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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis 6

Mapping the Scientific Landscape of Integrated Scheduling To...

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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Putri Ardyanti, Anak Agung Ayu Xie, Zhiqiang Karnyoto, Andrea Stevens Pardamean, Bens Estiyanti, Ni Made School of Computer Science and Technology Harbin University of Science and Technology Harbin150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, computer Science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions. © 2025 The Authors. Published by Elsevier B.V.

关键词： Job shop scheduling

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Decision Support Framework: Integrating Analytic Hierarchy Process with Support Vector Machine and Top-K Algorithms

Decision Support Framework: Integrating Analytic Hierarchy P...

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IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

作者： Mervin Jommel T. De Jesus Melvin A. Ballera Graduate Program Technological Institute of the Philippines Manila Philippines Department of Computer Science Technological Institute of the Philippines Manila Philippines

ISBN: (数字)9798350353464

ISBN: (纸本)9798350353471

Effective recommendation systems are essential for supporting decision-making in various fields in this age of abundant information. This paper presents a novel framework for a Modified Recommender Algorithm that combines Top-K and Support Vector Machine (SVM) algorithms with the Analytic Hierarchy Process (AHP). Traditional decision-making frameworks such as AHP are susceptible to subjectivity and inconsistencies, necessitating innovative approaches to improve their reliability and effectiveness. The objective is to improve recommendation systems' efficacy and precision by integrating sophisticated machine-learning techniques with resilient decision-making approaches. The proposed framework establishes the hierarchical structure of decision elements and prioritizes alternatives according to user preferences by utilizing AHP, a potent multi-criteria decision-making tool. Support Vector Machine (SVM) is then used as a text classification model to enrich the feature space for recommendations by classifying textual data into pertinent classes. In addition, the framework applies Top-K Algorithms to select the most pertinent alternatives based on SVM classification output, thereby refining the recommendation results. Top-K Algorithms improve overall recommendation accuracy and relevance by iteratively filtering and ranking alternatives. This research advances the field of data science by providing a thorough framework that combines innovative machine learning techniques with conventional decision-making methodologies to address the challenges of recommendation systems in complex and dynamic environments.

关键词： Support vector machines Machine learning algorithms Heuristic algorithms Text categorization Refining Analytic hierarchy process Machine learning

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Modified Recommender Algorithm based on Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Methodology with Entropy Weighting Method (EWM)

Modified Recommender Algorithm based on Technique for Order ...

引用

Science and Information Technology in Smart Administration (ICSINTESA), International Conference of

作者： Mark Reden S. Pacaon Melvin A. Ballera Graduate Program Technological Institute of the Philippines Manila Philippines Department of Computer Science Technological Institute of the Philippines Manila Philippines

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

This research exhibits an algorithm adapted from the Technique for Order of Preference by Ideal Solution (TOPSIS) methodology, integrating the Entropy Weighting Method (EWM) for objective and efficient recommendation processes. Decision-making methodologies have indicated gaps of subjective influence affecting performance values on several implementations with additional limitations on the flexibility of handling complex problems that require multiple factors while maintaining an acceptable running time. The study takes this into account and formulates an adaptable and efficient framework that offers objective and data-driven recommendations for diverse situations. Future endeavors include subjecting the framework to real-life scenarios and testing its effectiveness.

关键词： Decision making Entropy Information technology Testing

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Courier System with Data Analyzer Using Time Series Forecasting and Recommender Model

Courier System with Data Analyzer Using Time Series Forecast...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Shawe G. Belano-Regla Jheanel E. Estrada Graduate Program Technological Institute of the Philippines Manila Philippines College of Computer Studies Technological Institute of the Philippines Manila Philippines

ISBN: (数字)9798350389692

ISBN: (纸本)9798350389708

A traditional courier service provider in the Philippines operating region-wide, is commended to innovate their business process by leveraging technologies in response to digital civilization. A courier system curated to meet the business needs of the courier service provider is developed in this study. The Scrum methodology was followed in developing the system. It incorporates descriptive analytics, forecasting and recommendation analytics to assist the top-level management in decision making. Notably, the FastAPI framework was used to develop the recommender model and implement time series forecasting using ARIMA. The designed system was evaluated by 66 stakeholders, it gained a mean average score of 4.43, indicating that user expectations towards the system's quality are highly accepted.

