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Development of educational game as a media to raise public awareness of illegal animal trafficking issue in Indonesia 9th

Development of educational game as a media to raise public a...

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

作者： William, Jonathan Ahmadi, Khalid Fajar, Muhamad Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The amount of illegal wildlife trade cases increases every year in Indonesia. This causes some unique Indonesian wildlife to become endangered or even extinct. Therefore, the purpose of this research is to raise public awareness to illegal wildlife trade issue by using a game as its media to reduce the number of cases of illegal wildlife trade in Indonesia. The game made in this research will be developed using the GDLC development method and 2021.3.11f1 version of Unity as its game engine. To evaluate the game that has been developed in this research, a comparation to other related games is conducted and resulted in the game that has been developed in this research is significantly better than other related games in Challenge, Learnability and Concentration aspects (p © 2024 The Authors.

关键词： Invertebrates

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Player evaluation and learning outcomes of "NusaVenturas": A serious game for enhancing player knowledge and interest in Indonesian traditional foods 9th

Player evaluation and learning outcomes of "NusaVenturas": A...

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

作者： Sanjaya, Vito Sebastian Tanoto, Nicholas Valenthinus Tandinata, Nicholas Ramdhan, Dimas Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The popularity of Indonesian traditional food has been declining due to the increasing influence of foreign cuisine. This study presents the development method that combining Game Development Life Cycle (GDLC) with Experiential Game Learning Design Framework and evaluation of a serious game "NusaVenturas" using usability, learning outcome, and Game Experience Questionnaire (GEQ) that designed to introduce, promote interest, educate, and preserve knowledge of Indonesian traditional foods. "NusaVenturas" is a unique 2D serious game that integrates puzzle-platformer elements with time-management cooking mechanics. The study involved 37 participants aged 18 to 23. Evaluation results indicate that "NusaVenturas" significantly enhances players' knowledge of Indonesian traditional foods, with statistical analysis confirming the significance of the findings. © 2024 The Authors.

关键词： Food ingredients

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Development of "Peter's First-Aid Adventure" Virtual Reality-Based Serious Game in First-Aid Education: Usability Analysis of Virtual Reality Interaction Tools 9th

Development of "Peter's First-Aid Adventure" Virtual Reality...

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

作者： Rainer, Alexander Setiono, Angeline Leonardrich, Kevin Ramdhan, Dimas Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Incidents that threaten lives can occur unexpectedly, highlighting the importance of immediate first aid. Studies show that Virtual Reality (VR)-based Serious Games (SG) are excellent alternatives for learning, especially for physical training, as they provide immersive and realistic scenarios where users can learn and practice their skills in a safe environment. Therefore, this research proposes the design of a VR-based SG for learning first aid procedures. A total of 31 participants tested the game's usability using both VR controllers and hand tracking, playing the game with both tools in random order, and then completing the XR-GUQ and Interaction Categories questionnaire. The results indicate that controllers offer higher usability than hand tracking. However, the game can still effectively utilize both interaction tools, given their satisfactory usability ratings. © 2024 The Authors.

关键词： Virtual environments

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File Classification Containing Secret Key in Git Repository Using Character Level CNN and Shannon Entropy 4th

File Classification Containing Secret Key in Git Repository ...

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4th International Conference on Advances in Computational science and Engineering, ICACSE 2023

作者： Muhammad, Rafie Musdholifah, Aina Master Program in Computer Science FMIPA UGM Yogyakarta Indonesia Department of Computer Science and Electronics FMIPA UGM Yogyakarta Indonesia

ISBN: (纸本)9789819729760

Current technological developments are directly proportional to the number of information technology projects made. This project is usually in the form of a program formed from a code. To facilitate version control and contributions between developers, git tools are usually used which are placed on an online platform such as Github. If a repository on an online platform contains sensitive information such as secret key variables and the repository can be accessed by the public, then this can be used to harm the company or organization that owns the repository. Several ways have been done before to detect this secret key variable by using the regex method and using machine learning to minimize false positive results. In this research, we will try to build a text or file classification model that contains secret key variables using the character level CNN and Shannon entropy. The Shannon entropy algorithm is used during pre-processing to retrieve the group of words with the largest entropy value and the CNN character level will be used because it is considered suitable for this case since the value of the secret key is abstract and does not require a sequence context for the said secret key in a file. The results of this study were able to obtain an accuracy value of 96.1% for the accuracy value for the classification of files containing secret key. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Character level CNN Git repository Secret key Shannon entropy Text classification

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Seamless High Availability in MySQL Database Systems: An Advanced Implementation of ProxySQL, Orchestrator, and Keepalived

Seamless High Availability in MySQL Database Systems: An Adv...

