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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Susanti, Meilia Nur Indah Ramadhan, Arief Warnars, Harco Leslie Hendric Spit Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Currently, Indonesia and the whole world are being hit by the Covid-19 pandemic which has an impact on various fields of life. It affects all sectors, including the education sector. The government through the Ministry of Education and Culture makes a policy in education in terms of the learning process. Teaching and learning activities that were initially carried out face to face become distance learning which was carried out at home. In this study, a systematic literature review is conducted on automatic assessment of essay answers. Various previous studies discuss the essay answer scoring system that has been developed using various methods. We synthesize the results to enrich our understanding of the automated essay exam scoring system. The expected result of this research is that it can contribute to further research related to the automated essay exam scoring system, especially in terms of considering methods and dataset forms. © 2022 Elsevier B.V.. All rights reserved.

关键词： Distance education

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UML Design for Decision Support Model in Determining the Sustainability of Online Course Materials 6

UML Design for Decision Support Model in Determining the Sus...

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

作者： Sihotang, Erna Fransisca Angela Kurniawan, Afdhal Utama, Ditdit Nugeraha Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

The scenario of online learning is a very urgent need in the world of future knowledge. Since the Corona Virus Disease-19 pandemic, the world economy has started to plummet and caused many adults to lose their jobs. The advantage is the flexibility and rapid development of the internet. In 2020, the number of unemployed increased significantly. This reason makes people strive to improve their ability to meet job requirements by taking online courses. Online courses are a way that people can choose to improve their skills anywhere and anytime. The sustainability of online course material that is offered to the course user and issued by the company will be discussed in this study. The novelty of this research is to obtain a decision support model based on fuzzy logic for determining online courses. The method used is decision-making based on UML and fuzzy logic for the final decision. The fuzzy inference model process begins by determining the decision parameters then using fuzzification with absolute input then refracted with fuzzy criteria, and ends with defuzzification with absolute output. There are two groups of parameters in this study, company profits which consist of 5 parameters and user benefits, which consist of 9 parameters. Once the model is verified and valid, the final decision is useful for users looking for online course and also useful for the decision unit of online course companies in determining the sustainability of online course materials. © 2022 IEEE.

关键词： Decision support model fuzzy logic online course UML

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The Use of Deep and Machine Learning for Face Expression Recognition: A Literature Review 7

The Use of Deep and Machine Learning for Face Expression Rec...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Pangestu, Gusti Hendric Spits Warnars, Harco Leslie Soewito, Benfano Gaol, Ford Lumban BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

In the current era, Artificial Intelligence (AI) and computer Vision take the main role and participating to the people daily activities. Face Expression became as interesting topic to be explore. Face expression recognition or detection could be applied in many aspects, such as for student focus detection based on face expression, intruder detection system, lie detection and many more. Referring the useful of face expression detection, there are also much research that focused on the methodology to detects or recognize the face expression. Several approaches are use such by using Deep Learning, Machine Learning and statistical method. This paper focused on the process to obtain and knowing the best approach or methods to recognize the face expression by using Systematic Literature Review (SLR) process. From hundreds of retrieved papers with similar interest, we do the selection based on the interest, scope, and topic similarity. The process keeps repeating until we found papers that has similarity criteria in output, dataset, subject and the methods. There are 6 papers in total that fulfil our requirements based on subject, output, result and methods. Subsequently, every research paper was deep-reviewed and compared with another to find the best approaches proposed and dataset used. © 2022 IEEE.

关键词： Intrusion detection

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Optimized LightGCN for Music Recommendation Satisfaction 6

Optimized LightGCN for Music Recommendation Satisfaction

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

作者： Hansel, Aaron Christian Adrianus Pradana, Lunardi Suganda, Abba Girsang Nugroho, Ariadi Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

With the large amount of information available on the internet, recommendation tasks have grown to be more crucial than ever. Businesses that store digital media on the internet such as video streaming and music streaming platforms, benefit a lot from recommendation systems. A simple yet powerful recommendation system that can give better recommendation performance is always being sought after. Light Graph Convolution Network (LightGCN) is a simplified version of Graph Convolution Network (GCN) for collaborative filtering in recommendation systems. LightGCN architecture includes only the most essential part of GCN for collaborative filtering that is the neighborhood aggregation, it removes the feature transformation and nonlinear activation because both of them contribute little to no effect to the recommendations. The focus of this research is to optimize LightGCN by tuning the hyperparameters using exhaustive search (grid search). The optimized LightGCN model is able to out-perform LightGCN by more than 140% in music recommendation © 2022 IEEE.

关键词： exhaustive search hyperparameter tuning LightGCN music recommendation Recommendation system

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Gender-Based Bimodal Analysis of Speech and Text in Non-Contextual Emotion Recognition

Gender-Based Bimodal Analysis of Speech and Text in Non-Cont...

