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Enhancing Road Segmentation in Satellite Images via Double U-Net with Advanced Pre-Processing

Enhancing Road Segmentation in Satellite Images via Double U...

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International Conference on Informatics and Computing (ICIC)

作者： Raden Bagus Muhammad Adryanputra Adhy Wijaya Wahyono Undergraduate Program in Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Roads play an important role in people’s lives by providing access to essential facilities such as schools and hospitals, thereby increasing people’s productivity. The use of satellite imagery and computer vision technology can speed up and improve the efficiency of road map creation. Deep learning methods such as U-Net have been used for road segmentation from satellite images, but the results have yet to be optimal. This study aims to examine the performance of DoubleU-Net and the effect of image pre-processing in satellite image-based road segmentation. This research implements the DoubleU-Net deep learning model for road segmentation based on satellite images. Pre-processing methods such as rotating augmentation, contrast stretching, and edge enhancement are applied to increase the contrast value and clarify the edges in the satellite images used. The results show that combining the two U-Net models into a DoubleU-Net model results in a significant improvement in the IoU and dice coefficient values, achieving an average increase of $\mathbf{2 \%}$ and integrated with image processing, the model performance experiences an average increase in IoU and dice coefficient values of $\mathbf{2 - 4} \%$. The highest performance was achieved by the DoubleU-Net model with rotating augmentation pre-processing, resulting in an IoU performance value of $\mathbf{4 5. 9 9 \%}$ and a dice coefficient performance of $\mathbf{6 1. 1 2 \%}$.

关键词： Deep learning Productivity Image segmentation computer vision Smoothing methods Roads Image edge detection Semantic segmentation Satellite images Remote sensing

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Evaluation of EIRLYS's E-Commerce Website from a User Experience Perspective using a User Experience Questionnaire (UEQ)

Evaluation of EIRLYS's E-Commerce Website from a User Experi...

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2022 International Conference on Electrical Engineering and Informatics, ICELTICs 2022

作者： Gabrila, Amara Nova Ramadhani, Mirza Fadila, Fujishiro Larasati Izdihar, N.S. Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia Bina Nusantara University Computer Science School of Computer Science Jakarta11480 Indonesia

ISBN: (数字)9781665487665

ISBN: (纸本)9781665487665

Fashion is one of the industrial sectors that never die. However, the majority of brands in this industrial sector are slowly forgetting the existence of Indonesian culture. EIRLYS is a company engaged in the fashion industry that produces clothing with the theme of Indonesian culture. Customers will be able to get clothes that have elements of Indonesian culture but still have a relaxed and informal impression. Clothing from EIRLYS emphasizes the principles of simplicity, minimalism, and elegance. These three principles want to be carried out in the design and user experience of the EIRLYS website to provide convenience for customers in transacting. Almost all industries, whether large, medium, or small, have used technology to promote their products in various ways, including using e-commerce websites. However, to ensure that EIRLYS has provided the best service through its website, it is important to know whether EIRLYS has met the overall User experience (UX) dimension. User experience Questionnaire (UEQ) is a technique that will be used to assess and test whether EIRLYS has met the expectations of users based on the User experience dimension before it can be used by customers. Based on the results of the user experience questionnaire filled out by EIRLYS users, it can be seen that EIRLYS has been able to meet user needs and expectations from all dimensions, ranging from attractiveness, perspicuity, efficiency, accuracy, stimulation, and novelty. © 2022 IEEE.

关键词： Websites

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Video Quality Indicators for Video-Based Learning System in Higher Education 23

Video Quality Indicators for Video-Based Learning System in ...

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9th International Conference on Frontiers of Educational Technologies, ICFET 2023

作者： Zulkarnain, Novan Prabowo, Harjanto Gaol, Ford Lumban Isa, Sani Muhamad Computer Science Department BINUS Graduate Program Computer Science Information System Bina Nusantara University Indonesia Department School of Information System Bina Nusantara University Indonesia Management Department BINUS Business School Undergraduate Program Information System Department School of Information System Bina Nusantara University Indonesia

ISBN: (纸本)9798400707353

Higher education worldwide has adopted Video-Based Learning (VBL) over the past decade. They have tried to build a VBL system to improve services to students. However, the researcher's topic was not fully explored, especially in making the video itself. What features are mandatory and must be considered in making a video lecture to increase student engagement. A systematic review of the literature (SLR) is a way to identify these features. This study provides a critical analysis of the current research in VBL over the last five years (2017 - 2021). It presents a general trend examining 1336 journals and many literary works related to VBL design in Higher Education, selected through a stepwise process based on PRISMA Framework guidelines, using pre-defined selection criteria. We carefully selected 32 journals and found 22 features referring to the Lecture Video Design succession. © 2023 ACM.

关键词： Learning systems

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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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Multiclassifier for Aspect-Based Sentiment Analysis on Indonesian Reviews of Kredit Pintar Online Lending App

Multiclassifier for Aspect-Based Sentiment Analysis on Indon...

