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All Journal Technomedia Journal Aptisi Transactions on Technopreneurship (ATT) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) IAIC Transactions on Sustainable Digital Innovation (ITSDI) Startupreneur Business Digital (SABDA Journal) Journal of Computer Science and Technology Application
Anjani, Sheila Aulia
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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A Platform Based Business Revolution Activates Indonesia's Digital Economy Meilinda, Vivi; Anjani, Sheila Aulia; Ridwan , M
Startupreneur Business Digital (SABDA Journal) Vol. 2 No. 2 (2023): Startupreneur Business Digital (SABDA)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v2i2.279

Abstract

In the past twenty years, the rise of the internet, often known as e-commerce, has been extremely rapid. The rise of a digital economy was then influenced by this phenomenon. This tendency will revolutionize people's lives in the long run as well as how business, commerce, and the economy develop. Although not all of them are able to grow as large as businesses that have become examples of international success, it can be seen that the development of the many startup companies that are beginning to blossom in Indonesia closely follows this trend. In the past twenty years, the rise of the internet, often known as e-commerce, has been extremely rapid. The rise of a digital economy was then influenced by this phenomenon. This tendency will revolutionize people's lives in the long run as well as how business, commerce, and the economy develop. Although not all of them are able to grow as large as businesses that have become examples of international success, it can be seen that the development of the many startup companies that are beginning to blossom in Indonesia closely follows this trend.
Unveiling New Horizons: AI-Driven Decision Support Systems in HRM - A Novel Bibliometric Perspective Shantilawati, Irma; Suri, Oryza Intan; Sunarjo, Richard Andre; Anjani, Sheila Aulia; Robert, Dariari
Aptisi Transactions On Technopreneurship (ATT) Vol 7 No 1 (2025): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v7i1.561

Abstract

The integration of Artificial Intelligence (AI)-driven Decision Support Systems (DSS) in Human Resources Management (HRM) has become crucial for optimizing workforce management and enhancing decision-making processes. This bibliometric analysis investigates the research landscape of AI-driven DSS in HRM from 2015 to 2024, using data from the Dimensions database and analyzed through VOSviewer. Key trends, influential authors, and significant publications are identified, revealing the dominant roles of the United States, China, and India, with institutions like MIT, Stanford University, and IIT Delhi leading in productivity and impact. Notable contributors such as Dwivedi, Lowry, and Bose are highlighted for their practical and theoretical advancements in the field. Influential journals including "Decision Support Systems", "Information & Management", and "Sustainability" are identified as shaping the research landscape. The findings emphasize the transformative impact of AI-driven DSS on HRM practices, offering insights into future research opportunities and applications. This study provides a comprehensive framework for understanding the current state and future directions of AI-driven DSS in HRM, contributing to both academic and practical advancements.
Integration of Business Intelligence and Predictive Analytics for Student Success Based on Blockchain: Integrasi Business Intelligence dan Analitik Prediktif untuk Keberhasilan Mahasiswa Berbasis Blockchain Rahardja, Untung; Rakhmansyah, Mohamad; Wijaya, Surta; Anjani, Sheila Aulia; Davies, Mary
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2389

Abstract

In the digital era, education is undergoing a significant transformation, with predictive analytics becoming an important approach to increasing student success. Rapid advancements in technology have enabled institutions to collect and analyze diverse datasets, yet challenges remain in ensuring data accuracy, transparency, and reliability. This research explores the integration of blockchain technology to address data integrity challenges, with a focus on its application in predictive analytics. The objective is to enhance the reliability of student-related data while improving the effectiveness of academic performance predictions. Specifically, this research examines the relationship between Academic Performance Metrics (APM), Student Engagement Data (SED), Socioeconomic Factors (SEF), Blockchain-Enabled Data Integrity (BDI), and Predictive Algorithm Efficiency (PAE). Using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, data were collected through structured surveys and institutional records involving higher education students. The constructs were validated through measurement model testing before proceeding to structural path analysis. The results show the significant influence of socio-economic factors and blockchain-based data integrity on academic outcomes, while student engagement and predictive algorithm efficiency also demonstrate moderate effects. The study also identifies areas that require improvement in predictive models, particularly regarding the alignment of input variables with algorithm design. These findings emphasize the importance of leveraging technology to develop more equitable and effective educational strategies, while underscoring the need for continued improvements in construct design to increase the reliability and validity of models. This research contributes to the growing field of educational data science by offering a blockchain-enhanced framework for predictive analytics in education.
Analysis of Omni Channel Strategy in Digital Retail on Modern Indonesian Consumer Behavior: Analisis Strategi Omni Channel dalam Ritel Digital terhadap Perilaku Konsumen Indonesia Modern Baso, Farisha Andi; Sitorus, Santa Lusianna; Meilinda, Vivi; Anjani, Sheila Aulia; Rodriguez, Marta
ADI Bisnis Digital Interdisiplin Jurnal Vol 6 No 1 (2025): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v6i1.1226

