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检索条件"机构=Computer Program"

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Parallelization of LSTM-GRU Architectures for Multivariate Prediction of Stock Prices 9

Parallelization of LSTM-GRU Architectures for Multivariate P...

引用

9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Tarigan, Gabriel Asael Hermawan, Eric Girsang, Abba Suganda Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Anticipating stock market movements is challenging, as hasty prediction risks large financial losses. Stock price prediction is complex due to the high volatility and many influencing external factors. Recurrent Neural Network (RNN) models are made to learn time series data making it ideal for stock prediction based on records. Well-known RNN architectures for forecasting problems are Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). However, past studies only explored standalone models and have not generated convincing performance results. By integrating the efficiency of GRU to effectively handle shorter data sequences with LSTM's ability to capture long-term dependencies, our model aims to improve stock price forecasting accuracy by collaborating the strength between both architectures. The proposed model was used to forecast multivariate stock prices and evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). We found that parallelization of LSTM-GRU offers better prediction, up to 9.1% improvement compared to sequential LSTM-GRU and Bidirectional LSTM (Bi-LSTM). © 2024 IEEE.

关键词： Mean square error

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Implementation of Light Gradient Boosting Machine (LGBM) for Customer Services Feedback Classification 5

Implementation of Light Gradient Boosting Machine (LGBM) for...

引用

5th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2024

作者： Anggreainy, Maria Susan Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11530 Indonesia

ISBN: (纸本)9798331528553

Customer complaints are an important aspect in the business world. Every company must face complaints from its customers, whether related to unsatisfactory products, services or experiences. Customer complaints are a sign of unmet needs or expectations. A customer service person is tasked with serving questions asked by customers or consumers. The purpose of this research is to classify types of complaints to help customer service. The classification carried out is in binary form, namely disputed or not. This research compares several machine learning algorithms for classification of customer questions into appropriate categories for more efficient responses. Based on evaluation metrics, the F1 Score light gradient boosting machine (LGBM) is the best model compared to Multinomial Naive Bayes (MNB), Logistic Regression (LR), SVM (Support Vector Machine), and EXTC (Extra Tree Classifier). © 2024 IEEE.

关键词： Sales

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The Fuzzy-AHP Decision Model for Managing Smart City: An Object-Oriented Model for Bibliometric Based Literature Review 11

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

引用

11th International Conference on ICT for Smart Society, ICISS 2024

作者： Utama, Ditdit Nugeraha Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350389654

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. © 2024 IEEE.

关键词： Smart city

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Object Driven Fuzzy Decision Model for Evaluating the Cryptocurrency's Performance 11

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

引用

11th International Conference on ICT for Smart Society, ICISS 2024

作者： Utama, Ditdit Nugeraha Binus Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350389654

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. © 2024 IEEE.

关键词： Fuzzy logic

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Automated Adversarial-Attack Removal with SafetyNet Using ADGIT 10

Automated Adversarial-Attack Removal with SafetyNet Using AD...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Halim, Steven Anandi, Arvio Devin, Vyos Agung Santoso Gunawan, Alexander Eka Setiawan, Karli School of Computer Science Bina Nusantara University Data Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350363104

In the realm of artificial intelligence (AI), a notable challenge has surfaced: adversarial attacks, these attacks involve altering input data to mislead AI models. Developing defensive measures against adversarial attacks is necessary for a more reliable AI system to protect its users from potential harm. In response to the risk of adversarial attacks, this study aims to mitigate the risk of such attacks, especially in image classification tasks, by proposing Adversarial Detection Guided Input Transformation (ADGIT) as an architecture designed to handle such attacks. In this study, the author will experiment with creating such architecture and measure the quality of the proposed technique. ADGIT works by utilizing SafetyNet as an adversarial detector to detect and cleanse adversarial attacks. The author concludes that the proposed technique could improve robustness against adversarial attacks increasing consistent prediction accuracy from 43% to 60% and reconstructing adversarial input images to be more similar to their unperturbed version, with reconstructed images' PSNR score on 0.007 perturbation increased from 43.1182 to 89.0999. The technique proposed could be used as a new defensive measure and improving robustness against adversarial attacks. Although ADGIT is capable of handling adversarial samples, ADGIT has a drawback in performance speed due to the extra preprocessing step. © 2024 IEEE.

关键词： Adversarial machine learning

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E-commerce Security Issues for SMEs: A Systematic Literature Review 7th

E-commerce Security Issues for SMEs: A Systematic Literature...

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7th International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2022

作者： Gunawan, Zaldy Abdurachman, Edi Soewito, Benfano Gaol, Ford Lumban Computer Science Department BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819950140

Significant advancements in information technology have altered existing markets, transforming them from physical to online electronic markets (e-commerce). The practice of conducting business online by smaller and medium-sized companies has received encouragement and assistance from governments all around the world, particularly those of developing nations. With the evolution of e-commerce, businesses must find a better way to implement e-commerce while maintaining its security. The purpose of this article is to carry out a Systematic Literature Review (SLR) in order to determine the types of vulnerabilities that are present in e-commerce platforms used by SMEs. As a result, in the conclusion, security issues and recommended solutions related to e-commerce systems for SMEs will be presented. These outcomes can serve as a foundation for further study on e-commerce security issues, such as solutions and recommendations for providing a secure e-commerce system for SMEs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electronic commerce

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The Learning Outcomes Achievement and User Experience Analysis of a Cryptography Education Web Game 10

The Learning Outcomes Achievement and User Experience Analys...

