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8th International Conference on Informatics and Computing, ICIC 2023

作者： Andy Achmad, H. Ramadhan, Arief Warnars Harco Leslie, H. Budiharto, Widodo Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Telkom University School of Computing Bandung40257 Indonesia

ISBN: (纸本)9798350342604

Car spare parts are parts of a car that consist of components that form a certain unity and function, there are some parts that are damaged more often and therefore must be replaced more often. In this research, to predict the availability of spare parts using the times series moving average prediction method with random forest. The dataset used in this research is 19,068 consisting of location, transaction number, transaction date, part number, quantity and odo-km. Distribution of spare parts classified based on recapitulation of spare part distribution is RAE=54.5541% and RSE=63.8888%, distribution of spare parts based on location is RAE=55.5541% and RSE=65.2118%, maintenance based on ODO-KM is RAE=33.0949% and RSE=41.2241 % and distribution quantity RAE=33.749% and RSE=36.2317%. The results of spare part distribution analysis using the Confusion Matrix with probability accuracy are TP Rate=0.903, FP Rate=0.067, Precision=0.911, Recall=0.903, F-Measure=0.893, MCC=0.857, ROC Area=0.983 and PRC Area=0.948. The aim of this research is to determine the factors needed to build a machine learning-based spare parts distribution model, implementation, measurement and prediction in the automotive industry in Indonesia. © 2023 IEEE.

关键词： Automotive industry

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Single and Multi-Documents Text Summarization Technologies for Natural Language Processing: a Systematic Review on Method and Dataset

Single and Multi-Documents Text Summarization Technologies f...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Sukmandhani, Arief Agus Ramadhan, Arief Abdurachman, Edi Trisetyarso, Agung Bina Nusantara University Binus Online Learning Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665468763

The summarization technologies have been increasingly used in recent decades. Those technologies are a very important part of emerging topics in computer science and engineering, such that Natural Language Processing (NLP). Several methods have been used for analysis to get good summary results. There are two types of document summaries: single document summaries and multi-document summaries. Single document summaries aim to extract information from a single document to get new and relevant summary information, while multi-document summaries extract information from multiple documents. This study focuses on the activities of the semantic literature in previous studies to obtain the basis of the widely used base methods and data sets used in this study. Data was collected from Scopus publication sources from 2019 until 2022 Q2 for analysis. Researchers use guidelines from the semantic literature method by using the basis of Kitchenham and Charters as a reference in its design. In this study, there were forty-eight articles obtained from the filtering results of several criteria used, including exclusion and quality assessment. © 2022 IEEE.

关键词： Semantics

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Protein Structure Prediction Using Dynamic Speciation Evolutionary Algorithm with Aggregated Problem Information 21

Protein Structure Prediction Using Dynamic Speciation Evolut...

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21st IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2024

作者： Parpinelli, Rafael Stubs Wojeicchowski, Nicholas Will, Nilcimar Neitzel State University of Santa Catarina Graduate Program in Applied Computing Joinville Brazil State University of Santa Catarina Computer Science Department Joinville Brazil

ISBN: (纸本)9798350356632

Protein structure prediction in three dimensions represents a fundamental challenge in Structural Bioinformatics. Leveraging problem-specific information such as fragment insertion, secondary structure, and contact maps can significantly enhance the exploration of the search space. In this study, an evolutionary algorithm is introduced, which incorporates such problem information for protein structure prediction. The proposed method employs a dynamic speciation technique alongside fragment insertion to foster population diversity. To ensure a rich variety of fragments, a fragment library is constructed using the Rosetta Quota protocol. Additionally, information from contact maps and secondary structure is integrated into two selection strategies to facilitate a more thorough exploration of the conformational search space. The results of an experimental evaluation involving 9 proteins are presented, demonstrating competitive performance compared to existing literature. Evaluation metrics include RMSD, GDT, and processing time. © 2024 IEEE.

