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HighTech and Innovation Journal 2025年第1期6卷 21-41页

作者： Oktavia, Tanty Wijaya, Eric Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

In today's data-driven business landscape, robust metadata and data documentation practices are essential for enterprises aiming to maximize their data assets. When integrated with Business Intelligence (BI) systems, this architecture empowers data democratization, allowing widespread utilization by stakeholders across the organization. This research explores the critical role of metadata in shaping Business Intelligence (BI) systems and organizational effectiveness within today's data-driven business landscape. Through a systematic literature review, a preliminary study, a quantitative survey with 318 responses, and a focus group discussion, the study identifies key metadata components influencing BI systems effectiveness and organizational outcomes. Findings indicate a direct and positive impact of BI systems effectiveness on organizational effectiveness. Certain metadata components exhibit direct positive effects on both BI systems and organizational effectiveness. The research underscores the importance of strategic metadata implementation for enterprises seeking to optimize data-driven decision-making processes. Overall, the study provides practical implications for organizations and contributes valuable insights to the understanding of metadata's role in enhancing enterprise effectiveness. © Authors.

关键词： Data assimilation

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Outlier Detection in VPN Authentication Logs for Corporate Computer Networks Access Using CRISP-DM

HighTech and Innovation Journal

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HighTech and Innovation Journal 2024年第4期5卷 1101-1117页

作者： Legowo, Nilo Bad, Wilyu Mahendra Information Systems Management Department Binus Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

A Virtual Private Network (VPN) serves as a critical network access solution widely employed by corporations, enabling users to connect to company computer networks via a global infrastructure. Amid the ongoing Covid-19 pandemic, heightened reliance on computer network access has increased the vulnerability to data breaches by unauthorized parties. This necessitates a proactive approach from companies to safeguard data integrity, particularly by identifying abnormal access patterns and timestamps. This study aims to develop a model for detecting anomalous activities within authentication log data obtained from VPN usage. The dataset comprises log entries from September to November 2022, totaling 36,807 records, selected via a systematic sampling approach. Two key attributes, namely user ID and access time, are analyzed to trace access patterns. Employing the CRISP-DM method ensures a structured and efficient research process. The selection of the k value in the K-Nearest Neighbors (K-NN) method significantly impacts outlier detection and can be tailored to suit organizational requirements. By utilizing the K-Means algorithm for data clustering and K-NN for measuring inter-point distances, the study identifies outliers that warrant further investigation by the company. Integration of the proposed model into the company's big data platform facilitates real-time monitoring, enabling the security team to preemptively address potential threats and mitigate network access misuse. By enhancing awareness and responsiveness to information security risks, the model contributes to fortifying the company's cyber security posture amidst evolving digital landscapes. © 2024, Ital Publication. All rights reserved.

关键词： K-means clustering

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A deep learning framework for automatic assessment of presence in virtual reality using multimodal behavioral cues

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Neural Computing and Applications 2025年第8期37卷 6283-6303页

作者： Pannattee, Peerawat Shimada, Shogo Yem, Vibol Nishiuchi, Nobuyuki Graduate School of Systems Design Tokyo Metropolitan University Tokyo191-0065 Japan Graduate School of Science and Technology Degree Program in Systems and Information Engineering University of Tsukuba Ibaraki3058573 Japan

Effective development of virtual reality (VR) applications is heavily reliant on the evaluation of user experience (UX). However, traditional methods such as questionnaires have inherent limitations which hinder their ability to capture nuanced behavioral responses and impede the agility of VR content creation: They are time-consuming, burdensome for users, and require significant human effort for interpretation. This study introduces an automated framework aimed at addressing the limitations of questionnaire-based evaluations to assess UX in VR. Our primary focus is to validate the concept of this framework through assessment of the sense of presence (SOP), a crucial psychological perception with significant impact on VR UX. Our proposed framework utilizes a deep neural network (DNN) to analyze patterns in multimodal behavioral cues, including facial expressions, head movements, and hand movements, to predict scores from the Igroup Presence Questionnaire (IPQ). Additionally, we introduce two statistical profiles: the Visual Entropy Profile (VEP), which offers insights into visual complexity by depicting scene entropy, and the Experiential Presence Profile (EPP), which is designed to capture users’ historical SOP levels to enable personalized baseline and sensitivity estimation. The proposed framework achieves a significant correlation between actual and predicted IPQ scores, with a Spearman’s rank correlation coefficient of 0.7303, showcasing the potential of DNNs in analyzing complex behavioral signals and automating SOP assessment. This study represents a pioneering effort in leveraging DNNs for the automatic assessment of SOP and paves the way for future advances in automatically assessing VR UX and unlocking new opportunities in the field. © The Author(s) 2025.

