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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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Machine Learning Implementations in Childhood Stunting Research: A Systematic Literature Review 8

Machine Learning Implementations in Childhood Stunting Resea...

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

作者： Rahutomo, Reza Elwirehardja, Gregorius Natanael Isnan, Mahmud Asadi, Faisal Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Binus Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Childhood stunting is a condition anticipated to affect the growth potential of children under the age of five. With numerous stunting researches that have been conducted, stunting datasets are now widely available to facilitate stunting research. This provides an opportunity to implement machine learning (ML) principles to produce a broader insight or a novel technique in stunting prediction. A systematic literature review is necessary to discover the landscape of machine learning implementation in the application domain as a preliminary study for creating an effective research roadmap. This paper presents a systematic literature review (SLR) of 22 curated manuscripts that focuses on identifying the ML models applied in stunting research, as well as the datasets used in such studies that were published during 2017-2022. The SLR process found that ML principles have been applied in stunting research since 2017, and the diversity of ML implementation has become more varied in 2021-2022. In terms of ML models, XGBoost and Random Forest are recognized as the two most utilized models, and stunting prediction is the most common ML implementation. The majority of stunting research utilizing ML has been conducted in Indonesia. Although national survey data has been the most commonly utilized dataset in stunting research, researchers in Indonesia have shown a preference for utilizing data from regional or independent surveys. This study will be followed by developing a classifier model for stunted children using XGBoost and Random Forest algorithms. The model will be trained on a dataset generated from StuntingDB. © 2023 IEEE.

关键词： Machine learning

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Database Design for Pre-Eclampsia Case Administration 8

Database Design for Pre-Eclampsia Case Administration

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

作者： Asadi, Faisal Elwirehardja, Gregorius Natanael Trinugroho, Joko Pebrianto Rahutomo, Reza Pardamean, Bens School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350344691

The Ministry of Health of Indonesia has referred to pre-eclampsia as one of the most severe diseases affecting women. As an urgency, it is crucial to administrate pre-eclampsia cases for disease prevention as a long-term national healthcare strategy. Regarding health science, case data was significant in developing research and innovation. However, the main problem regarding pre-eclampsia case administration is data handling, recording, and management incompetence. Hence, this research proposed a conceptual design of a database for pre-eclampsia case administration. The proposed design covered conceptual, logical, and physical design. We elaborate the concept into three concepts of pre-eclampsia disease: pre-treatment, treatment, and post-treatment. This study proposed a solution to gain more data and study pre-eclampsia disease in Indonesia. © 2023 IEEE.

关键词： Medical informatics

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Hybrid Cryptosystem with Cramer-Shoup and Spritz Algorithms for Securing Digital Documents

Hybrid Cryptosystem with Cramer-Shoup and Spritz Algorithms ...

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International Conference on Electrical, Telecommunication and computer Engineering (ELTICOM)

作者： Delisman Hulu Maya Silvi Lydia Mohammad Andri Budiman Master of Informatics Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798331531249

ISBN: (纸本)9798331531256

Symmetric algorithms offer speed but have weaknesses in key distribution, while asymmetric algorithms are secure but less efficient for encrypting and decrypting large text messages. This research aims to secure data and digital documents through the implementation of a hybrid cryptosystem that combines the Cramer-Shoup algorithm and Spritz. This research also analyzes and evaluates the effectiveness and speed of encryption and decryption, as well as the efficiency of the system in protecting various types of data, including docx and pdf document files. The methodology of this research includes a literature review, analysis of the encryption-decryption process, and performance testing of the system using the Python programming language. The speed test results show that this hybrid cryptosystem provides fast encryption-decryption times, with an encryption time of 0.002607 milliseconds for 400 characters and a decryption time of 0.001537 milliseconds, while for digital documents of the pdf file type, the encryption time is 0.424478 milliseconds and the decryption time is 0.404343 milliseconds. In addition, the use of the SHA-3 hash function has proven effective in maintaining data integrity. In conclusion, this hybrid cryptosystem offers an efficient and secure solution for protecting various types of digital data, including text and documents.

关键词： Hash functions Resistance Data integrity Scalability Portable document format Encryption Testing Python Videos Systematic literature review

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Understanding People Analytics Adoption to Support Higher Education Competitive Advantages: A Literature Review 9

Understanding People Analytics Adoption to Support Higher Ed...

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

作者： Prasetyaningtyas, Sekar Wulan Rohman, Abdul Loeis, Minaldi Mahatmaputra, Samuel Siek, Michael Binus Business School Master Program Binus University Jakarta Indonesia Business Information System Program School of Computer Science Binus University Jakarta Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

This study expects to systemically review the current investigations on the relationship of people analytics adoption to support higher education's competitive advantage. Through a systematic literature review, with the help of Publish or Perish v8 Software, the assessment chose 19 papers, then played out a descriptive analysis of the writing to address the accompanying exploration questions: 1) what people analytics implies and its significance, and 2) what can People Analytics give to higher education competitive advantage? Researchers did a far-reaching writing audit investigation to accomplish the referenced targets of the paper. Given the examination, the adoption of people analytics to support higher education competitive advantage centers around instructing and learning investigation. The level of analytics is used primarily in the descriptive and diagnostics area. The predictive and prescriptive analytics were not much discussed. The empirical papers of this people analytics range from subject matters to data storage in the library business unit. The competitive advantages were mainly discussed regarding students' specific academic prescription to career paths in higher education. © 2022 IEEE.

