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

作者： Kristiana, Idha Meyliana, Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Management Departement Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

The exponential growth of data is compelling organizations to employ data in decision-making. As one of the businesses with an ecosystem that contributes to data growth, banks have challenges in generating insight. A high level of data security is frequently linked to a high level of data access difficulties. This poses a challenge to the implementation of data-driven business, where taking control of our data is one of the best ways to ensure that we not only own data but also have the ability to process and use data to extract business value. Through literature review, a number of challenges to optimizing the implementation of big data analytics in the banking industry were discovered. Data governance refers to the methods and procedures that assist banks in managing and securing data. A big data architecture is presented to address the highlighted issues, particularly with a multi-tiered approach to big data structures. With the adoption of this architecture, it will be simpler to generate business-value-generating insights for the banking industry using big data with accessibility and protection of data. © 2023 IEEE.

关键词： Big data

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Semantic Literature Review on Non-Fungible Token: Expansion Area of Usage & Trends 8

Semantic Literature Review on Non-Fungible Token: Expansion ...

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8th International Conference on information management and Technology, ICIMTech 2023

作者： Martha, Gede Indra Raditya Warnars, Harco Leslie Hendric Spits Prabowo, Harjanto Meyliana Hidayanto, Achmad Nizar Bina Nusantara University Binus Graduate Program - Doctor of Computer Science 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 System Department Jakarta11480 Indonesia University of Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350326093

Blockchain, Metaverse & NFT are technologies that were booming during the Pandemic. As a derivative product of blockchain, the Non-Fungible Token (NFT) is one of the technologies that has attracted the most interest from investors and the public because of its potential benefits and has always been closely associated with the Metaverse as a main purposes research of the NFTs. This paper is to explore the possibilities and provide an overview of the current use of NFT technology so that it can provide insight for further research & gap with the big picture that it is trying to present in this paper. However, after exploring further related to NFT in this research, it was found that the problem that most people are trying to solve through NFT is related to the topic of Decentralization & Web3 not as a Metaverse main backbone. © 2023 IEEE.

关键词： Blockchain

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Predicting User Preferences with Neural Network Learning to Rank Method 5

Predicting User Preferences with Neural Network Learning to ...

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5th IEEE International Conference on information Technology, information Systems and Electrical Engineering, ICITISEE 2021

作者： Qomariyah, Nunung Nurul Fajar, Ahmad Nurul Bina Nusantara University Faculty Of Computing And Media Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program-Master Of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781665401968

User preference learning has been around for many years. This is a common problem arise in e-commerce system, where the companies need to understand their customers in order to sell the correct products to their target customers. The user preference is also needed in the movie domain area, as the film companies who produce the movie also need to understand how the customers value their movie products, whether the market like it or not. This can help them to predict the best components for the future movie. In order to produce the recommendation to the customer, we can show a list of item in a correct order, sorted from the most relevant/the most liked one to the most irrelevant item. In this paper, we utilize the Learning to Rank (LTR) approach from information retrieval domain area to learn the user preference in recommender system domain. We applied LTR with pairwise approach from the two most popular algorithms in this area, i.e. RankNet and LambdaRank, on 25, 345 user ratings from 5, 000 movie dataset and evaluate both algorithms. We used a Neural Network architecture as the learning mechanism. We also measuring the speed performance of the two algorithms. © 2021 IEEE.

关键词： Sales

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Security Risks and Best Practices for Blockchain and Smart Contracts: A Systematic Literature Review 8

Security Risks and Best Practices for Blockchain and Smart C...

