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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Chandra, Yakob Utama Prabowo, Harjanto Gaol, Ford Lumban Purwandari, Betty School of Information Systems Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia BINUS Business School Bina Nusantara University Doctor of Research Management Management Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350339543

The proliferation of data has become an inevitable consequence of the digital age as individuals across all domains increasingly rely on data for various purposes. Both companies and governments have a significant need for data. However, the sheer volume and complexity of this data, along with the potential risks associated with mishandling it, necessitate the establishment of a framework known as data governance. The primary objective of this research paper is to examine the factors that contribute to the effective implementation and utilization of Data governance. This study employs qualitative methods and adopts a systematic literature review approach to address the research inquiry: 'What are the important factors that determine the utilization of data governance technology?' Through the systematic literature review, a total of 41 key factors were identified from 20 research literatures that have been found to significantly impact the effective implementation of data governance. There are thirteen primary technological factors that hold significance in the realm of data governance. These factors encompass technology, application and use, storage of data, sharing, archiving, and preservation, big data algorithmic systems, data flow, deletion, diversity of data, mechanisms, size of data, control, and data integrity. © 2023 IEEE.

关键词： Digital storage

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Integration of the Use of Conventional Technology Towards Smart Home Technology for People in the City of Jakarta 10

Integration of the Use of Conventional Technology Towards Sm...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Oktavia, Tanty Lintang, Febian Wijaya Ongko, Gerald Christian Benedicta, Griselda Valerie Michelle Sembiring, Vieri Aska Juneio Ananta, Zaldy Raditya Hosoda, Takaaki Gaol, Ford Lumban Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339543

Smart Home technology offers technological concepts that can be controlled through smart devices to make it easier for the community. Therefore, smart home technology is starting to seize the home electronics market in Indonesia, especially in the city of Jakarta. This study aims to determine the integration of conventional technology into smart home technology for people in Jakarta. The research model in this study uses UTAUT2 which analyzes nine variables, namely Perceived Usefulness, Perceived Cost, Perceived Ease of Use, Social Influence, Perceived Compatibility, Trust, Perceived Pleasure, and Effort Expectations, Intention to Use Smart Home Technology. After the responses were received, data analysis was carried out using the PLS-SEM approach with the SmartPLS application. The results of this study show that there are many people who live in Jakarta who are helped by the presence of smart home technology. However, there are some people who don't really know how to use a smart home because of a lack of knowledge about this technology. © 2023 IEEE.

关键词： Technology transfer

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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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Scheduling Production in the Flexible Packaging Industry Using Mathematical Models and Genetic Algorithms

Scheduling Production in the Flexible Packaging Industry Usi...

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2023 International Conference on Informatics Engineering, science and Technology, INCITEST 2023

作者： Tarigan, Masmur Gaol, Ford Lumban Mauritsius, Tuga Budiharto, Widodo Esa Unggul University Bina Nusantara University Computer Science Department / Computer Science Graduate Program Jakarta Indonesia Binus Graduate Program Bina Nusantara University Computer Science Department Jakarta Indonesia Management Bina Nusantara University Department of Information System Jakarta Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350317862

Minimizing time wastage is a crucial objective for all production operations. Reliable manufacturing scheduling The objective is to mitigate time-based production waste caused by excessive processing, waiting, and transportation. Industry 4.0 promotes technological innovation across all industrial sectors to increase efficiency and effectiveness while preserving high competitiveness. The implementation of artificial intelligence in Industry 4.0 is expected to result in a reduction in time wastage. Non-dominance sequencing genetic algorithms (NSGA), genetic algorithms (GA), and evolutionary algorithms (EA) are the three most common scheduling approaches, according to literature-indexed research summaries from the past five years. The examination of production scheduling in the flexible packaging business, which involves the utilization of different machines and processes and is produced on demand, had not been conducted before in this study. A mathematical scheduling model will be developed in this research to ascertain the shortest production time span in the flexible packaging industry. As a form of technological innovation, this mathematical model will be utilized in experiments employing a genetic algorithm approach. For the genetic algorithm to generate a minimum makespan in the flexible packaging industry's production scheduling process. © 2023 IEEE.