关键词： Virtual environments

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System Architecture for IT Talent Ecosystem Using Service Oriented Approach

HighTech and Innovation Journal

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HighTech and Innovation Journal 2023年第4期4卷 739-748页

作者： Fajar, Ahmad Nurul Limonthy, Stanley Handopo, Josua J. Purnawan, Fandy Kesuma, Adidharma E. Information Systems Management Department Binus Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

The purpose of this research is to propose a System Architecture to facilitate the IT Talent ecosystem using a service-oriented approach. The need for this is important to support digital transformation in the IT Talent ecosystem. Human resources in the IT field are one of the key factors in implementing IT in organizations. However, the availability of IT human resources has not been able to meet the needs and challenges of the organization in synergizing IT and business. Meanwhile, on the other hand, the qualifications of IT human resources do not meet the existing competency standards. In this research, we use a service-oriented system development method. It consists of three stages, such as (1). Analysis and Observation, (2). Analysis from an in-depth interview, and (3) System Architecture Design, which includes Analysis Features of the systems, Service Analysis and Identification, Specification of Architecture, and Layering. The novelty and findings of this research are a system architecture, which is called a middleware architecture, that can bridge entities in the IT Talent ecosystem to provide and use services to each other for support collaboration. In this study, we proposed a system architecture that acts as middleware to support collaboration and integration in the IT Talent ecosystem. We proposed TALENT-IT, which acts as a service bus mechanism. We used a service-oriented approach to develop this platform. The results of this study are: list of features, list of services, SOA layer, SOA architecture, and monetization feasibility and challenges. © Authors retain all.

关键词： Computer architecture

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Mobile Service Quality’s Impact on Customer Repurchase Intention in Food and Beverage Mobile Applications

HighTech and Innovation Journal

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HighTech and Innovation Journal 2024年第3期5卷 703-715页

作者： Oktavia, Tanty Christian, Jonathan T. Kristanto, Kelven J. Satria, Ricky S. Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia

This study aims to assess the impact of mobile service quality on customer repurchase intention in Indonesia’s food and beverage mobile applications. The research identifies key dimensions such as application design, ease of use, privacy, and customer support and evaluates their influence on customer e-satisfaction and repurchase behavior. A quantitative approach was employed, utilizing purposive sampling to gather data from 401 active users of these applications. The analysis, conducted using Structural Equation Modeling-Partial Least Squares (SEM-PLS), revealed that these dimensions significantly enhance overall mobile service quality, which in turn positively affects customer e-satisfaction and repurchase intention. The findings underscore the importance of a minimalist and user-friendly design, robust privacy measures, and responsive customer support—particularly for Gen-Z users in Indonesia, where privacy concerns are increasingly prominent. This study contributes to the existing literature by providing insights specific to the Indonesian market and offering practical recommendations for the food and beverage industry to improve mobile service quality, thereby fostering stronger customer loyalty and increasing repurchase rates. The novelty of this research lies in its focus on the rapidly growing mobile app market in Indonesia, addressing unique regional challenges and opportunities. © 2024, Ital Publication. All rights reserved.

关键词： Sales

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Critical Success Factor of Discord Usage: A Systematic Literature Review 4

Critical Success Factor of Discord Usage: A Systematic Liter...

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

作者： Margatan, Natalicia Oktavia, Tanty Binus Graduate Program Bina Nusantara University Information Systems Management Department Jakarta Indonesia

ISBN: (纸本)9798331506490

Discord has evolved from a gaming-centric communication tool into a platform widely used in education, professional settings, and community building. This systematic literature review explores the critical success factors (CSFs) driving Discord's growth from 2019 to 2024, focusing on ease of use, cross-platform compatibility, customization, and integration with tools like GitHub and YouTube. In education, Discord's real-time and asynchronous communication features enhance student engagement, support remote learning, and foster interactive classrooms. In professional contexts, its adaptability aids project collaboration, workflow efficiency, and remote team management, making it a valuable workplace tool. User satisfaction averages 85%, with a reported 20% increase in workflow efficiency among teams. However, challenges such as information overload and privacy concerns limit its effectiveness, underscoring the need for improved protocols and security. These findings highlight Discord's user-centered design and feature versatility as key success factors. Despite its strengths, research gaps remain regarding its long-term impact on productivity and user satisfaction outside gaming. Addressing these through future studies is crucial for maximizing Discord's potential in reshaping communication, collaboration, and community building. © 2024 IEEE.

关键词： Efficiency

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Smart Insurance Enterprise in Digital Transformation Wave 11

Smart Insurance Enterprise in Digital Transformation Wave

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Legowo, Nilo Kristanda, Hengki Deta, Bernadette Bina Nusantara University Binus Graduate Program Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350389654

The rapid growth in the number of marketers has contributed greatly to the increase in company revenue. The marketing channel for insurance products through agencies has consistently reached 92% of Company case total annual revenue. The company's growth was also accompanied by an increase in the number of complaints and a decrease in company efficiency. Changes in regulations that often occur also cause an increase in company operating costs which reduce the company's net profits. The purpose of this study is to design a smart enterprise structural design, specifically for the insurance company, based on the conception of TOGAF. The research stages follow the Togaf framework stages starting from preliminary to Architecture Change Management. It is necessary to design an architecture according to management needs to face the digital transformation wave. The result shows the new smart insurance enterprise architecture which is ready to compete. © 2024 IEEE.