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8th International Conference on information management and Technology, ICIMTech 2023

作者： Yulianto, Semi Hendric Spits Warnars, Harco Leslie Prabowo, Harjanto Meyliana Hidayanto, Achmad Nizar Bina Nusantara University Binus Graduate Program - Doctor of Computer Science 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 Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350326093

The rise of blockchain technology and smart contracts has brought widespread attention due to their capacity to transform multiple industrial sectors through decentralized, transparent, secure transactions. However, despite their promise to revolutionize various fields worldwide, lingering concerns regarding security risks impede their adoption rate. Addressing these concerns is crucial now more than ever;therefore, we conducted a comprehensive literature review within our study's scope that focused on published papers between 2014-2023 centered around security risks concerning blockchain and smart contracts. Our systematic approach using the PRISMA checklist analyzed nine categorized research model-based primary studies while recognizing vulnerabilities in smart contract development and providing best practices to mitigate such issues. These findings benefit both researchers and practitioners as they showcase how acknowledging these vulnerabilities can further develop into exploring more significant aspects of blockchain technology's security issues and smart contract development processes. Our study contributes significantly by expanding knowledge in this field while providing novel insights valuable for individuals involved in designing or implementing blockchain technologies. © 2023 IEEE.

关键词： Smart contract

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Learning Pairwise Preferences from Movie Ratings 7

Learning Pairwise Preferences from Movie Ratings

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Qomariyah, Nunung Nurul Fajar, Ahmad Nurul Bina Nusantara University Faculty of Computing and Media Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

Preference Elicitation is now considered a crucial stage in recommender system. That is the stage where we collect and query preferences of the users as part of interactive decision support system. Preference elicitation can be performed using many ways, such as asking the user explicitly to give ratings or feedbacks for some products, or implicitly observing their behaviour. Once this preference has been collected by the system, it can then be used to generate item recommendation. Using explicit feedback itself, such as rating only, has several drawbacks. Using ratings is very subjective. Two users with similar taste might give different rating to the same item. A user also may not be consistent in giving number to express their liking. In other case, a user may like an item more than the other items, but feels difficult to give lower rating on the other item, because it means that the particular item is just as bad as the one he/she does not like. By showing two different items as a pair, it will be easier for the users to pick which one is the best. In this paper, we show the result of our experiment in predicting user pairwise preferences by using their movie ratings data. We evaluated five different machine learning algorithms to predict the data in pairwise preference format. The result shows that K-Nearest Neighbour and Random Forest outperformed the other algorithms. © 2020 IEEE.

关键词： Recommender systems

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Specify of Estimation Using C4.5 Algorithm of Software Project Estimation at the Point of Sales Application with Cocomo II 4

Specify of Estimation Using C4.5 Algorithm of Software Proje...

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4th International Conference on science and Technology, ICST 2018

作者： Novel, Kadinar Sfenrianto, Sfenrianto Gata, Windu Nainggolan, Kaman Wahyudi, Mochamad Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Master of Computer Science Postgraduate Programs STMIK Nusa Mandiri Jakarta Indonesia

ISBN: (纸本)9781538658130

In software development, it is required an appropriate estimate. One of the most commonly used software project estimation models is Constructive Cost Model(COCOMO II). The model is often used to obtain accurate results in estimating important factors such as cost and human resources. However, to obtain the more accurate estimation results, this study proposes a C4.5 algorithm based on COCOMO II estimation results. In this study, software project estimates are used in the Point of Sales (POS) applications. Based on these data with COCOMO II method, it is estimated that the schedule, staff, and cost are also specifying estimation from the result of COCOMO II using a C4.5 algorithm. The accuracy of the estimation results is around 90% with Algorithm C4.5. The value can be used as a reference for the development of the next POS software project. © 2018 IEEE.

关键词： Decision trees

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Fuzzy modeling with genetic algorithms

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computerS AND ARTIFICIAL INTELLIGENCE 1997年第3期16卷 275-293页

作者： Wuwongse, V Veluppillai, S Computer Science and Information Management Program School of Advanced Technologies Asian Institute of Technology Bangkok Thailand

Recent applications of fuzzy control have created an urgent demand for fuzzy modeling techniques. Several methods for identification of fuzzy models from numerical input-output samples have been proposed. Among them, Sugeno and Yasukawa's method [6], which employs fuzzy c-means clustering, holds significant promises. This paper improves the method of Sugeno and Yasukawa. Identified fuzzy models are tuned at various stages by means of genetic algorithms, i.e., the numbers of input variables and rules are reduced and membership function parameters are adjusted. The technique, when applied to a nonlinear system, demonstrates its efficiency in a comparison with the original method of Sugeno and Yasukama.