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2025 International Conference on Advancement in Data science, E-learning and Information System, ICADEIS 2025

作者： Loa, Jeremy Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331513320

High availability (HA) in MySQL databases remains a critical challenge, particularly due to risks such as single point of failure (SPOF) and limited scalability in existing setups. Previous studies have explored various approaches to address these issues. One study implemented ProxySQL and Orchestrator for query routing and failover but relied on a single server instance, creating a SPOF that could disrupt client access during failures. Another study implemented HAProxy to balance traffic and couple database servers with specific web applications. While effective for certain use cases, this approach reduced resource efficiency and scalability, because it relies on HTTP protocol and database server are coupled to each application, making it less suitable for dynamic, shared environments requiring high flexibility. These limitations highlight the need for a more robust and scalable HA solution. This paper proposes an improved HA architecture that eliminates SPOFs and enhances scalability by combining redundant ProxySQL instances synchronized with Keepalived managed Virtual IP (VIP) and automated failover using Orchestrator. The architecture allows shared database resources across multiple applications while decoupling them from specific application servers. Test results confirm the system's ability to maintain seamless failover, consistent query routing, and uninterrupted client access through dynamic Virtual IP reassignment to backup server. By addressing the issues of previous studies, this solution provides a practical and scalable framework to achieve high availability in the MySQL cluster by combing ProxySQL, Orchestrator, and Keepalived, making it suitable for modern enterprise environments. © 2025 IEEE.

关键词： HTTP

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Input Representation on Text Data for E-Commerce Product Review Summarization using Graph Convolutional Network 6

Input Representation on Text Data for E-Commerce Product Rev...

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

作者： Sari, Azani Cempaka Heryadi, Yaya Kartowisastro, Iman Herwidiana Budiharto, Widodo Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

This paper investigates recent advancements and methodologies in Automatic Text Summarization, a field that has garnered significant attention for its ability to condense lengthy documents into concise summaries while preserving key information and themes. The study examines the development of Automatic Text Summarization models, including both extractive and abstractive approaches. Additionally, the research delves into the use of graph convolutional networks for text representation in e-commerce product review summarization. The study employs an e-commerce dataset in conjunction with a graph convolutional network model, covering stages from preprocessing and tokenization to constructing graph-based data representation. The expected outcome is a graph-structured representation of input text data derived from Indonesian-language e-commerce product reviews. © 2024 IEEE.

关键词： Convolutional E-commerce Graph Network Product Review Summarization Text

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Evaluating Vision Transformers Efficiency in Image Captioning 4

Evaluating Vision Transformers Efficiency in Image Captionin...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Samosir, Bintang Kevin Hizkia Isa, Sani Muhamad Binus University Binus Graduate Program Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331506490

This study investigates the performance of Vision Transformer (ViT) variants - the Shifted Window Transformers (SWIN), Distillation with No Labels (DINO), and Data-efficient Image Transformers (DeIT) - in image captioning tasks using the Flickr8K dataset. While ViT architectures have shown promise in image classification, their effectiveness for image captioning, particularly with smaller datasets, remains unclear. The models' performance was evaluated using BLEU metrics, while training efficiency was analyzed through Pareto front analysis of computational time and accuracy. Among the tested variants, SWIN Transformers demonstrated superior performance (BLEU-1: 64.4, BLEU-2: 33.9, BLEU-3: 17.1, BLEU-4: 8.4), followed by DINO (BLEU-1: 63.1, BLEU-2: 32.7, BLEU-3: 16.4, BLEU-4: 7.5), while DeIT showed the weakest performance (BLEU-1: 61.6, BLEU-2: 31.1, BLEU-3: 14.7, BLEU-4: 6.5). SWIN Transformers achieved the shortest training time at 3 minutes 31 seconds per epoch, making it the most efficient model among ViT variants based on Pareto front analysis. While ViT variants achieved competitive BLEU-1 scores comparable to previous top models, they struggled with generating coherent, longer sentences, as evidenced by suboptimal BLEU-4 scores. These findings provide empirical evidence of how the lack of inductive bias in transformer architectures affects their ability to capture complex scene relationships, despite their strong feature detection capabilities, contributing to the understanding of transformer models' limitations in vision-language tasks, especially with limited data. © 2024 IEEE.

