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Machine Learning Approaches in Detecting Autism Spectrum Disorder 8

Machine Learning Approaches in Detecting Autism Spectrum Dis...

引用

8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Daniel Dominic, Nicholas Cenggoro, Tjeng Wawan Pardamean, Bens Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Early detection of Autism Spectrum Disorder (ASD) needs to be increased to prevent further adverse impacts. Thus, the classification between ASD and Typically Development (TD) individuals is an intriguing task. This review study has collected 26 related papers to answer four research questions, i.e., what are the most used data inputs, brain atlases, and machine learning models for ASD classification, as also to discover the significant parts of the brain correlated with the ASD. It was eventually found that functional connectivity matrix, Support Vector Machine, and CC200 are the most frequently used data input, model, and brain atlas, respectively. Researchers also concluded that the posterior temporal fusiform cortex, intracalcarine cortex, cuneal cortex, subcallosal cortex, occipital pole, and lateral occipital cortex are the brain regions highly correlated with ASD. © 2023 The Authors. Published by Elsevier B.V.

关键词： autism spectrum disorder brain atlas brain region machine learning

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Dual Word Embedding Framework for Gender-Based Writing Style Analysis Using Word2Vec and BERT

Dual Word Embedding Framework for Gender-Based Writing Style...

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Informatics International Conference (BTS-I2C), Beyond Technology Summit on

作者： Aditya Riyanto Amalia Zahra Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331508579

ISBN: (纸本)9798331508586

Social media has evolved into a vast and multifaceted data repository, presenting valuable opportunities to investigate gender-based variations in writing styles. This study aims to enhance the precision of gender classification on Twitter text by leveraging a combined word embedding approach. The paper proposes a framework that utilizes two distinct word embedding models - a combination of GloVe and BERT, as well as GloVe and Word2Vec - to capture both global and contextual linguistic nuances within the text. The dataset comprises a comprehensive collection of tweets and user profile descriptions harvested from Twitter, which underwent meticulous preprocessing and word representation steps before being further processed using the robust Random Forest algorithm. The experimental findings indicate that the combination of GloVe and BERT outperforms the other combination of GloVe and Word2Vec, and also surpasses the performance of single embedding models, with 62.93% accuracy being the highest achieved result. This study provides valuable insights into the potential of combined word embedding techniques for enhancing the accuracy of gender classification in social media text analysis.

关键词： Biometrics Text analysis Accuracy Social networking (online) Blogs Supervised learning Writing Linguistics Natural language processing Random forests

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The Learning Outcomes Achievement and User Experience Analysis of a Cryptography Education Web Game

The Learning Outcomes Achievement and User Experience Analys...

引用

HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Helmi Yusuf Susanto Yulyani Arifin Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350380439

ISBN: (纸本)9798350380446

The rising threat of cybercrimes in Indonesia, including a significant breach of the national data center, reveals the urgent need for effective cybersecurity education. Cryptography, a key component of cybersecurity, is often difficult for beginners to grasp. To address this, we developed an interactive web game that blends puzzle-solving with a visual novel to make cryptographic concepts more accessible. This study analyzes the game’s user experience (UX) using the ARCS model—Attention, Relevance, Confidence, Satisfaction—and assesses learning outcomes by comparing pre-test and post-test results. The findings show significant improvements in participants’ understanding and high levels of engagement, demonstrating a strong correlation between positive user experience and enhanced learning outcomes. However, some aspects of the educational content still need refinement. Future updates will offer multilingual support and personalized learning paths, with pre-and post-tests targeting specific cryptography and cybersecurity sub concepts, and analysis of UX features through targeted surveys and in-game analytics to enhance learning experiences.

关键词： Surveys Visualization Analytical models Data centers Correlation Education Games User experience Multilingual Cryptography

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An Object-Driven Fuzzy Decision Model for Determining Fuel in Boiler Machines

An Object-Driven Fuzzy Decision Model for Determining Fuel i...