关键词： fuzzy modeling fuzzy c-means clustering genetic algorithms

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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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Study of runway crosswind and tailwind potential for airport sustainability: A study of Soekarno Hatta airport, Cengkareng, Indonesia 2

Study of runway crosswind and tailwind potential for airport...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Sardjono, W. Zulkarnain Kusnoputranto, H. Soesilo, T.E.B. Utama, D.N. Sudirwan, J. Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management BINA NUSANTARA University Jakarta11480 Indonesia Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Faculty of Public Health University of Infonesia Jakarta Indonesia Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

Airport runway designs must consider wind climatology to reduce the potential for crosswind and tailwind events that can cause accidents and aircraft delays. The large potential of crosswind and tailwind on a runway at the airport is very detrimental to aircraft passengers and airlines. Therefore, it is necessary to know the potential of crosswind and tailwind on the runway of Soekarno Hatta Airport and find the right parameters for the approximate direction and speed of the wind on the airport runway. Analysis was carried out using the direction and wind speed data from the Soekarno Hatta meteorological station in 2007-2017 to determine the potential for crosswind and tailwind on the runway of Soekarno Hatta airport and run a Weather Research and Forecasting (WRF) weather model to determine the parameterization of the right weather model for wind forecast at Soekarno Hatta airport. The highest maximum crosswind component in the 2007-2017 period occurred in August 30.53 knots, while the highest maximum tailwind of 25 knots occurred in January for a 250-degree runway and 24 knots occurred in August for a 070-degree runway. The potential for crosswind and tailwind is different every month. The scheme produces forecasts of wind direction and speed with a strong level of correlation with observations of wind direction and speed from the Soekarno Hatta meteorological station, the correlation value is 0.61. The most significant social impact of plane delays is time loss for passengers. While the economic impact on one of the crosswind events at Soekarno Hatta airport was an economic loss for one airline of US $ 43,392. © Published under licence by IOP Publishing Ltd.

关键词： Losses

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Performance Evaluation of Oversampling Methods on Deep Learning-Based Skin Cancer Classification

Performance Evaluation of Oversampling Methods on Deep Learn...

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2023 International Seminar on Application for Technology of information and Communication, iSemantic 2023

作者： Supriyanto, Catur Salam, Abu Zeniarja, Junta Wijaya, Adi Universitas Dian Nuswantoro Bachelor Program in Informatics Engineering Faculty of Computer Science Semarang Indonesia Universitas Indonesia Maju Department of Health Information Management Jakarta Indonesia

ISBN: (纸本)9798350339215

The field of dermatology faces considerable challenges when it comes to early detection of skin cancer. Our study focused on using different datasets, including original data, augmented data, and SMOTE oversampled data, to identify skin cancer. Our dataset consisted of images of skin lesions from the MNIST Skin Cancer dataset (HAM 10000), including samples of both cancerous and benign cases in the dataset. We employed data augmentation to expand the dataset's size and increase the diversity of skin lesion features. Furthermore, to tackle class imbalance in the dataset, we applied the SMOTE oversampling technique to generate synthetic samples for the under-represented group. With the original, augmented, and SMOTE oversampled datasets, we trained a Convolutional Neural Network (CNN) model. The performance of the model was evaluated using accuracy, recall, precision, and F1-score. The comparison between the results obtained from the original data, augmented data, and SMOTE oversampling data clearly revealed distinctions in performance. Our findings clearly demonstrate that employing data augmentation and SMOTE oversampling can significantly enhance the efficacy of skin cancer detection. © 2023 IEEE.

关键词： Neural network models

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