关键词： Operating costs

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Sentiment Analysis of Digital Customer Service Helpdesk Tickets: A Comparison between BERT and SVM

Sentiment Analysis of Digital Customer Service Helpdesk Tick...

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2024 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Jayusman Jayadi, Riyanto Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368802

This research aimed to perform a comparative analysis of the effectiveness of customer support systems and the management of helpdesk tickets, which play a pivotal role in maintaining customer satisfaction and loyalty in the current digital age. As helpdesk tickets surge in number, leveraging automation to accurately gauge and address customer emotions becomes essential. This research introduces the application of Bidirectional Encoder Representations from Transformers (BERT), a sophisticated natural language processing (NLP) technique, for analyzing the sentiments expressed in helpdesk tickets of digital products. A BERT model was crafted and trained to categorize the sentiments of these tickets as either positive, negative, or neutral. This endeavor aims to equip businesses with deeper insights, enabling them to improve their approach to customer service. The model underwent training with a collection of helpdesk tickets from a variety of digital products, such as software, mobile applications, and online services, featuring a total of 8,240 entries with a distribution of 991 negative, 6,613 neutral, and 636 positive comments. Findings reveal that the BERT model outshines the Support Vector Machine in accuracy, achieving a 90% success rate versus the latter's 88%. © 2024 IEEE.

关键词： Customer satisfaction

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Royalty Management by Using Blockchain Network: A Multiple Case Study 9

Royalty Management by Using Blockchain Network: A Multiple C...

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

作者： Nathaniela, Thalea Christy Princes, Elfindah Wang, Gunawan BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

The rise of music streaming services has led to significant challenges in royalty management, particularly affecting independent musicians who face poor royalty payments and a lack of transparency in royalty calculations. This research explores the application of blockchain technology to address these issues, focusing on its potential to revolutionize royalty management within the music industry. The study provides a conceptual framework for understanding music streaming services, digital music piracy, and royalty transparency, analyzing the impact of blockchain on revenue generation in the Indonesian music industry. Utilizing a literature review, case studies, and a theoretical framework, the research investigates the effectiveness of blockchain in enhancing transparency, and fairness in revenue distribution, and rights management. Through purposive sampling and the analysis of BitTorrent as a case study, the results highlight the trans formative potential of blockchain in the music industry, particularly in addressing the 'value gap' in unallocated royalties and improving revenue generation for musicians. The findings underscore the significant implications of blockchain technology for the future of royalty management and the overall music ecosystem. © 2024 IEEE.

关键词： blockchain music streaming services Royalty management

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Optimizing Customer Retention in Urban Laundry Services: A Comparative Analysis of Machine Learning Algorithms in Jakarta's MSME Sector 9

Optimizing Customer Retention in Urban Laundry Services: A C...

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

作者： Putri, Rhisa Adika Mauritsius, Tuga Ananda, Bryan Jayadi, Riyanto BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

In the rapidly urbanizing context of major cities such as Jakarta, the demand for efficient and rapid laundry services poses a considerable challenge, particularly within residential settings like boarding houses or dormitories in Central Jakarta, where access to communal laundry facilities is markedly constrained. Against this backdrop, laundry enterprises categorized under Micro, Small, and Medium Enterprises (MSMEs) in the service sector have witnessed significant growth. These services typically encompass the collection, washing, drying, folding, and delivery of laundry to the customer's domicile. Nevertheless, the burgeoning proliferation of laundry businesses has precipitated intensified competition within the sector, compelling these enterprises to devise strategies for customer retention and revenue augmentation. This research endeavors to delineate effective strategies and solutions to navigate the competitive landscape of the laundry industry. The study undertakes a meticulous evaluation of various machine learning algorithms, including Decision Tree, Logistic Regression, Naïve Bayes, Support Vector Machine, Random Forest, XGBoost, LightGBM, and CatBoost, based on their performance with unseen data. This evaluation employs a comprehensive set of metrics such as precision, recall, Fl-score, and ROC AUC to determine the efficacy of each model. The findings reveal that the CatBoost Classifier algorithm outperforms others, achieving a training accuracy of 95.9% and a testing accuracy of 85.7%. The novelty of this study lies in its comprehensive comparison of multiple machine learning algorithms in the context of MSMEs in Jakarta's laundry sector, highlighting the superior performance of the CatBoost algorithm. Furthermore, the study contributes by demonstrating the practical application of these algorithms to improve customer retention strategies, enhance service quality, and optimize marketing tactics. Based on these results, the study recommends the implemen

关键词： Decision trees

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