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2024 Beyond Technology Summit on Informatics International Conference, BTS-I2C 2024

作者： Angkasa, Abby Rasya Zahra, Amalia Fung, Wai-Keung Binus Graduate Program Computer Science Department Jakarta11480 Indonesia Cardiff Metropolitan University Cardiff School of Technologies Engineering Department Cardiff United Kingdom

ISBN: (纸本)9798331508579

Emotion recognition can help human-computer interactions by enabling systems to respond empathetically and adapt to users' emotional conditions. This capability improves user experience, supporting the development of a more intuitive and emotionally responsive communication system. This study analyzes a bimodal approach based on gender (male and female) to recognize emotions without contextual information in dialogue analysis. Utilizing the Multimodal EmoryNLP dataset extracted from the TV series Friends with acted speech, we focused on four primary emotions: Angry, Neutral, Joy, and Scared. The model used in this study for text classification is RoBERTa, and wav2vec 2.0 is used for audio feature extraction with the Bi-LSTM model for classification. The experiment results using weighted F1-score reveal that data augmentation enhanced the performance of analyzing the original dataset from 0.46% to 0.52% and the male dataset from 0.43% to 0.51 %. In comparison, the female dataset remained consistent at 0.46%. The weighted F1-score and Unweighted Averaged Recall (UAR) from the male dataset are higher, 51 % and 48%, respectively, than those from the female dataset, 46% and 47%, respectively. Gender-based analysis indicated that male and female datasets exhibited distinct performance patterns, highlighting variations in emotional expression and recognition between genders. These findings underscore the effectiveness of multimodal strategies in emotion recognition and suggest that gender-specific factors play a significant role in enhancing classification performance. While these results highlight performance trends, further validation through repeated trials and statistical analyses could provide stronger generalizations and insights into gender-based differences. © 2024 IEEE.

关键词： Emotion Recognition

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Website and Mobile Based Application Utilization to Increase & Upscale MunchUp Selling Margin 10

Website and Mobile Based Application Utilization to Increase...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Putra W, Muhammad Faadhil Pramono, Andi Gabriella, Jerica Zahirah, Avicena Zalfa Rosalinda, Elina Purnomo, Agung School of Computer Science Bina Nusantara University Computer Science Computer Science Department Jakarta11480 Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339543

Indonesia's Food and Beverage (F&B) development is increasing rapidly every day. Our surroundings demonstrate that more and more food and beverage items, particularly light snacks, are being sold. As a result, the company's chances of connecting with a potential customer are indirectly reduced as market competition in the F &B industry heats up. To solve this problem, MunchUp, which specializes in selling light snacks F &B, tries to fully shift its marketing strategy to utilize the latest technology. The technology that MunchUp uses is a website and mobile-based applications. This research aims to investigate the impact of website and mobile app usage on the selling margin of a business. The study was conducted by analyzing sales data from a sample of the companies that have implemented a website and mobile app for their sales process. The study results indicate that businesses with a website and mobile app have seen an increase in their selling margin compared to companies that do not have a website and mobile app. The study also found that features such as push notifications, loyalty programs, and personalized recommendations can help keep customers engaged and encourage repeat purchases. This research suggests that a well-designed and user-friendly website and mobile app can be a powerful tool for any business looking to boost its sales and increase its revenue. © 2023 IEEE.

关键词： Websites

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Investigation of player emotion and instinct on racing video game using 6-11 framework (Case study: split second (2010) single player modes)

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Procedia computer science 2024年 245卷 87-99页

作者： Galih Dea Pratama Andien Dwi Novika Elshad Ryan Ardiyanto Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Master of Computer Science Binus Graduate Program Bina Nusantara University Jakarta 11480 Indonesia

Racing is one of the most prominent genres in the modern video game industry, where the games within the genre enable players to use any vehicle of their choice and win through doing series of action within gameplay. Thus, it made the genre popular over the years, spawning many famous titles such as Split Second back in 2010. Like every other video game title, Split Second also invokes the player emotion and instinct during its gameplay session. To understand the emotion and instinct aspect present in players of the game, we will use 6-11 framework which focuses on the two aspects. As part of the conclusion, Split Second game involves instincts such as Competition, Collecting, and Survival, with emotions including Fear, Pride, Joy, and Excitement, which can be found from its vast single player game modes.

关键词： video games racing video games game analysis 6-11 framework

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One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion 8

One Policy to Run Them All: an End-to-end Learning Approach ...