关键词： Distribution transformers

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Envisioning Risk Management for Smart Contracts: A Conceptual Model

Envisioning Risk Management for Smart Contracts: A Conceptua...

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

作者： Yulianto, Semi Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350317862

This study proposes a smart contract risk management model built on the NIST Risk Management Framework (RMF) to help identify, assess, and manage the risks of smart contracts. While smart contracts are beloved as a means to automate and disintermediate business processes, their security vulnerabilities can be critical. The main issue discussed in this paper is the lack of a holistic approach to risk management smart contracts. The resulting framework consists of six steps: Risk identification, assessment, prioritization, mitigation, testing, and continuous monitoring (and was developed through reviewing existing literature on smart contract security and the NIST RMF). It is recommended that a case study be performed to prove the proposed model's effectiveness in managing the risks of smart contracts and minimizing financial losses and reputational harm. The paper presents a risk management framework for smart contracts to increase trust and adoption to enhance security while reducing financial losses and reputation damage. This has wider implications for the security of smart contracts and can be used as a starting point for future work. This study is expected to significantly contribute to smart contract security by introducing an organized way to address these contracts' risks using the NIST RMF. © 2023 IEEE.

关键词： Smart contract

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Investigating the Impact on Data Recovery in computer Forensics 1

Investigating the Impact on Data Recovery in Computer Forens...

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1st IEEE International Conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Soewito, Benfano Bina Nusantara University Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

Defragmentation can potentially be employed as a tactic by perpetrators to conceal, misrepresent, or eliminate digital evidence. This study explores the effects of minor defragmentation, a potential method to conceal digital evidence, on recovering file system data in digital forensics. Our investigation sought to determine the influence of minor defragmentation on the effectiveness of data recovery and to identify methods that can augment the success rate post-defragmentation. We limited the scope of this study to defragmentation in Hard Disk Drives (HDDs), solid-state drives (SSDs), and USB drives. A mixed-method approach employs a literature review, case studies, and controlled experiments. Comparative analysis was used as the main data analysis technique to investigate its impact. Preliminary findings suggest that minor defragmentation hampers data recovery;however, certain strategies can augment success rates. These results can significantly influence the development of data recovery policies, particularly those of digital forensic analysts and law enforcement. The primary objective of this study is to bolster the efficiency and dependability of file system data recovery post-defragmentation while upholding ethical and legal standards. © 2023 IEEE.

关键词： Recovery

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GeoBeeDashboard: An Intelligent Geospatial Platform for Enhancing Waste Management in Tangerang City 13

GeoBeeDashboard: An Intelligent Geospatial Platform for Enha...

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13th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2024

作者： Muljana, Richie Deffansyah, Syauqi Akmal Andrew, Hari Gunawan, Alexander Agung Santoso Irwansyah, Edy Pramudya, Fabian Surya Ario, Muhamad Keenan Syahputra, Muhammad Edo Achmad, Said School of Computer Science Bina Nusantara University Data Science Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Mathematics Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368086

In this study, we created an Intelligent Geospatial Platform called GeoBeeDashboard. The GeoBeeDashboard combines advanced geospatial technologies and artificial intelligence (AI), allowing real-time data visualization and optimized decision-making across multiple sectors. The system architecture consists of a ***-based front end, a FastAPI-driven back end, and PostGIS for geospatial data management. One of the GeoBeeDashboard's primary use cases is addressing waste management issues in Tangerang City, Indonesia. As rapid urbanization increases waste generation, effective management becomes critical. The dashboard identifies critical trends and inefficiencies in Tangerang's districts by K-Means clustering waste management data from 2020 to 2023. Our findings identify distinct clusters, highlighting areas with effective waste management and those that require targeted interventions. The benefits that local government can get from GeoBeeDashboard by utilising insights based on clustering analysis of data per each district in Tangerang to optimise waste collection, allocate resources efficiently, and improve the policy-making process for each district in Tangerang. The GeoBeeDashboard improves local government capabilities by providing a scalable model for other cities facing similar urban challenges. In conclusion, GeoBeeDashboard provides local governments with a powerful tool for addressing waste management inefficiencies and fostering sustainable urban development. © 2024 IEEE.

关键词： Urban planning

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