关键词： Prediction models

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The Effect of Viewpoint Change Strategies on Multi-View Video and Audio Transmission QoE Over ICN/CCN 38

The Effect of Viewpoint Change Strategies on Multi-View Vide...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Nunome, Toshiro Takada, Yoshiyuki Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350302196

In this paper, we exploit caches on intermediate nodes for QoE enhancement of multi-view video and audio transmission over ICN/CCN by controlling the content request start timing of consumers. We assume the selected single viewpoint transmission method;a consumer receives video and audio streams of a requested viewpoint. We perform a simple experiment with two consumers. When the consumers play video and audio with the time difference, we assess the effect of cached content by the former consumer's request on the output quality of the latter consumer. We deal with two types of viewpoint change strategies for the former consumer, which affect the efficiency of cache utilization. From the assessment results, we see that cache utilization has an important factor in enhancing QoE. © 2023 IEEE.

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QoE Assessment of Audiovisual Streaming over a Full-Duplex Wireless LAN with Interference Traffic

QoE Assessment of Audiovisual Streaming over a Full-Duplex W...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Nunome, Toshiro Deguchi, Daiki Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350324174

This paper evaluates the QoE of video and audio transmission over a full-duplex wireless LAN with interference traffic through a computer simulation and a subjective experiment. We employ a simulation environment with a pair of audiovisual transmission and reception terminals and a pair of interference traffic transmission and reception ones. We investigate the effect of the transmission rate of interference traffic and communication distance in a wireless channel on the output quality of the video and audio stream at the reception terminal. We perform a subjective experiment with the output timing of video and audio obtained by the simulation. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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Classification of Alzheimer's Disease using Random Oversampling and Albumentations on Convolutional Neural Network 8

Classification of Alzheimer's Disease using Random Oversampl...

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8th International Conference on Informatics and Computing, ICIC 2023

作者： Kamardi, Calvin Laksana, I Kadek Perry Bagus Anggreainy, Maria Susan Fitriawati, Nora Yonatan, Michiko Amaya Mangkang, Tesalonika Abigail Eikwine Pengesa, Vianny Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Online Learning Information Systems Department Jakarta Indonesia

ISBN: (纸本)9798350342604

Alzheimer's Disease (AD) is a brain disorder that causes dementia and affects the memory, cognitive, and behavioral function. Early detection for AD can help to reduce the symptoms and slow down AD progression. Deep learning, particularly Convolutional Neural Network (CNN), a component of artificial intelligence, has demonstrated efficacy in resolving image-related issues and has gained widespread use in the analysis of medical images. CNN works well on large datasets, however, in imbalanced datasets, it can perform poorly by misclassifying minority classes. In this study, the random over-sampling technique is used to address the imbalance in the dataset, while Albumentations is used for image augmentation to prevent overfitting. The results demonstrate that the combination of these techniques leads to improved classification performance compared to traditional approaches. The proposed method has the potential to improve the accuracy of AD diagnosis and contribute to the development of effective treatments for this debilitating condition. © 2023 IEEE.

关键词： Convolutional neural networks

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The Effect of Bitrate Control Methods of MPEG-DASH Streaming on Multi-View Video and Audio QoE

The Effect of Bitrate Control Methods of MPEG-DASH Streaming...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Nunome, Toshiro Wakayama, Yamato Nagoya Institute of Technology Computer Science Program Department of Engineering Graduate School of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350324174

This paper investigates the effect of bitrate control methods on QoE of multi-view video and audio streaming with MPEG-DASH. We adopt three bitrate control methods for conventional single-view video streaming to the MVV-A system with MPEG-DASH. We conduct a subjective experiment changing available network bandwidth and investigate the effect of the methods on QoE. © 2023 IEEE.

关键词： Video streaming

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Social Network Analysis and PowerBI Dashboard to Determine E-Wallet Marketing Strategies 4

Social Network Analysis and PowerBI Dashboard to Determine E...

