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

作者： Mola, Sebastianus Adi Santoso Widiastuti, Tiwuk Roma, Rosa V. K. Isabela Ohe Karnyoto, Andrea Stevens Pardamean, Bens University of Nusa Cendana Faculty of Science and Engineering Kupang Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

A subscription movie streaming service from the United States, Netflix, has been present in Indonesia since 2016 and provides a wide variety of films without showing any single advertisements that can be viewed from anywhere, as long as there is access to the internet. Despite these advantages, many users have complained through the Google Play Store's comments column. Some of the common complaints include frequent buffering and connectivity issues, dissatisfaction with the limited selection of Indonesian movies, lack of subtitles for specific languages, or pricing concerns have also been raised. In this study developed two combined scenario methods using the InSet and SentiStrength-id dictionary to obtain better performance and compare them against independent InSet and SentiStrength-id. This study collected users' comments for the Netflix app in the Google Play Store as a dataset using web scraping techniques through the Google Collaboration tool. The dataset contains 3250 rows spanning the period from January 22, 2024, through June 6, 2024. To ensure proper processing of the text, data cleaning, lowercasing, normalization, tokenization, stemming, and stopwords removal are conducted. The results show that most user opinions are negative. The InSet dictionary has an accuracy of 92%, SentiStrength-id 78%, Combined scenario 1 is 87%, and scenario 2 reaches the highest among others which is 92.52%. © 2024 IEEE.

关键词： Video streaming

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Developer-Centric Task Allocation: An Intelligent Approach for Enhanced Software Productivity 15

Developer-Centric Task Allocation: An Intelligent Approach f...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Fensterseifer Filho, Evandro L. R. Assuncao, Joaquim V. C. Fontoura, Lisandra M. Federal University of Santa Maria - Ufsm Graduate Program in Computer Science RS Santa Maria Brazil Federal University of Santa Maria - Ufsm Applied Computing Department RS Santa Maria Brazil

ISBN: (纸本)9798350368833

Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essential to consider the skills and profile of each developer, thus maximizing their productivity. In projects with large teams, task allocation can be challenging, and the help of tools can facilitate its execution. In this work, we propose an intelligent approach for allocating software development tasks suitable to the profile of developers. From the literature, we define the appropriate skills and technical profiles for a development team, and the assessment is based on the developer completing a questionnaire. We developed a recommendation system to suggest tasks to be allocated to developers, employing text processing techniques. For validation, 495 tasks were used from an actual project developing simulator software for military training. The recommended allocations were evaluated by the project developers and used to improve the system. Validations showed that the developed approach makes consistent and coherent task recommendations to developers according to the developer profile, as participants agree with the recommendation for 76% of tasks. © 2024 IEEE.

关键词： Project management

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Detection of Narcotics Money Laundering in Suspicious Financial Transactions Using Convolutional Extreme Gradient Boosting (ConvXGB)

Detection of Narcotics Money Laundering in Suspicious Financ...

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

作者： Leonardus Verrell Sayoga Kinantra Winarno Antoni Wibowo Computer Science Department Binus Graduate Program – Master of Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

With the development of narcotics problems that continue to increase, the Indonesian Government responds through the Badan Narkotika Nasional (BNN) with data showing the condition of narcotics tends to grow every year and is followed by the number of assets of money laundering (ML) crimes against narcotics cases. One of the banks in Indonesia as a reporting party for suspicious financial transactions (SFT) has obstacles in detecting narcotics ML due to complex and rarely found patterns. Some previous studies conducted experiments using Convolutional Neural Network (CNN), Extreme Gradient Boosting (XGBoost), and even a combination of both into Convolutional Extreme Gradient Boosting (ConvXGB), and improved model performance in several datasets. This paper designs a model using the ConvXGB algorithm by adopting the CNN architecture, LeNet-5, by applying several convolution layers and pooling layers as a baseline model for feature learning, and the XGBoost as feature classification. Three phases of research are the preprocessing phase by collecting data, transforming data, balancing data with a hybrid sampling technique, splitting data, and scaling data, followed by the implementation phase by creating a ConvXGB model, training and testing the model, then finally the evaluation phase by analyzing results and hyperparameter tuning. The dataset used is SFT from the bank during 2023. This ConvXGB has three convolution layers, a pooling layer, and a flattened layer. The performance test results are the accuracy value and F1-Score value of 99.11% each after hyperparameter tuning. By performing a hybrid model, the model performance results are better.

