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Toward Digital Transformation Adoption: A Conceptual Framework from Transformational Leadership Perspective

Procedia Computer Science 2024年 234卷 1175-1182页

作者： Marcel Ford Lumban Gaol Suhono Harso Supangkat Benny Ranti Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information System Department Universitas Kristen Krida Wacana Jakarta Indonesia Smart Cities and Communities Innovation Center Faculty of Digital Communication and Hotel & Tourism Institute of Technology Bandung Bandung Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

Digital transformation is about transforming processes, business models, domains, and culture. Studies show that the failure rate of digital transformation is quite high up to 90%. Studies show that the transformational leadership model has a significant impact on digital transformation adoption. This paper identifies the positive and negative attributes of transformational leadership including the components that support and are affected for successful adoption of digital transformation. Furthermore, the paper combines several findings related to the attributes and components in the form of a conceptual framework. The conceptual framework can serve as a guide for organizations for their digital transformation journey.

关键词： transformational leadership digital transformation digital adoption conceptual framework

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South jakarta's air quality using PM 2.5 data at the beginning of COVID-19 Restriction 6

South jakarta's air quality using PM 2.5 data at the beginni...

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6th International Conference on information Management and Technology, ICIMTech 2021

作者： Rahutomo, Reza Purwandari, Kartika Hidayat, Alam Ahmad Pardamean, Bens Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

As soon as the lockdown was established in Jakarta, Indonesia, people experienced a change in Jakarta's air quality. This research was conducted to answer several challenges such as: where to find Indonesia's air quality open data platforms, how to handle the acquired data with SQL technology, and how to validate whether the air quality of Jakarta was significantly changed from a period to another or not. With particulate matter 2.5 (PM 2.5) data acquired by The United States Diplomatic Post in South Jakarta, a data visualization was generated to describe the fluctuation of PM 2.5 from February 29th to June 29th. By conducting a two-sample t-test, a significant change in South Jakarta's air quality was revealed. The test concluded that South Jakarta's air quality got worse even after a lockdown was established. © 2021 IEEE.

关键词： COVID-19

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Contribution of Virtual Reality Technology to Increase Student Interest in Vocational High Schools

Contribution of Virtual Reality Technology to Increase Stude...

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2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021

作者： Maulana, Fairuz Iqbal Pangestu, Gusti Sano, Albert Verasius Dian Purnomo, Agung Rahmadika, Sandi Widartha, Vandha Pradwiyasma Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia Graduate School Pknu Pukyong National University Interdisciplinary Program of Information Security Busan Korea Republic of Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia

ISBN: (纸本)9781665428477

This research investigates the feasibility of school-based learning using Virtual Reality technology in Electric Power Generation learning during the COVID-19 pandemic. This research employs a qualitative approach. Vocational High School Nurul Jadid Paiton Probolinggo is the site of this study. Data was gathered through observation, literature review, and interviews. In the Electrical Engineering section, interviews were conducted with a teaching instructor. Triangulation was used to investigate the data's authenticity, in addition to further interviews with the curriculum staff and instructors at the school. The teacher's assessment of learning media using Virtual Reality application technology shows valid criteria with an average value of 3.6. In comparison, after using the Virtual Reality application learning media, the assessment of students obtained an average value of 3.77 compared to conventional assessments with an interval of 2.71. The use of Virtual Reality technology has proven that it can help and facilitate student learning. The use of technologies of Virtual Reality as a means of learning in classrooms will also be an alternate option for virtual laboratories during the COVID-19 pandemic. © 2021 IEEE.

关键词： Virtual reality

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Preliminary Plan for Data Collection on Stakeholder information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones

Preliminary Plan for Data Collection on Stakeholder Informat...

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International Symposium on Communications and information Technologies (ISCIT)

作者： Penpitcha Arayachookiat Kumpol Saengtabtim Akira Kodaka Natt Leelawat Jing Tang Kenji Watanabe Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness.

关键词： Disasters Disaster management Data collection information and communication technology Stakeholders Floods Risk management Iterative methods Interviews Resilience

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Restaurant Customer Feedback Sentiment Analysis using Aspect Embedding Long Short-term Memory Model

Restaurant Customer Feedback Sentiment Analysis using Aspect...