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

作者： Rita, Rita Monica, Sheila Aurelia, Miracle Girsang, Abba Suganda Puspita, Virienia Binus Business School Bina Nusantara University Jakarta11480 Indonesia Binus Graduate Program Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Graduate Program Bina Nusantara University Communication Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

The rapid growth of digital payment platforms like OVO, ShopeePay, and GoPay in Indonesia has driven the need for businesses to optimize marketing strategies by analyzing customer interactions through social media. This study leverages Social Network Analysis (SNA) and Power BI to extract insights from Twitter data, offering a comprehensive view of how these platforms engage with consumers and shape brand perceptions. By applying sentiment analysis and classification using IndoBERT results, this study aims to identify key influencers, assess the sentiment around these brands, and visualize marketing communication patterns. The integration of SNA and BI tools provides a detailed, data-driven approach to improving business decision-making in the competitive digital payment market, by utilizing them to evaluate e-wallet tweet activity and user interactions in Indonesia and identifying key periods and regions for targeted marketing. Strategies like loyalty programs and segmented campaigns are recommended to enhance user engagement, address security concerns, and maximize market reach during culturally significant periods such as Eid and the holiday season. © 2024 IEEE.

关键词： Business Intelligence Digital Wallet Marketing Strategy Social Media Social Network Analysis

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E-Government Interoperability: Provincial-Level Architecture Model to Enable Fast Healthcare Interoperability Resources (FHIR) 9

E-Government Interoperability: Provincial-Level Architecture...

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

作者： Wijayanti, Diana Urbaya, Satriawansyah Sitompul, Taufiq Adrian, Verry BINUS Graduate Program Bina Nusantara University Department of Information Systems Jakarta11480 Indonesia Program USAID Indonesia Jakarta12930 Indonesia University of Oslo Department of Informatics Oslo0316 Norway Binus Graduate Program - Doctor Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Jakarta Provincial Health Office Center of Data and Information Technology Jakarta10160 Indonesia

ISBN: (纸本)9798350390025

The process of using ICT to provide services to the public is known as the Indonesian e-Government system, or Sistem Pemerintahan Berbasis Elektronik (SPBE). The e-Government initiative in Jakarta Provincial Health Office involves enhancing collaboration among public health entities for efficient data exchange and streamlined processes, especially between the Provincial and District Health Offices, public hospitals, government clinics, and primary health care centers (Puskesmas). Achieving interoperability requires standardized protocols and a well-defined architectural model to integrate data seamlessly. This study presents a provincial-level architectural model focused on improving electronic health records interoperability, aiming to promote the adoption of the national Fast Healthcare Interoperability Resources (FHIR) health information exchange platform and enhance the integrity of health data in Jakarta. The study methodology involves conducting literature reviews, observations, and discussions with representatives from healthcare facilities to develop the e-Government architecture model and prototype of the infrastructure layer aiming to facilitate the interoperability of Electronic Health Records (EHRs) across 93 healthcare facilities, all of which are part of the SPBE users. © 2024 IEEE.

关键词： e-government

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Efficiency of Multi-Language Data Serialization for Hybrid Cloud-Edge HRIS

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Procedia computer science 2024年 245卷 28-38页

作者： Andreas Winata Haryono Soeparno Ford Lumban Gaol Yulyani Arifin Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In hybrid cloud-edge systems, data processing is distributed between cloud servers and edge servers, this makes data serialization critical for efficient data transfer between servers. This study evaluates the efficiency of multi-language data serialization of Human Resources Information System (HRIS) in a hybrid cloud-edge environment. Because lack of existing studies that specifically evaluate multi-language data serialization for hybrid cloud-edge HRIS, this study conducted a Systematic Literature Review (SLR) to get the list of current state of the art of data serialization methods and then used this result to evaluate the methods. By focusing on HRIS employee data from the employee management module, this study measures both data serialization and deserialization using performance metrics of time, data size, and CPU usage. The results indicate that no methods excel in all metrics, but FlatBuffers, Protocol Buffer, and Apache Avro can provide balanced effectivity across the metrics. The study gives valuable insight for selecting data serialization methods, architecture, and systems requirements in hybrid cloud-edge HRIS to ensure the performance efficiency of the system.

关键词： Data Serialization Human Resources Information System Hybrid Cloud-Edge Performance Metrics Employee Management

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