关键词： Training Representation learning Analytical models Convolution Government Boosting Data models Convolutional neural networks Tuning Testing

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Fuzzy Logic for Assessing the Health of a Corn Crop within Family Farming

Fuzzy Logic for Assessing the Health of a Corn Crop within F...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Mendonca, Vanessa Santos, Mikael Munoz, Daniel M. Humberto Llanos, Carlos Federal Institute of Brasilia Department of Computer Science Brazil Mechatronics Graduate Program Department of Mechanical Engineering Brazil Federal Institute of Brasilia Department of Agronomy Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Technological advancements are increasingly evident across various sectors, including automobiles, industry, and healthcare. In precision agriculture, significant progress has been made, with AgroTICs and Smart Agriculture gaining substantial traction in the market. However, a gap remains between cutting-edge technology and family farming, presenting a challenge from both social and applied research perspectives. However, there is still a gap between cutting-edge technology and family farming, which creates a challenge from a social and applied research point of view. In this context, this paper proposes a monitoring model based on Fuzzy Logic and sensor automation applied to estimate the health of a corn crop. The proposed Fuzzy inference system involves calculating an indicator of nutrients as well as the average color and area of corn plants. The nutrient indicator is automatically computed by an ESP32 microcontroller using sensor readings, while the average color and area inputs are manually entered via a mobile application. Additionally, the Fuzzy inference is integrated into the ESP32. The model underwent experimental validation on the health of the plantation, and the results were evaluated in four areas: one was designated for testing, and three were for validation. The model achieved an accuracy of 97.5% in Scenario 3, categorized as 'Very Favorable', and an accuracy of 65% in Scenarios 2 and 4, categorized as 'Unfavorable'. The implications of this research contribute to the advancement of AgroTICs among small producers, with the potential to enhance and automate the monitoring of their harvest production. © 2024 IEEE.

关键词： Agribusiness

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Exploring Cooperation and Competition in computer science Education: An Investigation Based on Game Theory 17

Exploring Cooperation and Competition in Computer Science Ed...

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17th International Conference on computer Supported Education, CSEDU 2025

作者： Moura, Waldir Siqueira Delbem, Edgar França, Juliana Baptista dos Santos Dias, Angélica Fonseca da Silva Computer Science Graduate Program PPGI Federal University of Rio de Janeiro Térreo Bloco E CCMN/NCE University City Rio de Janeiro68.530 Brazil

ISBN: (纸本)9789897587467

The study investigates the use of the game Overcooked as a pedagogical tool in primary education, focusing on cooperation and competition. The research, conducted throughout 2022, analyzed one semester as a baseline and another with pedagogical interventions. Four groups were studied: control (no interventions), game without instructions, game with teamwork guidance, and game without verbal communication. Questionnaires and qualitative/quantitative data assessed engagement, motivation, and cooperation. The interventions significantly improved performance, motivation, and skills such as teamwork and problem-solving, validating gamification as an educational resource. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Teaching

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Literature Review: Analysis of Essential Metadata Attributes of Digital Goods for Transaction in The Virtual World 9

Literature Review: Analysis of Essential Metadata Attributes...

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

作者： Martha, Gede Indra Raditya Prabowo, Harjanto Gaol, Ford Lumban Wiputra, Richard BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

In online-based virtual worlds such as Metaverse, Online Games, and other online digital spaces, the virtual/digital goods (digital items / digital assets) are fundamental things that must be available to be able to do business & create an economy in the virtual world through monetization & transactions from these digital goods. This research focuses on summarizing and exploring the attributes used in digital goods in the virtual world by extracting attributes in digital goods from other related studies using the Systematic Literature Review methodology & PRISMA Framework comprehensively so that it can be a reference for developers in designing the properties and functions of digital goods in the virtual world that are being developed, which in this case will be in the form of an NFT in the future. Based on research that has been carried out, 3 essential metadata attributes have the most influence on transactions, number 1 Visual Design / Aesthetic (Representative), number 2 Effect (Utilities), and number 3 Statistics / Performance (Utilities) which must be considered in developing/making digital goods in the form of NFTs in the virtual world so that the value of digital goods can attract users to buy or transact them in the virtual world. © 2024 IEEE.

