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Sentiment Analysis on YouTube Comment Data for the Candidate Debate in the 2024 Presidential Election of the Republic of Indonesia 5

Sentiment Analysis on YouTube Comment Data for the Candidate...

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

作者： Purwandari, Kartika Jiwanggi, Meganingrum Arista Yulianti, Evi School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Universitas Indonesia Computer Science Faculty of Computer Science Depok16424 Indonesia Universitas Indonesia Faculty of Computer Science Depok16424 Indonesia

ISBN: (纸本)9798331528553

The 2024 presidential election in Indonesia is just around the corner, and political figures are actively campaigning to increase their electability. Sentiment analysis has become a valuable tool in understanding public opinion, especially in the context of political campaigns. This study aims to analyze the sentiments expressed by YouTube comments towards the candidates during the presidential debates. We compared several machine learning (Support Vector Machine, Multinomial Linear Regression, Multinomial Naive Bayes, Random Forest) models along with TF-IDF, BoW, and Word2Vec feature techniques compare with deep learning models (IndoBERT and RoBERTa). From the experimental results, the best result is RoBERTa, with accuracy 83% and F1-score 81%. Evaluation of the best model results is applied to the remaining data and then used for the analysis process. According to our data, the result of the Indonesian presidential election in 2024 had a mean absolute error (MAE) of 6.92%. Based on the relatively low MAE, YouTube comments can potentially provide useful insights for predicting future elections considering a good agreement between the real count and our sentiment analysis. © 2024 IEEE.

关键词： Contrastive Learning

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User Interface (UI) of Singosari Temple Interactive Virtual Reality Touring System 3

User Interface (UI) of Singosari Temple Interactive Virtual ...

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3rd International Conference on Digital Transformation and Applications, ICDXA 2024

作者： Sari, Wina Permana Primadani, Tiara Ika Widia Huda, Miranti Nurul Acarya, Hanustavira Guru School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Interior Design School of Design Bina Nusantara University Jakarta Indonesia Visual and Communication Design School of Design Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350373424

After the current COVID-19 pandemic, many sectors have been affected, one of which is the tourism sector. The tourism sector is at the bottom of the ranking which has experienced the most drastic decline in income. There is a positive side that can be learned from the post-pandemic conditions, several tourism sectors are starting to innovate with IT technology which has made tourism able to survive to this day. However, unfortunately, this IT technology innovation can only be implemented for tourism and medium to large scale purposes, but for tourism in local and remote areas this cannot be done due to limited human resources, facilities in the temple area and around the temple, lack of technology. support and limited marketing regarding Singosari temple. Especially for heritage tourism such as temple buildings which according to today's millennial children are less interesting to visit, because they think they are outdated and old school. This is the background for researchers to develop the application 'Singosari Temple Interactive Virtual Reality Tour System for Rebranding Heritage Tourism in Malang'. This application aims to preserve Indonesian culture and help rebranding and marketing tourism, especially heritage tourism in Malang, with the help of technology, namely Virtual Reality, in accordance with suggestions from Singosari Temple experts. So it can attract the interest of not only millennial children but also all ages, from domestic to foreign visitors because bilingual languages are available. The results of this paper are that Scrum is very suitable to be implemented in this Virtual Reality research because it supports rapid change and by using the UAT testing method the average user satisfaction is 92.1% (usability aspect 91.52%, information quality aspect 90.97%, and interaction quality aspects 94.06%). © 2024 IEEE.

关键词： Virtual reality

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Exploring the Impact of Feature Data Normalization and Standardization on Regression Models for Smartphone Price Prediction 8

Exploring the Impact of Feature Data Normalization and Stand...

引用

8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Bonamutial, Marcellino Prasetyo, Simeon Yuda School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Smartphone has become a necessity and the most accessible for every individual and is mainly used for communication. Smartphone price is higher than the previous years because of the new features provided. Smartphone Price Prediction will be using machine learning to predict the smartphone price with the provided feature. The dataset will be obtained through web-scraping with 14 features that consist of categorical and numerical features. Categorical features consist of Brand, Chipset, CPU, GPU, Screen Type, Resolution, and Total Camera, while numerical features consist of RAM, Weight, Storage, Screen Size, Pixel Density, battery capacity, and Price for the target. The model that is proposed for the study will be a decision tree regressor, random forest regressor, k-nearest neighbor regression, and multilayer perceptron regression using two pre-processing data methods that is data normalization and data standardization. The result of the research is data normalization is the most impactful pre-processing data on regression models in terms of performance and error rates. Random forest regressor with no scaling performs better than other models with a score of 0.10425 and 0.97552 for MAPE and R2 respectively. © 2023 IEEE.