关键词： Genetic algorithms

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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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Monitoring Applications for Vehicle based on Internet of Things (IoT) using the MQTT Protocol 8

Monitoring Applications for Vehicle based on Internet of Thi...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Nurudin Sukmandhani, Arief Agus Zarlis, Muhammad Computer Science Department BinusOnline Learning Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Monitoring of vehicle conditions is needed as one of the securities in driving because one of the accident rates is negligence in checking the condition of the vehicle. This study aims to help reduce the level of accidents and increase human awareness for vehicle conditions, especially minibus type vehicles. The system works to provide information on the condition of vehicles sourced from the Engine Control Unit (ECU). ECU data cars are obtained by SNIP traffic broadcast message and ask for data directly at the ECU. The car can provide vehicle information using a Canbus communication protocol through the OBD-II socket. Vehicle information can be seen by users through the website in real time. Based on the evaluation from the user side, this system provides ease of monitoring vehicle conditions because it can be accessed via the internet using various kinds of devices. © 2023 The Authors. Published by Elsevier B.V.

关键词： Blackbox ECU OBD-II Sstem Logging

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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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Development of Key Performance Indicators in e-Learning Implementation in Higher Education Institutions 8

Development of Key Performance Indicators in e-Learning Impl...

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

ISBN: (纸本)9798350326093

Companies or organizations usually use key performance indicators (KPI) as indicators to determine their performance. The company's performance achievements are reflected in the set indicators that will describe the overall performance, as well as higher education institutions can also set key performance indicators, to see their performance achievements. The use of e-learning as a tool to support teaching and learning processes to be more effective and efficient is an example of which performance needs to be measured. This article discusses how the process of developing key performance indicators is carried out through the stages of designing questionnaires and distributing questionnaires to students, data is processed using the method of factor analysis to obtain the main indicators determining performance and the method of regression analysis is also used to build performance models. obtain KPI determinants, and then develop KPI models. The results show that there are indicators of sharing knowledge, managing knowledge, understanding knowledge, and utilization knowledge as performance measurement indicators. © 2023 IEEE.

关键词： Regression analysis

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Deep-Learning Approach for An Analysis of Real-estate Prices and Transactions

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IEEE Access 2025年 13卷 89248-89265页

作者： Yang, Cheng-Hong Lee, Borcy Lin, Yu-Da Tainan University of Technology Department of Information Management Tainan Taiwan National Kaohsiung University of Science and Technology Department of Electronic Engineering Kaohsiung Taiwan Kaohsiung Medical University Ph.D. Program in Biomedical Engineering Kaohsiung Taiwan Kaohsiung Medical University School of Dentistry Kaohsiung Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Kaohsiung Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

Research on the study of houses, condominiums and buildings in Taiwan’s metropolitan areas continues to be an important area of research. In real estate forecasting and analysis, methods such as statistical analysis and questionnaire data collection are widely used. However, when multidimensional data is considered, these methods are time-consuming and inadequate. This study aimed to build a real estate forecasting model that can adapt to a changing environment. Data were collected from public government databases, the collected data were standardized for accurate clustering, an appropriate data clustering algorithm was applied to the standardized data, and cross-statistical analysis was performed to verify the adopted algorithm. We used a deep learning based on autoencoder algorithm to increase the accuracy of the clustering analysis. A double-bottom map particle swarm optimization (DBM-PSO) clustering algorithm was then used to determine the optimal clustering solution. Cluster analysis and deep learning were conducted on data collected from public websites to understand the factors that led to the sustained increase in housing prices in Taiwan over the past decade. The results of this study indicate that three key factors—the number of real estate transactions, the average unit price of real estate transactions, and the building material and construction index—significantly affected real estate prices in Taiwan. Our results could help researchers and governments to focus on specific aspects of real estate development without being influenced by other related factors. In addition, the relationships between real estate trends and the aforementioned three key factors were determined to obtain valuable information that can enable the Taiwanese government to regulate the property market and prevent excessive growth. The framework proposed in this paper allows researchers and governments to focus on specific aspects of real estate development without being influenced b

关键词： Houses

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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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