关键词： Digital storage

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The Adoption Model of People Analytics in Higher Education: A Soft System Approach

The Adoption Model of People Analytics in Higher Education: ...

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2022 International Seminar on Application for Technology of information and Communication, iSemantic 2022

作者： Prasetyaningtyas, Sekar Wulan Rohman, Abdul Loeis, Minaldi Mahatmaputra, Samuel Siek, Michael Binus University Binus Business School Master Program Jakarta Indonesia Binus University Business Information System Program School of Computer Science Jakarta Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

The Adoption of the People Analytics process, especially in higher education, is highly complex and should be understood by scholars. We use seven stages of soft systems methodology to contribute to a deeper understanding of The Adoption of the People Analytics process, especially in higher education as a policy issue. The research was done in one of Indonesia's most prominent private universities. The method used was an exploratory study. In-depth interviews were done to gather data. The main interviewees were all stakeholders (H.R. Director, Business Incubator Director, Research Manager, and more) related to the process. The outcomes showed the actors involved and the obstacles experienced by the actors in transforming the existing condition into the analytics one. The paper proposed a people analytics adoption model in higher education using the soft system approach. The research limitation was due to the limited research object used, so broader research using this approach is urgent to understand the model. © 2022 IEEE.

关键词： E-learning

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Disaster recovery plan implementation evaluation model at the corporation 7

Disaster recovery plan implementation evaluation model at th...

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7th information Systems International Conference, ISICO 2023

作者： Sardjono, Wahyu Perdana, Widhilaga Gia Putra, Gustian Rama Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta13220 Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

The application of information technology in addition to making internal business processes more effective and efficient, is also to improve customer service. This role is important for companies to maintain the sustainability of information systems as a strategic tool for competitive advantage so system availability is absolutely essential. Research related to the Disaster Recovery Plan (DRP) needs to be carried out to see the readiness of a corporation to build a backup system in different places and locations. By using the method of factor analysis and regression analysis to form an evaluation model, it will obtain an overview of what factors must be considered and what the current conditions are. The results of the study show that there are Core Technical DRP, Organizational Preparation, and Costing factors which are the main variables in supporting DRP readiness. The conclusion from this study, through these three new factors a mathematical model can be built as a reference for improving DRP implementation in corporations. © 2023 The Authors. Published by Elsevier B.V.

关键词： Factor analysis

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Yu, Jen-Chien Yang, Chun-Chieh Gilbert, John Reuben Liu, Rou-Jun Oyang, Yen-Jen Yang, Meng-Han National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung City807618 Taiwan National Taiwan University Master Program in Statistics Taipei106216 Taiwan National Taiwan University Department of Computer Science & Information Engineering Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan

ISBN: (纸本)9798350303780

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset. © 2023 IEEE.

关键词： Probability density function

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Fundamental Components of Microlearning for Sustainable Quality Education: A Systematic Literature Review 8

Fundamental Components of Microlearning for Sustainable Qual...

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

作者： Rahutomo, Reza Hiererra, Siti Elda Arifin, Yulyani Suprayogi, Muhamad Nanang Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Humanities Psychology Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

E-learning was disrupted by a new concept of education named microlearning that carried various digital learning materials in convenient learning paths that were customizable according to users' necessity by using digital application. The competitive advantage of microlearning has been published but caused ubiquitous bias definition. This study aims to identify and analyze fundamental components of existing microlearning research and implementations in e-learning platforms. 42 research articles from SCOPUS database were collected from 2018 to 2022. They were reviewed to discover fundamental components of microlearning that must be considered in its implementations. The result of this study uncovered 'Content's variety' the most fundamental components. In contrast, this study finds that advance technology is the least discussed but required in supporting specific usage of microlearning. Limitation of this study lies on the determination of database and keyword usage and the methodology. This study recommends to consider combination of microlearning components to concept a specialized microlearning for sustainable quality education. © 2023 IEEE.

关键词： E-learning

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Model of Customer Relationship Management Systems Evaluation Using Factor Analysis 8

Model of Customer Relationship Management Systems Evaluation...

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

作者： Sardjono, Wahyu Kristin, Desi Maya Putra, Gustian Rama Binus Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Pakuan University Computer Science Study Program Faculty of Mathematics & Natural Sciences Bogor Indonesia

ISBN: (纸本)9798350326093

Relationship with customers is one of the most crucial factors in business continuity and development. Many current businesses have started delving into Customer Relationship Management (CRM) to establish and maintain their sales and customer relationships. This research was conducted on one retail company that implements CRM but experiencing a gap in their unit sales performance between their targeted sales and the realization. This study aims to analyze the gaps causing factors using Factor Analysis Method, constructing a suitable regression model, and proposing the company's necessary strategy. The research was conducted quantitatively using a questionnaire from 264 respondents. The result of this study showed that there are five causing factors which are CRM Reliability, Underutilization of CRM, CRM Capability, CRM Unpreparedness, and Customer Relation Quality, as well as forming a regression model of the company's CRM performance. © 2023 IEEE.

关键词： Sales

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