Abstract

The development of digital technology has driven a profound transformation in the retail industry, giving rise to the omni-channel strategy as a holistic ap proach to meet modern consumer expectations. This study aims to analyze the influence of online and offline channel integration on Indonesian consumer behavior in the context of digital retail. Using a qualitative approach through literature review and secondary data analysis, this study reveals that today’s In donesian consumers show a high preference for convenience, personalization, and speed of service in the shopping experience. An omni-channel strategy enables companies to provide a consistent, adaptive, and integrated consumer journey across various interaction points, which has a positive impact on customer loyalty and operational efficiency. Furthermore, the implementation of this strategy aligns with sustainability principles, particularly in supporting Sustainable Development Goals (SDGs) 9 (industrial and infrastructure innova tion) and point 12 (responsible consumption and production). These findings confirm that the success of digital retail in Indonesia is highly dependent on the ability of business actors to strategically manage channel integration, under stand evolving consumer behavior, and prioritize sustainability values in their operations.
Predictive Analysis of Startup Ecosystems: Integration of Technology Acceptance Models with Random Forest Techniques Bennet, Daniel; Anjani, Sheila Aulia; Daeli, Ora Pertiwi; Martono, Dedi; Bangun, Cicilia Sriliasta
CORISINTA Vol 1 No 1 (2024): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i1.8

Abstract

In the dynamic realm of startup ecosystems, forecasting trends and measuring success pose significant challenges. To tackle this multifaceted issue, a novel research method proposes integrating the Technology Acceptance Model (TAM) with the robust Random Forest algorithm, thereby enhancing predictive accuracy. This innovative approach encompasses various aspects including technical intricacies, financial dynamics, stakeholder interactions, and entrepreneurial challenges. Employing empirical data, such as revenue growth, capital raised, innovation rate, and active users, forms the foundation of this methodology. The model’s efficacy is demonstrated through a process involving training on 80% of the dataset and testing on the remaining 20%, showcasing superior predictive capabilities compared to conventional methods. Comparative analysis with established models like logistic regression further highlights the superiority of the integrated TAM and Random Forest approach, particularly in predicting startup success. These findings offer invaluable insights for entrepreneurs navigating the complexities of the startup landscape, as well as for investors, policymakers, and educators. Understanding and supporting growth dynamics within the startup ecosystem can foster innovation and prosperity. Moreover, in the academic sphere, this research contributes a novel framework for startup prediction, enriching existing knowledge and facilitating informed decision-making. Overall, this research not only provides practical applications for immediate stakeholders but also contributes to advancing the theoretical foundations of startup prognostication, thus serving as a significant milestone in the field. 
Corporate Strategies to Improve Platform Economic Performance: The Role of Technology, Ethics, and Investment Management Leffia, Abigail; Anjani, Sheila Aulia; Hardini, Marviola; Sihotang, Sondang Visiana; Aini, Qurotul
CORISINTA Vol 1 No 1 (2024): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i1.14