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Computer Science, information Technology and Engineering (ICCoSITE), International Conference on

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

In the past ten years, there has been a proliferation of unstructured textual data from a variety of fields, allowing for the analysis of the sentiment polarity of the text authors in each of those datasets. To analyze sentiment polarity from unstructured data, machine learning tasks such as aspect-based sentiment analysis are used. The public dataset of restaurant patron feedback was used as the input for this study's empirical results of aspect-based sentiment analysis utilizing the Aspect Embedding Long Short-Term Memory model. The primary experiment's results show that the aspect embedding long short-term memory model can predict aspect sentiment polarization from customer feedback to restaurant service and aspect text representation (aspect text embedding) as input with excellent performance. For example, the Aspect Embedding Long Short-term Memory model, which uses ReLU as its activation function in the Dense layer tends to achieve higher performance (0.97 average accuracies) than the same model equipped with Sigmoid, and Tanh functions which achieve 0.954 and 0.956 average training accuracy respectively.

关键词： Training Computer science Sentiment analysis Analytical models Computational modeling Machine learning Predictive models

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Strengthening IT Governance in the Crypto Marketplace: Leveraging Penetration Testing and Standards Alignment

Strengthening IT Governance in the Crypto Marketplace: Lever...

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International Conference on Informatics, Multimedia, Cyber and information system (ICIMCIS)

作者： Semi Yulianto Erly Krisnanik Muhammad Syarif Hartawan Computer Science Department Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Information System Department University of Pembangunan Nasional Veteran Jakarta Indonesia Faculty of Technology University of Krisnadwipayana Jakarta Indonesia ICT Department Asia e University Malaysia

This research explores the vital role of penetration testing in cybersecurity, specifically its alignment with ISO 27001:2022, COBIT 2019, and NIST CSF standards in the context of crypto asset exchange management. These sectors grapple with rapidly evolving threat landscapes, necessitating robust cybersecurity strategies. However, the integration of penetration testing with these standards remains underexamined. Through a comprehensive approach, including literature reviews, surveys, case studies, and interviews, this study investigates the incorporation of penetration testing into an organization's cybersecurity. It unveils the current state of penetration testing practices, interprets ISO 27001:2022, COBIT 2019, and NIST CSF perspectives, and pinpoints integration challenges and opportunities. This study offers practical insights and best practices for integrating penetration testing into cybersecurity frameworks by emphasizing alignment. It underscores the importance of aligning penetration testing with information security standards in the crypto asset exchange management sector, enhancing security, proactively identifying vulnerabilities, and effectively mitigating risks in the context of growing crypto asset importance. This research provides invaluable guidance for safeguarding digital assets in this evolving domain.

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Aspect-based Sentiment Analysis using Long Short-term Memory Model for Leveraging Restaurant Service Management

Aspect-based Sentiment Analysis using Long Short-term Memory...

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Computer Science, information Technology and Engineering (ICCoSITE), International Conference on

In general, the hospitality industry has been acknowledged as a major sector that gives a high contribution to economic development in many countries including Indonesia. For that reason, many initiatives have been implemented to help the growth of the hospitality industry in many countries including Indonesia to rebound from the harsh impact of the Covid-19 Pandemic. One such initiative is improving restaurant services as the main sector of the hospitality industry. This paper presents empirical results of sentiment analysis as a means to assess the quality of restaurant services as the first step to improving service quality. In particular, this study explores the aspect-based sentiment analysis method to identify some aspects of restaurant service which need improvement by learning the polarity of customers toward the restaurant services without having to meet the customers directly. By using the aspect-based sentiment analysis method, the customer sentiments comprising opinions, sentiments, evaluations, attitudes, and emotions from restaurant service can be analyzed using customers’ online reviews as input. The main experiment findings showed that the Long Short-term Memory model can achieve high performance in predicting aspect polarization in restaurant service reviews. Other findings suggest that Sigmoid as an activation function achieved 0.97 average training accuracy and 0.69 average testing accuracy giving a better performance to the model in comparison to ReLU, Tanh, and ELU activation functions.

关键词： Industries Training Economics Sentiment analysis Pandemics Computational modeling Predictive models

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Comparing the Effect of Attention Mechanism and Aspect Embedding on the Performance of Long Short-term Memory Model for Aspect-Based Sentiment Analysis

Comparing the Effect of Attention Mechanism and Aspect Embed...