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10th International HCI and UX Conference in Indonesia, CHIuXiD 2024

作者： Susanto, Helmi Yusuf Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350380439

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. © 2024 IEEE.

关键词： ARCS Model cryptography cybersecurity educational games puzzle games user experience Visual Novels web games

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Indonesian Tweet Emotion Detection Using IndoBERT 9

Indonesian Tweet Emotion Detection Using IndoBERT

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Masaling, Nikita Ananda Putri Siswanto, Ricky Reynardo Girsang, Abba Suganda Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

This study investigates emotion detection on tweets written in the Indonesian language, using the IndoBERT model that has been trained for 50 epochs. The examination conducted in this study provides a comprehensive analysis of the performance dynamics shown by the model. The assessment results provide an accuracy score of 0.74, indicating the model's proficiency in identifying sentiments within the collection of tweets. By using assessment criteria such as accuracy, recall, and the F1-score, the model's comprehensive analytical ability is validated, emphasizing its effectiveness in deciphering various emotional circumstances. The accuracy, recall, and F1-score of the model, with average values of 0.79, 0.78, and 0.78 respectively, combined demonstrate its resilience in accurately capturing subtle emotional subtleties. This study enhances our comprehension of language model applications in the field of emotional intelligence by exploring the complexities of sentiment analysis. It emphasizes the practical value of these applications in real-world scenarios. © 2024 IEEE.

关键词： Emotion Recognition

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"Nyctophy": Assessing the effectiveness of serious game for nyctophobia based on virtual reality by usability and heart rate monitoring 9th

"Nyctophy": Assessing the effectiveness of serious game for ...

引用

9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Ardiyanto, Elshad Ryan Alexander, Patrick Putra, Edyth Novian Ramdhan, Dimas Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Nyctophobia is a phobia of the dark and is common among children but also found in adults. While the phobia itself is commonly known, the diversity of its treatment is still minimal. As technology has reached its highest point, numerous inventions and innovations have emerged in the medical sector. This study aimed to examine the usability of Virtual Reality and Keyboard and Mouse as an interface using the Extended Reality Game Usability Questionnaire (XR-GUQ) in Nyctophobia therapy and to analyze the heart rate response, impact, and implications using t-test Paired/Wilcoxon Signed Rank. Thirty-four Bina Nusantara University students from various backgrounds completed the test using interfaces and a smartwatch. They were divided into two groups, high- and low fear, using the modified Acrophobia Questionnaire (AQ), which resulted in a significant difference. The XR-GUQ result was insignificant in all variables, which indicates similar usability scores on both interfaces. The t-test Paired/Wilcoxon Signed Rank test revealed a significant difference between the high- and low-fear groups when using the Virtual Reality interface compared to the Keyboard and Mouse interface. This significant difference was found within each group regardless of the interface used. This research shows similar scores in terms of usability but a significant difference in heart rate response with the help of a serious game to give a new sensation of phobia therapy. © 2024 The Authors.

关键词： Serious games

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Cosmetics Recommendation System Based on Ingredients Using Cosine Similarity 7

Cosmetics Recommendation System Based on Ingredients Using C...

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7th International Conference on Data Science and Its Applications, ICoDSA 2024

作者： Alisha Firdaus, Sekar Dwi Nurmuthia, Laksmi Imtiyaz, Raina Agung Santoso Gunawan, Alexander Eka Setiawan, Karli School of Computer Science Bina Nusantara University Data Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350365351

In the rapidly evolving beauty industry, consumers are often bombarded with an overwhelming array of skincare brands and products, making the quest for the perfect skincare regimen a daunting task. This saturation of the market not only confuses consumers but also poses the risk of resource wastage and potential skin damage due to incompatible ingredient combinations. To mitigate these challenges, our research presents an innovative recommendation system designed to streamline the product selection process. Utilizing the principle of cosine similarity, our methodology involves a detailed analysis of the ingredients contained in various skincare products. A quantitative foundation for evaluating ingredient lists of various skincare products is provided by cosine similarity, a mathematical metric that evaluates the similarity between two non-zero vectors by computing the cosine of the angle between them. Our algorithm generates customized product recommendations by thoroughly comprehending the intricate interactions among different constituents. This bespoke approach simplifies the decision-making process for consumers, enabling them to make well-informed choices that cater to their unique skin health needs. The effectiveness of our recommendation system is validated through comprehensive user feedback, demonstrating its potential to redefine the paradigm of personalized skincare recommendations within the beauty industry. Through providing customers with critical information and encouraging a culture of knowledgeable choice, we see a time when customized skincare products will not only increase customer satisfaction but also brand loyalty, which will be a big step toward the democratization of customized skincare. © 2024 IEEE.

关键词： Skin care products

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