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

作者： Ditdit Nugeraha Utama Jeremia Widyanto Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

There are many alternative fuel types that can be used by a particular type of engine. Determining which fuel alternative is optimal for an engine presents its own challenges. This is especially true in an industrial setting, where certain standards are necessary to select the best fuel alternative to be used and operated. This study aims to develop a decision model for selecting a fuel type for boiler engines based on specific parameters or criteria. The decision model is designed using an object-oriented approach, utilizing three types of diagrams: object, activity, and sequence. An object-oriented model design approach allows for the decision model to be depicted transparently and very close to reality. Additionally, the analytical hierarchical process (AHP) and fuzzy logic are the core methods employed in constructing the decision model. Then, in developing this decision model, four main criteria or parameters are considered: cost, heating value, safety, and emissions. These four parameters were derived from a literature review and interviews with experts. Among the three evaluated fuel types (i.e., natural gas, industrial diesel oil or IDO, and coal), coal received the highest decision score of 0.78. Thus, based on this decision value―the outcome of the model's recommendation―it can be concluded that coal remains an objective choice as a fuel for use in boiler engines.

关键词： Fuzzy logic Object oriented modeling Oils Coal Analytic hierarchy process Boilers Safety Engines Standards Systematic literature review

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Object Driven Fuzzy Decision Model for Evaluating the Cryptocurrency's Performance

Object Driven Fuzzy Decision Model for Evaluating the Crypto...

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International Conference on ICT For Smart Society (ICISS)

作者： Ditdit Nugeraha Utama Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

The assessment of cryptocurrency performance has been subject to criticism due to the lack of a standardized approach, leaving the evaluation process without clear guidance. In this research, an innovative object-driven decision model based on fuzzy logic (OFDM) conception was developed to systematically analyze cryptocurrency performance. Object-oriented operated as the main method in analyzing and designing the model. In this context, the model elements deeply observed and functioned to become fundamental thinking for constructing the model. Then, fuzzy logic with curve membership function form was also used as the primary method to avoid the bias value of three key parameters; trend line (and then used to see the slope distance), price consistency, and transaction volume consistency. The constructed model is a novel decision model that was successfully constructed for assessing the determined cryptocurrency performance. Utilizing six months of real data from three major cryptocurrencies (Bitcoin, Ethereum, and Dogecoin), the model conclusively demonstrates that Bitcoin exhibits the strongest performance, scoring 36.39 performance points.

关键词： Fuzzy logic Analytical models Object oriented modeling OFDM Bitcoin Market research Data models Context modeling

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Object-Driven Fuzzy Decision Model for Assessing the Employees' Work from Home Eligibility

Object-Driven Fuzzy Decision Model for Assessing the Employe...

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

作者： Ditdit Nugeraha Utama Christiawan Immanuel Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

Work from Home (WFH), especially in the post-pandemic era, has emerged as an alternative work system adopted by many companies. Efficiency and effectiveness are the two main reasons why WFH is favored. In addition, the implementation of the WFH system in conducting business processes within the company allows for greater flexibility in work methods. For certain types of jobs or specific industry domains, this WFH system can be quite reliable. Workers can perform their tasks from anywhere and at any time. Also, monitoring systems enable employees to be remotely tracked by the company. However, the question remains: is an employee's work environment suitable enough to ensure the successful implementation of WFH? To answer this, a standardized model is needed to assess the level of eligibility for WFH implementation. This study aims to develop a fuzzy-based decision model to evaluate the eligibility of an employee's work environment for implementing WFH. An object-oriented approach is used to describe the design of the decision model, while fuzzy logic serves as the primary method for building the model. The model successfully simulated 24 raw employee data points, yielding a highest eligibility score of 88.61 with a similarity index of 0.78 when compared to the model proposed in previous research.

关键词： Industries Fuzzy logic Object oriented modeling Buildings Companies Data models Reliability Monitoring Business

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Virality Prediction on Twitter Using Combined CNN and BERT Models

Virality Prediction on Twitter Using Combined CNN and BERT M...

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

作者： Hilarius Ryan Auxilio Benedecas Abba Suganda Girsang Computer Science Department Binus Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

Nowadays, social media serves as a platform for sharing and receiving information. One indicator of the importance of information is its virality. Virality is an interesting topic in the world of Natural Language Processing (NLP), including the prediction of virality and identifying features that influence it. Research in this area has utilized Bidirectional Encoder Representations from Transformers (BERT) models and yielded promising results. Previous studies aimed to predict virality based on specific features. This research aims to predict virality by combining the abilities of Convolutional Neural Network (CNN) and BERT models. The BERT model transforms textual data into numerical and adds new features, while the CNN model excels in numerical classification. Data for this study is sourced from Twitter and in Indonesian language. The proposed model demonstrates improvements compared to the model from previous research. Specifically, it shows a 7.1% increase in precision, a 9.9% increase in recall, a 3.8% increase in accuracy, and an 8.1% increase in F1-Score compared to the previous model. These findings contribute to future research on similar topics, particularly in leveraging multiple models for prediction tasks. Overall, the study provides insights into effectively utilizing the strengths of various models and combining them in prediction tasks.