关键词： Smartphones

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An Exploratory Computational Approach for Elucidating a Nonstructural Protein Interaction in Dengue Virus 2 9th

An Exploratory Computational Approach for Elucidating a Nons...

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

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Pardamean, Bens Mathematics Department School of Computer Science Bina Nusantara University 11480 Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

As the dengue infection still impacts hundreds of millions of people globally, unprecedented efforts in dengue drug development have been more progressive in recent decades. Computational methods provide a fast, sustainable, and efficient screening of active compounds and newly created drug molecules, including those specifically targeting nonstructural proteins (NS) of dengue viruses. In this work, protein modeling for the NS proteins of DENV-2/16681 strain was performed using a template-based homology modeling for the NS3 protein and an Artificial Intelligence (AI)-based prediction via AlphaFold for the NS4B protein. Moreover, the protein-protein interaction between the two structures was predicted using the HADDOCK server, which employs information about active and passive residues of the interaction interface to guide the docking process. After the modeling and its respective refinement process, the predicted structures of NS3 and NS4B improved their steric clashing scoring from MolProbity assessment. The refined models were then docked, and the resulting docking pose was analyzed to extract the interacting residues based on the polar contacts within the interface of the two proteins. Our result presents a preliminary study to create a dataset related to in silico molecular interactions of the NS3-NS4B interaction of different DENV types. It is helpful for building a computational pipeline for elucidating protein-ligand problems in dengue drug screenings. © 2024 The Authors.

关键词： Molecular docking

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Domain Adaptation in Color-Shifted Datasets Through Adversarial Learning Balancing 4

Domain Adaptation in Color-Shifted Datasets Through Adversar...

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Hidayaturrahman Trisetyarso, Agung Kartowisastro, Iman Herwidiana Budiharto, Widodo School of Computer Science Bina Nusatara University Mathematics Department Jakarta11480 Indonesia Bina Nusatara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Computer Engineering Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Due to the disparity in the levels of difficulty presented by the several tasks, doing domain adaptation in an adversarial way may result in an imbalanced learning process. In the MNIST dataset, this phenomenon also manifests itself in the form of domain adaptation for color-shifted distribution. In this particular situation, the domain classifier has a higher tendency to fit more quickly, but the category classifier fits quite poorly in the learning process. In order to address this problem, a new hyper-parameter has been added to the loss function in order to strike a compromise between the learning speed of the domain and the categorical classifier. By using this technique, the categorical classifier may better match the data while still maintaining the same level of performance as the domain classifier. In order to determine whether or not making use of this hyper-parameter is useful, the phenomena in question is examined using three distinct color-shifted settings. Following the evaluations, it was discovered that the newly introduced hyper-parameter is capable of coping with imbalanced learning while simultaneously engaging in domain adaptation. © 2023 IEEE.

关键词： Color

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Transforming Fashion Marketplaces: A Design Thinking Approach to AR and AI Integration 6

Transforming Fashion Marketplaces: A Design Thinking Approac...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Basuki, Carola Pratiwi, Chairani Putri Rohman, Akbar Zaidan Hasaini, Hasyid Fitra Halomoan, Leandro Nardphine Cuthbert, Ricardo Hendranata, Verdhinan Binus Entrepreneurship Center Management Department BINUS Business School Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

In the rapidly evolving landscape of fashion e-commerce, the integration of Augmented Reality (AR) and Artificial Intelligence (AI) opens new horizons for enhancing consumer experiences and empowering fashion brands. This study explores a design thinking-driven approach that leverages AR and AI technologies to transform online fashion marketplaces. AR and AI-driven fashion marketplaces present an innovative solution to address persistent challenges such as size discrepancies, visualization limitations, and lack of customization options. The marketplace offers consumers a more immersive, interactive, and personalized shopping experience by incorporating these technologies. The findings reveal that this integration not only boosts brand awareness but also significantly enhances customer engagement, streamlines the decision-making process, and drives higher conversion rates for fashion brands. The study underscores the potential of AR and AI to revolutionize how fashion is experienced online, ultimately benefiting both consumers and brands through increased satisfaction and operational efficiency. The findings provide valuable insights for fashion brands seeking to enhance customer experiences and drive business growth through the strategic integration of AR and AI technologies. The contribution of study as guide future investigations into the long-term effects and practical applications of AR and AI in online fashion. © 2024 IEEE.