关键词： Virtual environments

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ICT-Based Conceptual Model for Local Culture Communities using Soft System Methodology 7

ICT-Based Conceptual Model for Local Culture Communities usi...

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

作者： Nindito, Hendro Prabowo, Harjanto Sfenrianto Hendric, Spits Warnars Harco Leslie BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The problems that exist in the field of art and culture preservation experienced by the arts and culture community side are the limitations on physical facilities for disseminating works, exchanging information between arts and culture communities, as well as the need to increase professionalism so that they can be independent in order to help improve the economy, where the role of regulation in this regard also affects this condition. Based on the facts above, this community requires an interaction model that is integrated with the use of information technology. This study uses a Soft System Methodology approach to create a model that is suitable for the arts and cultural community. The result is an ICI-based conceptual model for a local culture community. (Abstract) © 2022 IEEE.

关键词： Information use

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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Yanfi, Yanfi Heryadi, Yaya Lukas, Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University Binus Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy. © 2022 IEEE.

关键词： Sentiment analysis

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Improved Model for Identifying the Cyberbullying Based on Tweets of Twitter

Informatica (Slovenia)

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Informatica (Slovenia) 2023年第6期47卷 159-164页

作者： Samalo, Darwin Martin, Rizky Utama, Ditdit Nugeraha Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

The surge of cyberbullying on social media platforms is a major concern in today's digital age, with its prevalence escalating alongside advancements in technology. Thus, devising methods to detect and eliminate cyberbullying has become a crucial task. This research meticulously presents a refined model for identifying instances of cyberbullying, building on previous methodologies. The process of devising the model involved a thorough literature review, object-oriented design, and decision tree methodologies to shape the labelling procedure and build the classifier. Data pre-processing was executed using RapidMiner, considering six intrinsic components. The final model successfully classified Indonesian-language tweets into five distinct categories: animal, psychology and stupidity, disabled person, attitude, and general bullying, with an accuracy rate of 99.56%. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Decision trees

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Implementation of Lightweight PRNG on PLC for Industrial Control Systems 3

Implementation of Lightweight PRNG on PLC for Industrial Con...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Sama, Andi Gaol, Ford Lumban Harso Supangkat, Suhono Ranti, Benny Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Institute of Technology Bandung Faculty of Digital Communication and Hotel & Tourism Bandung Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350394559

The Information Technology/Operational Technology convergence towards Industry 4.0 opens the opportunity to leverage recent advancements in Information Technology for Operational Technology, such as Cloud, Internet of Things, and Artificial Intelligence. Meanwhile, cyber-attacks are increasing for Operational Technology. The security aspect in Operational Technology systems has traditionally been a low priority, in contrast with speed. This introduces challenges as Industrial Control Systems such as programmable Logic Controller in Operational Technology have been traditionally optimized for speed rather than security due to limited computing power. As computations need to be as efficient as possible, security in Operational Technology has yet to be managed as robustly as in Information Technology. Operational Technology communication protocols for securing data transfer, for example, have no or just a few security capabilities, even for basic authentication and encryption. Common security algorithms rely on random numbers. However, Random Number Generator is not usually part of standard functions in programmable Logic Controllers, the core control component in Industrial Control Systems. In Industrial Control Systems, the Random Number Generator is mostly implemented as a software-based Pseudo Random Number Generator. This paper shows how to apply a Pseudo Random Number Generator in a Siemens Compact PLC S7-1200 using a modified lightweight XORshift algorithm. The XORshift algorithm can generate better randomness than the system's clock-based implementation in the Siemens Library of Generic Functions. © 2023 IEEE.

关键词： Internet of things

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