industries Sensitivity Soft sensors Data integrity Data protection Banking Data governance Artificial intelligence Protection Systematic literature review

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Hoax Detection in Social Media: A Literature Review

Hoax Detection in Social Media: A Literature Review

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International Conference on Artificial Intelligence and Data sciences (AiDAS)

作者： Carsten Sebastian Saputra Norbert Wijaya Maria Susan Anggreainy Afdhal Kurniawan Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

For both print and digital media, the accuracy of the information has long been a problem that has impacted society and the business world. Information travels so quickly on social networks and is amplified that it can be skewed, false, or misleading. Inaccurate or incorrect information has great potential to affect millions of real-world users directly. Therefore, finding or getting accurate, trusted, and precise information becomes a problem. People start to spread fake news, which can cause certain events, such as mental disturbance, riots, and unnecessary anxiety. To prevent these problems, we will solve/research them with CountVectorizer and TF-IDF, which is what this study is all about (Discusses the detection of hoax news using CountVectorizer and TF-IDF). It was found that using these methods makes it possible to detect which words are most common in fake news and real news.

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Microservices Architecture As a Data Governance Tools in Decentralized E-Government

Microservices Architecture As a Data Governance Tools in Dec...

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2022 International Conference on science and Technology, ICOSTECH 2022

作者： Paramita, Adi Suryaputra Gaol, Ford Lomban Ranti, Benny Supangkat, Suhono Harso Graduate Program Universitas Ciputra Surabaya/ Bina Nusantara University Information Systems Department/Doctor of Computer Science Jakarta Surabaya Indonesia Bina Nusantara University Doctor of Computer Science Graduate Program Jakarta Indonesia Institute of Technology Bandung Systems and Information Technology Department Bandung Indonesia

ISBN: (纸本)9781665479851

Electronic government, or e-Government, is the use of information and communication technology by the public sector (ICT). Additionally, it can be viewed as a paradigm shift in terms of how governments operate. The government protects public values, while citizens act as problem solvers, co-creators, and active participants in value creation. On the other hand, decentralized systems have grown in popularity over the last few years. Data has become a significant issue in decentralized E-Government;each local entity has their own data, which is private. A suitable data governance tool is required to ensure that data governance is properly implemented and to prevent the organizational entity from leaking information. The purpose of this research is to examine the data governance tools mechanism utilizing microservices. © 2022 IEEE.

关键词： Information use

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Personalized Recommendation System for Online Learning: An Opportunity

Personalized Recommendation System for Online Learning: An O...

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International Conference on Business and Industrial Research (ICBIR)

作者： Dina Fitria Murad Mohamad Toha Hendra Mayatopani Bambang Dwi Wijanarko Yaya Heryadi Meta Amalya Dewi Riyan Leandros Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Universitas Terbuka Indonesia Department of Information Systems Pradita University Indonesia Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

In the world of education, learning management systems are currently widely used. The massively open online courses are accessible either via the web or mobile. The Learning Management System (LMS) is one of the learning media that is widely used today in online learning. An LMS with the use of a personalized recommendation system can provide items tailored to the interests and behavior of its users. Items in the recommendation system can be in the form of recommendations for learning models, ways of learning, learning patterns, or learning stages according to the characteristics and profile of the user. The purpose of this study is to identify opportunities for better online learning by utilizing a customized recommendation system based on the history of user interaction with the system, using several factors as determinants or variables. The method used is a review conducted from several stages. The result of this is knowing the factors that influence the user, and the opportunities that exist in the system recommendations on personalized development.

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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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Fostering Digital Innovation in Indonesia: The Role of STEM-AI Skills in Overcoming Talent Deficits and Gender Stereotypes

Fostering Digital Innovation in Indonesia: The Role of STEM-...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Erwin Halim Amalia Zahra Maryani Lili Ayu Wulandhari Devi Fitrianah Virienia Puspita Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Communication Department BINUS Graduate Program Master of Strategic Marketing Communication Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

This research explores the optimization of digital talent in advanced industries, particularly in the context of rapid digital transformation. Despite the increasing importance of digital talent for gaining a competitive edge, several challenges persist. In Indonesia, for example, there is a significant shortage of digitally skilled workers, with the World Bank reporting a gap of 9 million skilled individuals over the past 15 years. Additionally, artificial intelligence (AI) is expected to impact 9.5 million jobs, further exacerbating the demand for digital skills. Furthermore, the employability of graduates remains low, largely due to inadequate training, poor language proficiency, and limited cultural sensitivity. Many companies face difficulties in finding qualified individuals, quickly upskilling their workforce, and fostering an innovative organizational culture. This study seeks to evaluate the factors influencing digital talent performance in the context of these challenges. It examines seven key variables: digital readiness, digital technology adoption, relevance of AI, digital skills, individual performance, problem-solving ability, and overall digital talent performance. Hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data was collected from 378 participants, primarily students with STEM backgrounds, in the Jabodetabek area of Indonesia in November 2024. The findings reveal that all hypotheses are significant, with results indicating that user satisfaction and the perceived value of digital talent in Indonesia have a notable impact on continued usage intentions in digital roles.

关键词： Training Industries Technological innovation Sensitivity Mathematical models Problem-solving Artificial intelligence Optimization Faces Gender issues

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