关键词： Time series analysis QR codes Predictive models Data models Real-time systems Stakeholders Resource management Forecasting Protection Business

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A Review on Collaborative Filtering Using Geographical Information 8

A Review on Collaborative Filtering Using Geographical Infor...

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8th International Conference on Information Technology and Digital Applications, ICITDA 2023

作者： Pohan, Husni Iskandar Sutoto Heryadi, Yaya Prabowo, Harjanto Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Indonesian Hospital Accreditation Commision Jakarta Indonesia Jakarta12960 Indonesia Binus Business School Doctor of Research in Management Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350344691

Since the corona pandemic, many internet users have maximized their interactions with the internet to minimize face-to-face meetings. As a result, many collaborative filtering algorithms, which are part of recommender systems, have been optimized so that users can obtain the best results. Collaborative filtering is an approach to providing recommendations that relies on the interactions and preferences of past users. Essentially, recommendations are generated by considering how users with similar preferences and behaviors have interacted. There are two primary forms of collaborative filtering: user-user and item-item. User-user collaborative filtering suggests recommendations based on users who share similar preferences with the current user. On the other hand, item-item collaborative filtering suggests recommendations based on items that are frequently selected together by other users. Both types of collaborative filtering rely on user interaction and preference data to deliver effective results. The latest trend related to collaborative filtering involves the use of geographic information. This paper aims to map the research developments related to collaborative filtering with geographic information in recent years, including the algorithms used, implementation issues, and challenges faced. Our hope is that this research can provide an overview of where this technology is heading. © 2023 IEEE.

关键词： Recommender systems

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Metrics and Red Teaming in Cyber Resilience and Effectiveness: A Systematic Literature Review

Metrics and Red Teaming in Cyber Resilience and Effectivenes...

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International Conference on Telecommunications (ICT)

作者： Semi Yulianto Benfano Soewito Ford Lumban Gaol Aditiya Kurniawan Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program. Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

Rising cyber risks have compelled organizations to adopt better cyber-protection measures. This study focused on discovering crucial security metrics and assessing the function of red teaming in enhancing cybersecurity defenses against novel cyber hazards. The PRISMA standard considered nine core research works issued between 2014 and 2023. The inclusion of red teaming best practices can significantly enhance cybersecurity architecture. Accurate simulations of cyber threats during red teaming exercises help identify vulnerabilities, and actively embracing red teaming can amplify an organization's capacity to repel future cyber assaults. Researchers and practitioners can utilize the study's insights to pioneer novel security solutions. Combining red teaming methodologies with relevant metrics is essential for enhancing cybersecurity posture. The study's discoveries grant companies a priceless benefit in navigating the rapidly changing cyber threat environment and reinforcing their cyber protection mechanisms.

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Recurrent Neural Network-based Models as Bahasa Indonesia-Sundanese Language Neural Machine Translator

Recurrent Neural Network-based Models as Bahasa Indonesia-Su...

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2023 International Conference on computer Science, Information Technology and Engineering, ICCoSITE 2023

作者： Wijanarko, Bambang Dwi Heryadi, Yaya Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota BINUS Online Learning Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Bina Nusantara University Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

Sequential data are available in many domains including weather observation data, stock price, gene sequence, and many others. Sequential data processing is very instrumental as a solution to a variety of downstream tasks in Natural Language Processing such as language translation. Translating a language to another language has become instrumental when peoples interact with other people who speak a different language. However, language translation is not an easy computation task when there is a language-resource gap. This paper presents some empirical results from the exploration of the Recurrent Neural Network (RNN), the Gated Recurrent Unit (GRU), the Long Short-term Memory (LSTM), and the Bidirectional Long Short-term Memory (Bi-LSTM) models as machine translation models from Bahasa Indonesia to the Sundanese language. These empirical results show that the Bi-LSTM achieved the highest performance (0.95 average training accuracy and 0.92 average testings BLEU score) compared to the RNN (0.93 average training accuracy and 0.91 average testings BLEU score), the GRU (0.88 average training accuracy and 0.89 average testings BLEU score), and the LSTM (0.92 average training accuracy and 0.91 average testings BLEU score) models. These results validate some previously reported studies that claim the Bi-LSTM model potentially outperforms the other recurrent neural network-based models when it is used to process sequence datasets. © 2023 IEEE.