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International Conference of Information and Communication Technology (ICoICT)

作者： Nanda Yuniar Aina Musdholifah Undergraduate Program in Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350363432

ISBN: (纸本)9798350363449

Aspect-based sentiment analysis is carried out to determine user sentiment's polarity while still considering the aspects of the discussion so that all information in the reviews can be represented. The multiclassifier in this research means that two classifiers are used, the first is an aspect classifier to perform aspect classification, and the second is a sentiment classifier to perform sentiment classification based on its aspect. Two approaches were studied according to their classification work, namely, individual model in the form of an aspect classification and sentiment classification based on the aspects individually and sequentially model by testing the aspect and sentiment models sequentially. This study evaluates the performance of Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC) algorithms and their combination in sequential testing. In addition, to overcome imbalance dataset, the use of oversampling types is also compared. In the individual approach, the SVM model with random oversampling showed the best performance with average accuracy, precision, recall, and f1 score of 92%, 86%, 80%, and 83% for the aspect model and 86%, 81%, 80%, and 80% for the sentiment model, respectively. While in the sequential approach, the combination of SVM-SVM with oversampling shows the best performance with an average accuracy, precision, recall, and f1-score of 79%, 56%, 50%, and 53%, while the performance of other model combinations is only in the maximum range of 77% accuracy, 55% precision, 51% recall, and 52% f1-score.

关键词： Support vector machines Sentiment analysis Accuracy Reviews Vectors Bayes methods Information and communication technology Classification algorithms Testing

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Optimizing Big Data Implementation to Create Business Value and Architecture Proposed in the Banking Industry: A Systematic Review

Optimizing Big Data Implementation to Create Business Value ...

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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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The Transfer Learning Influence on YOLO v8 Performance for Motorbike Detection 9

The Transfer Learning Influence on YOLO v8 Performance for M...

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Pangestu, Gusti Aziz, Baskoro Pratama, Febby Candra Pumomo, Agung Puspitasari, Chasandra Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University School of Design Interior Design Department Jakarta Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Enterpreneurship Department Jakarta Indonesia

ISBN: (纸本)9798350370126

The number of motorbike theft case in Indonesia has increasing rapidly. This phenomenon led to the increasing of the criminal number especially motorbike theft case. Nowadays, the use of CCTV (Closed Circuit Television) camera has been widely applied. Nevertheless, CCTV does not has the ability to prevent criminal acts such motorbike theft case. Therefore, there is a need of a technology based to prevent motorbike theft acts. This research proposed an initial research of motorbike theft detection system that focused on the process of motorbike detection using Deep Learning approach. In this research, the YOLO architecture was utilized to detect the motorbike object inside an image frame. There are two testing scenarios for motorbike detection process, using trained model, and using pre-trained model. The trained model obtain better result rather than using pre-trained model by achieving 0.93 of its accuracy that proven the YOLO v8 model are working well especially when it is applied with transfer learning process for its based model. © 2023 IEEE.

关键词： Deep learning

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Recommendation News for Joumalist Based on Twitter Data Using CNN 6

Recommendation News for Joumalist Based on Twitter Data Usin...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Harvy, Ikrar Girsang, Abba Suganda Saragih, Melva Hermayanty Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

Getting the update news fast is important for journalist. This study uses Twitter data which is fast and rich information for get the update news and useful for journalist. This study starts from collecting data from Twitter, then predicting the category of tweet using convolution neural network (CNN) algorithm. With convolution neural network data, Twitter can categorize 10 news categories that mention news to official Twitter media on Twitter social media. Scenario data in predicting news by dividing the data based on 70% training, 15% validation, and 15% testing. Then the data is converted into vector form where the convolution neural network predicts the data in vector form. The results show that, the convolution neural network is able to conduct the good performance based on the values of accuracy, precision, recall and f1 score. It also compares by the other methods. © 2022 IEEE.

关键词： classification news convolution neural network deep learning journalist Social media

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Practical Methods for the Embroidery Problem 33

Practical Methods for the Embroidery Problem

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33rd Canadian Conference on Computational Geometry, CCCG 2021

作者： Tran, Michelle Computer Science Undergraduate Program University of Colorado Boulder United States

We consider the problem of optimizing thread usage while embroidering a given pattern denoted by a Euclidean graph G. A valid embroidery of a pattern is described as a closed tour with alternating front and back edges, each with an associated weight (which, due to the Euclidean embedding, is equivalent to the distance between vertices). We explore various options for calculating exact and approximate solutions, and analyze the feasibility of each in practice. © 2021 Meng He and Don Sheehy.

关键词： Textile printing

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Trend Intelligent Tutoring System 2018-2022 : Systematic Literature Review 3

Trend Intelligent Tutoring System 2018-2022 : Systematic Lit...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Suwita, Jaka Prabowo, Harjanto Hendric Spits Warnars, Harco Leslie Meyliana, Meyliana Binus Graduate Program Computer Science Bina Nusantara University Departement of Computer Science Jakarta11480 Indonesia Stmik Insan Pembangunan Department of Information System Tangerang15810 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)9798350381931

ITS is a method of teaching that uses technology to give lessons without the need for an instructor to be there. A systematic literature review (SLR) was conducted in this research to identify the components of an intelligent tutoring system, and the results are presented. The method used in this literature review is the prism method. The steps in the prism method are slr protocol, search for literature, select literature, summarize evidence and disseminate results. The slr protocol stage, it consists of determining a research question, searching for scientific reference sources with the keyword intelligent tutoring system, then sorting out the appropriate articles and making final conclusions. This article gives a detailed look at how the intelligent tutoring system changed over time during the pandemic epoch. Our contribution is complete information on the components of ITS in times of epidemic at universities, with the goal of improving their learning and practical use of the technology. © 2024 IEEE.

关键词： Prisms

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