关键词： Marketplaces

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Abstractive Indonesian News Summarization Using BERT2GPT 7

Abstractive Indonesian News Summarization Using BERT2GPT

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7th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2023

作者： Nasari, Maulin Maulina, Ayu Girsang, Abba Suganda Computer Science Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350382266

This study examines the necessity of employing BERT2GPT for single-document summarization in the current age of escalating digital data. The primary focus of this work is on the abstractive technique, which tries to generate versatile summaries that surpass the primary sentences of the original content. This study employs two models, namely BERT and GPT -2, for the purpose of the summarization system. The paper introduces the BERT2GPT model, which merges the bidirectional characteristics of BERT with the generative powers of GPT. The findings indicate that the BERT2GPT method successfully catches significant information and linguistic nuances, hence enhancing the quality of the generated summaries. The corresponding average values for Rl, R2, and RL are 0.62, 0.56, and 0.60, respectively. © 2023 IEEE.

关键词： Abstractive Summarization BERT2GPT single-document summarization

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Analysis of Enterprise Architecture Research Trends for Higher Education Institutions Using Systematic Literature Review and Vos Viewer

Analysis of Enterprise Architecture Research Trends for High...

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2023 International Conference on Informatics Engineering, science and Technology, INCITEST 2023

作者： Soegoto, Yudistira Prabowo, Harjanto Spits Warnars, Harco L H Trisetyarso, Agung Bina Nusantara University Binus Graduate Program Doctor Computer Science School of Computer Science Computer Science Departemen Jakarta11480 Indonesia Bina Nusantara University School of Computer Sicence Mathematics Departement Jakarta11480 Indonesia

ISBN: (纸本)9798350317862

Enterprise Architecture Framework (EAF) is a commonly used framework and the best solution for addressing and defining the transformation that needs to be built to support business operations. To be able to make the transition quickly, many higher education institutions (HEIs) are starting to adopt EAF. This research aims to help the evolution and transpiration of enterprise architecture research in higher education. This research uses a systematic literature review (SLR) research method which includes several steps, namely identifying research questions, identifying research sources, using keywords to complete the data discovery process, disseminating data, and analyzing the results to answer research questions. The data used comes from digital libraries, especially Emerald Insight, IEEE Xplore Digital Library, and science Direct. Data taken from 2019 to 2023 in RIS format will then be analyzed and visualized using VosViewer. The results of this research are to find the growth of research publications over five years, find research trends on enterprise architecture frameworks, identify relationships between scientific concepts, and determine the knowledge network of enterprise architecture frameworks based on keywords. © 2023 IEEE.

关键词： Digital libraries

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Designing a Story-based Text-based RPG Video Game to Minimize Feelings of Depression Caused by Losing Someone to Players

Designing a Story-based Text-based RPG Video Game to Minimiz...

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2023 International Conference on Data science and Its Applications, ICoDSA 2023

作者： Tan, Jonas Sihombing, Pascal Widianto, Mochammad Haldi Bina Nusantara University Bandung Campus School of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350305197

This paper aims to design a story-based and text-based Role-Playing Game (RPG) video game that can help reduce the negative impact of depression due to losing someone. Video game development uses a process called the Game Development Life Cycle (GDLC) method. This method is used to give guidance for the authors to develop a video game step by step. The stages of making the video game start from the idea generation using video game references that refers to specific genre, which is RPG games that focuses on narrative and emotional experiences. Therefore, the authors additionally research the storytelling side of the game before proceeding to work on the interface design stages or commonly called as prototyping. The authors made several important survey forms before publishing to collect player's data. Later then, the authors deployed the video game to the public at the end of the development. To collect research data, surveys were used before and after the game was played to detect the differences and the level of effectiveness of the game against players. The results of this research are expected to contribute to the development of video games to heal players' mentality and as a foundation for further similar research. © 2023 IEEE.

关键词： Software design

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Object Size Recognition as Intra-class Variations using Transfer Learning

Object Size Recognition as Intra-class Variations using Tran...

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2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

作者： Rahmania, Rissa Hendric Spits Warnars, Harco Leslie Soewito, Benfano Gaol, Ford Lumban Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

The ability to differentiate various products in the retail store plays an essential role to provide effectiveness to customers and reduce or even eliminate long queues. However, traditional machine learning algorithms are incapable of recognizing many subordinate categories in various retail product. This paper aims to recognize the retail product recognition algorithm based on the YOLOv7 model in terms of intra-class variations, with the sub-categories of brand and size. We used two schemes of the dataset to compare recognition performance between them. Firstly, the YOLOv7 is applied in the two schemes of the dataset that is annotated with the subordinate category to detect the brand as meta category. Secondly, the proposed method is applied by adding the object size classification into the YOLOv7 model where the square area of the bounding box was calculated to classify the product according to size. Confidence score and square area are used to verify the object and to obtain the product size, which represents sub-category of the product. The experimental results show that our proposed method achieves higher recall compared to baseline object detection. © 2023 IEEE.

关键词： Object recognition

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