关键词： Long short-term memory

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Intelligent Digital Enterprise Architecture: Perspectives, Trends, and Technologies 9

Intelligent Digital Enterprise Architecture: Perspectives, T...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Afriliana, Nunik Gaol, Ford Lumban Supangkat, Suhono Harso Ranti, Benny Computer Science Bina Nusantara University Computer Science Department Binus Graduate Program Jakarta11480 Indonesia Smart Cities and Communities Innovation Center Institut Teknologi Bandung Bandung40312 Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Nowadays, many companies, industries, and organizations deal with digital disruption issues. They have to deal with it and take the initiative properly to keep their sustainability. Initiating a digital transformation by creating intelligent digital systems is one of many initiatives that could be considered to overcome these issues. Developing an intelligent digital system will maintain a company's performance, efficiency, and compliance. Numerous organizations are willing to create an intelligent digital system for their governance. However, they do not have sufficient knowledge on how to do it, including its enterprise architecture. Knowledge of enterprise architecture is an important part of properly developing an intelligent digital system. This research aimed to conduct a literature review to determine the perspective of the enterprise architecture model in intelligent digital system development. The second goal is to find recent trends and technology in intelligent digital enterprise architecture. Theoretically, it gives a contribution to providing a new perspective of more intelligent Enterprise Architecture with its trends and technologies compared to the old paradigm. Practically, it will contribute to providing an overview of how an enterprise could align the IT and business perspectives in building an intelligent enterprise with its cognitive characteristics © 2022 IEEE.

关键词： Architecture Digital transformation Bibliographies Buildings Companies Market research Sustainable development

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Leveraging Social Learning for Improved Cybersecurity Maturity: A Case Study Using the NIST Framework

Leveraging Social Learning for Improved Cybersecurity Maturi...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Marcel Meyliana Hendric Spits Warnars, Harco Leslie Nugraha Mursitama, Tirta BINUS Graduate Program Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Krida Wacana Christian University Information Systems Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta Indonesia BINUS Business School Bina Nusantara University Management Department Jakarta Indonesia

ISBN: (纸本)9798350379839

This research shows that social learning can be used to increase an organization's cybersecurity maturity level. Using a literature study and case study approach. Literature studies are used to identify social learning's key success factors (KSF) and challenges in general. Then, the case study was performed in the context of assessing the maturity level of information security using the NIST Cybersecurity framework at ABC Software House, a small-scale software development company in Indonesia. Assessment activities are performed through FGDs which then also identify the most relevant social learning' KSF to increase the organization's information security maturity level. Next, referring to the selected KSF, a process of identifying and mapping social learning' challenges was carried out. The integration of social learning can help organizations gain better focus and understanding in nontechnical contexts to increase their maturity level. This research highlights that integrating social learning with the NIST cybersecurity framework can provide organizations with better focus and perspective for formulating non-technical solutions. This study also enriches the existing literature on social learning in cybersecurity and offers practical insights for organizations looking to improve their cybersecurity resilience. © 2024 IEEE.

关键词： case study cybersecurity maturity level NIST social learning

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Deaf Helper Mobile Application for Interaction of Hearing Disorders Communities 2

Deaf Helper Mobile Application for Interaction of Hearing Di...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Setyawan, Adrian Naphan, Gilbert Xervaxius Dynata, Kevin Friry, Jovano Edmund Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Information System Information Systems Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

People with hearing loss in this world have not received much serious attention from the authorities. This makes these sufferers confused in choosing learning media to interact with and isolated from their social environment. This application was created to help people with hearing loss to be noticed and understood from the way they communicate using sign language through the mobile application called Assistant for the Deaf, which has many features such as registration, interactive videos, sign language translator, forums, customer service, library, information, history, events, donations, and shops. The application is designed using use case diagrams and class diagrams modeling the database, and the implementation used Android Studio and MySQL database. © 2022 IEEE.

关键词： Audition

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