关键词： Measurement Social networking (online) Blogs Bidirectional control Predictive models Encoding Data models Natural language processing Numerical models Convolutional neural networks

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Immersive Learning in Using the Metaverse of Satellite Communication Systems science 9

Immersive Learning in Using the Metaverse of Satellite Commu...

引用

9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Akbar, Komputerio Meyliana Warnars, Harco Leslie Hendric Spits Jayadi, Riyanto Binus Graduate Program Bina Nusantara University Computer Science Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta Indonesia Binus Graduate Program Bina Nusantara University Information Systems Management Department Jakarta Indonesia

ISBN: (纸本)9798350383010

Education stands out as one of the most impactful applications of the metaverse, holding immense potential for the future. Within the realm of satellite communication system science education, the integration of immersive learning through the metaverse adds a layer of interest and interactivity to the teaching and learning process. Numerous design and evaluation techniques have been employed in a growing body of research, aiming to understand how immersive learning via the metaverse can effectively contribute to specific educational objectives. Hence, this research is dedicated to delving into the development of an immersive learning metaverse model for the science of satellite communication systems. The research contributes a model that advocates for a holistic learning approach by integrating metaverse technology, VR, the 6E Instructional Process Model, and the MSLQ evaluation instrument. The objective of this model is to enhance the efficiency, effectiveness, and interactivity of learning within the field of satellite communication systems science. © 2024 IEEE.

关键词： Satellite communication systems

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An Object-Oriented Fuzzy-AHP Decision Model for Education: A Generic Decision Model Based on Bibliometric Driven Review

An Object-Oriented Fuzzy-AHP Decision Model for Education: A...

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Technology & Engineering Management Conference - Asia Pacific (TEMSCON-ASPAC), IEEE

作者： Ditdit Nugeraha Utama Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331515881

ISBN: (纸本)9798331515898

The challenges in the education sector are extensive, encompassing issues such as human resource selection, technology choice, and business procedure assessment. To address these challenges both academically and practically, decision models can be effectively utilized. This study aims to conduct a bibliometric review to examine the trends in the use of fuzzy logic and identify popular methods combined with fuzzy logic in the development and implementation of decision models in educational contexts. The review results were then used to design a generic education decision model using an object-oriented approach. Based on the analysis of 165 selected articles from the past decade and an in-depth review of 10 articles, the study found that the use of fuzzy logic is growing rapidly, following a tight exponential trend. Additionally, the analytic hierarchy process (AHP) is frequently united with fuzzy logic in developing decision models. Consequently, an object-oriented decision model was designed, featuring 2 decision model blocks (i.e. selection and evaluation), 7 main objects, 9 use cases, and 5 human actors.

关键词： Fuzzy logic Object oriented modeling Education Bibliometrics Asia Analytic hierarchy process Market research Systematic literature review Context modeling Business

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The Fuzzy-AHP Decision Model for Managing Smart City: An Object-Oriented Model for Bibliometric Based Literature Review

The Fuzzy-AHP Decision Model for Managing Smart City: An Obj...

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International Conference on ICT For Smart Society (ICISS)

作者： Ditdit Nugeraha Utama Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Operating a smart city is intricate and requires comprehensive management. Implementing a decision model is one effective and efficient method to address this complexity. This study seeks to systematically review articles to see the trends in the utilization of fuzzy logic methods and their combinations, particularly in a decision model that supports smart city operations. Through four stages, the study not only presents the bibliometric-based review findings to address specific inquiries but also produces an object-oriented model for review purposes. Based on 131 articles, the research trend indicates a linear growth in studies focusing on smart cities and decision models, with a particular emphasis on incorporating fuzzy logic models. Additionally, according to 9 deep-reviewed articles, the analytic hierarchy process (AHP) emerges as a popular method often combined with the fuzzy logic method. As well, the object-oriented model for review purposes is developed with 19 interrelated objects. It is the main contribution of the study.

关键词： Fuzzy logic Analytical models Smart cities Reviews Object oriented modeling Bibliographies Bibliometrics Focusing Market research Complexity theory

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