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8th Conference on Robot Learning, CoRL 2024

作者： Bohlinger, Nico Czechmanowski, Grzegorz Krupka, Maciej Kicki, Piotr Walas, Krzysztof Peters, Jan Tateo, Davide Department of Computer Science Technical University of Darmstadt Germany Institute of Robotics and Machine Intelligence Poznan University of Technology Poland Research Department: Systems AI for Robot Learning Germany IDEAS NCBR Warsaw Poland Hessian.AI Germany Centre for Cognitive Science Germany

Deep Reinforcement Learning techniques are achieving state-of-the-art results in robust legged locomotion. While there exists a wide variety of legged platforms such as quadruped, humanoids, and hexapods, the field is still missing a single learning framework that can control all these different embodiments easily and effectively and possibly transfer, zero or few-shot, to unseen robot embodiments. We introduce URMA, the Unified Robot Morphology Architecture, to close this gap. Our framework brings the end-to-end Multi-Task Reinforcement Learning approach to the realm of legged robots, enabling the learned policy to control any type of robot morphology. The key idea of our method is to allow the network to learn an abstract locomotion controller that can be seamlessly shared between embodiments thanks to our morphology-agnostic encoders and decoders. This flexible architecture can be seen as a potential first step in building a foundation model for legged robot locomotion. Our experiments show that URMA can learn a locomotion policy on multiple embodiments that can be easily transferred to unseen robot platforms in simulation and the real world. © 2024 Proceedings of Machine Learning Research.

关键词： Deep reinforcement learning

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Validity and Reliability of Persian Version of Cyber-Bullying /Victimization Experience Questionnaire (CBVEQ) Among Iranian Adolescents

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International Journal of Bullying Prevention 2024年 1-12页

作者： Nooripour, Roghieh Hosseinian, Simin Ghanbari, Nikzad Wisniewski, Pamela Sikström, Sverker Department of Counseling Faculty of Education and Psychology Alzahra University Tehran Iran Faculty of Education and Psychology Shahid Beheshti University (SBU) Tehran Iran Department of Computer Science Faculty Fellow Flowers Family in Engineering Vanderbilt University Nashville United States Cognitive Psychology Chair of the Cognitive Division Department of Psychology Lund University Lund Sweden

This study aimed to measure validity and reliability of the Persian version of the Cyber-Bullying/Victimization Experience Questionnaire (CBVEQ) among Iranian adolescents. This cross-sectional validation study was conducted on Iranian adolescents between January 2022 and September 2022. Online questionnaires were completed by a total of 1439 Iranian high school students, with an age range of 14–18 years (M = 15.93 years, SD = 1.43). Participants completed Cyber-Bullying/Victimization Experience Questionnaire (CBVEQ), Online Disinhibition, Sensation Seeking, Empathy, and School Connectedness questionnaires. The validity and reliability of the CBVEQ were assessed through measures including Cronbach's alpha, construct validity via Confirmatory Factor Analysis (CFA), and evaluations of divergent and convergent validity. The CFA indicated that a two-factor model provides a good fit for the data: (_sbX² = 3011.31 (p < 0.01);SRMR = 0.06;CFI = 0.96;NFI = 0.96;IFI = 0.96;PNFI = 0.86;GFI = 0.83;RMSEA = 0.088). Cronbach’s alpha coefficient for the self-escapism was 0.89. There was a significant positive relationship between CBVEQ with online disinhibition (r = 0.47;P < 0.01) and sensation seeking (r = 0.44;P < 0.01). The finding showed significant negative relationship between CBVEQ score with school connectedness (SC) (r = -0.35;P < 0.01), and empathy (r = -0.42;P < 0.01). In addition, the findings have shown a relationship between CBVEQ and maternal educational status. Iranian researchers and specialists can use this scale for research or assessment purposes in Iranian adolescents to expand the existing knowledge about preventing and reducing cyberbullying. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Adolescent Cyber Bullying Cyber Victimization Measurement Validity

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One system for learning and remembering episodes and rules

arXiv

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arXiv 2024年

作者： Hewson, Joshua T.S. Sloman, Sabina J. Dubova, Marina Department of Cognitive Linguistic and Psychological Sciences Brown University ProvidenceRI United States Department of Computer Science University of Manchester Manchester United Kingdom Cognitive Science Program Indiana University BloomingtonIN United States

Humans can learn individual episodes and generalizable rules and also successfully retain both kinds of acquired knowledge over time. In the cognitive science literature, (1) learning individual episodes and rules and (2) learning and remembering are often both conceptualized as competing processes that necessitate separate, complementary learning systems. Inspired by recent research in statistical learning, we challenge these trade-offs, hypothesizing that they arise from capacity limitations rather than from the inherent incompatibility of the underlying cognitive processes. Using an associative learning task, we show that one system with excess representational capacity can learn and remember both episodes and rules. © 2024, CC BY.

关键词： Learning systems

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