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Computer Science, information Technology and Engineering (ICCoSITE), International Conference on

The attention mechanism is one of the key enablers which have positioned transformer models as the state-of-the-art models in Natural Language Processing. By having the attention mechanism, the first version (vanilla) transformer model can retrieve the hidden state but at the same time can maintain a low requirement on the context vector dimension by selectively choosing to which encoder hidden states to give priority attention. The objective of this study is to evaluate the effect of modified Long Short-term Memory models architecture on the model performance as a predictive model. The first model is modified by adding an attention mechanism to its architecture; whilst, the second model is modified by adding additional input to its architecture. The performance of both models is compared by assigning each model the same task: to address the aspect-based sentiment analysis task. The experiment results show that adding an attention mechanism is not significantly increase the performance of the Long Short-term Memory model in comparison to adding input to the same model. In particular, the average training accuracy of the former model is 0.885; whilst, the average training accuracy of the latter model is 0.942.

关键词： Training Analytical models Sentiment analysis Computational modeling Memory architecture Predictive models Transformers

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Trends of Digital Transformation in the Property Management Industry: A systematic Literature Review

Trends of Digital Transformation in the Property Management ...

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Smart information systems and Technologies (SIST), IEEE International Conference on

作者： Prasetya Cahya Saputra Harjanto Prabowo Arief Ramadhan Evaristus Didik Madyatmadja Computer Science Department BINUS Graduate Program-Computer Science BINUS University Jakarta Indonesia Management Department BINUS Business School Doctor of Research in Management BINUS University Jakarta Indonesia Telkom University Bandung Indonesia School of Information System BINUS University Jakarta Indonesia

After the Covid 19 pandemic, the property management industry is slowly starting to revive. Even though the occupancy rate has not returned to normal like the Covid19 pandemic, its growth is starting to move in a positive direction. The Covid19 pandemic has provided many lessons for all stakeholders in the property management industry. Digital transformation has become a part that has received important attention in the property management industry worldwide. With digital transformation in the property management industry, all stakeholders are expected to receive various benefits, directly or indirectly. The implementation of digital transformation will involve 6 components, namely: Strategy, Organization, Culture, Customer, People, and Technology. The implementation of digital transformation in the property management industry will require support from many parties, not only internal parties but also external parties. Technological developments, IoT, and demands from residents and property owners are challenges that must be answered by property managers. This systematic literature review will examine articles that have been published in the Scopus database regarding the development of digital transformation in the property management industry from various countries. The purpose of this SLR is to be able to see how the digital transformation trend and the application of its components are in the current property management industry.

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Model of Sustainable Development Based on FinTech in Financial and Banking Industry: A Mixed-Method Research 3

Model of Sustainable Development Based on FinTech in Financi...

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3rd International Conference on Computer and Informatics Engineering, IC2IE 2020

作者： Legowo, Mercurius Broto Subanidja, Steph Sorongan, Fanky Antoneus Information Technology Faculty Institute of Perbanas Information System Study Program Jakarta Indonesia Post Graduate School Institute of Perbanas Master of Management Program Jakarta Indonesia Economic and Business Faculty Institute of Perbanas Accounting Study Program Jakarta Indonesia

ISBN: (纸本)9781728182476

In the past decade, it stated that the discourse on Sustainable Development and the Financial Technology(FinTech) role in the financial and banking industries, has attention on researchers, practitioners, regulators, and policymakers. The real problem arises from the discourse on whether FinTech has an effect on sustainable development in the financial and banking industry in Indonesia. This discourse needed to be understood better and more deeply. For credible research results, it is necessary to use a mixedmethod research approach. This research aims to develop a model that will help uncover the phenomenon of FinTech to sustainable development in the Financial and Banking Industry in Indonesia, using mixed methods research. In this study, Exploratory Sequential Mixed Method used as a type of mixedmethod approach. The main results of this study reveal that FinTech, which is influenced by business drivers, has a significant role in sustainable development in the Financial and Banking Industry in Indonesia. The contribution of this research can provide insight and understanding for researchers and practitioners in the financial and banking industry who want to implement a sustainable development model based on FinTech in more depth. © 2020 IEEE.

关键词： Sustainable development

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