Abstract

Amid the rapid growth of the platform economy, companies are feeling the pressure to adopt innovative technologies to improve their performance. Meanwhile, in an effort to achieve sustainable growth, ethical issues also arise that must be resolved. This research aims to investigate how the integration of technology and ethical principles can contribute to improving corporate performance in the platform economy environment. We explore how companies can overcome the dilemmas that arise when they adopt advanced technologies while also considering deep ethical aspects. This research methodology involves the SmartPLS approach to analyze the relationship between technological variables and ethical variables on company performance, involving 120 participants. It is hoped that the results of this research will provide valuable insight into how companies can optimize the use of technology while still adhering to strong ethical principles, with the aim of achieving superior performance in the competitive platform economy market. Thus, this research provides a significant contribution in understanding how companies can achieve sustainable excellence amidst changing economic dynamics.
Software-Defined Networking: Revolutionizing Network Management and Optimization Maulana, Sabda; Anjani, Sheila Aulia; Sanjaya, Yulia Putri Ayu; S, Sondang Visiana; Sithole, Precious
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/g1as4162

Abstract

This study investigates the impact of Software-Defined Networking (SDN) on network management and optimization, comparing its performance to traditional networking approaches. Through a mixed-methods approach, including empirical experiments and expert interviews, the research demonstrates that SDN significantly enhances network performance by reducing latency, increasing throughput, and providing superior security management. The scalability of SDN was also confirmed, with the network efficiently handling an increasing number of devices without performance degradation. However, the study identified challenges in integrating SDN into existing infrastructures and the need for specialized skills to manage SDN environments effectively. These findings underscore the potential of SDN as a transformative technology in modern network management, while also highlighting areas where further research is needed to address integration and skill-related challenges.
Enhancing Network Security with Quantum Cryptography:A Study on Future-Proofing Computer Networks AgainstQuantum Attacks Supriati, Ruli; Purwanti; Anjani, Sheila Aulia; Anugrah, Rio Wahyudin; McCarthy, Ryan
CORISINTA Vol 2 No 1 (2025): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i1.58

Abstract

The rapid development of quantum computing presents a significant challenge to existing cryptographic systems, such as RSA and Elliptic Curve Cryptography, which rely on the complexity of mathematical problems for security. Shor’s algorithm, which can efficiently solve these problems, emphasizes the need for cryptographic solutions that are resistant to quantum threats. This study aims to investigate the potential of Quantum Cryptography, with a specific focus on Quantum Key Distribution (QKD), to strengthen network security in response to emerging quantum computing risks. Despite the theoretical potential of QKD, there remains a gap in its practical application, particularly in terms of scalability, high implementation costs, and sensitivity to environmental factors, which have hindered its widespread adoption. The novelty of this research lies in the comprehensive approach it takes, combining theoretical analysis of QKD protocols, simulations using Qiskit, and comparisons with traditional cryptographic methods. This provides a more robust understanding of QKD effectiveness in different network scenarios. The study reveals that the BB84 protocol consistently outperforms the E91 protocol in terms of key generation efficiency and noise resilience. However, despite its unmatched security capabilities, QKD faces challenges such as scalability and implementation costs. To overcome these challenges and achieve widespread adoption, integrating QKD with post quantum cryptography and developing hybrid approaches are essential. Quantum Cryptography, particularly QKD, holds the potential to become a cornerstone for securing critical infrastructure, ensuring communication security in the quantum era.
Integrating Artificial Intelligence in E-Learning for Organizational Well-Being through Orange Technology Mapping Simanjuntak, Arthur; Sutarman, Asep; Anjani, Sheila Aulia; Nuche, Asher
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 1 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i1.706

Abstract

This study conducts a bibliometric analysis of Artificial Intelligence (AI) in e-learning, emphasizing its role in organizational well-being and educational transformation. Using Scopus as the primary database and VOSviewer for visualization, 557 articles published between 2020 and 2025 were analyzed across country, organization, source, author, document, and keyword networks. The results reveal that the United States, United Kingdom, and Germany act as central contributors, while India, Saudi Arabia, Singapore, Hong Kong, and Egypt are rapidly growing in influence. Source analysis identifies leading journals that shape the discourse alongside new outlets that diversify the field. Author and document coupling highlight key works that connect immersive learning environments with pedagogy, while keyword analysis identifies three major clusters related to ethics and governance, motivation and technology enhanced learning, and AI tools such as ChatGPT and generative AI. Overall, the findings show that AI in e-learning has evolved from experimental initiatives into a multidimensional, evidence-based domain. The study concludes by emphasizing how Orange Technology and TRAIVIS frameworks can operationalize ethics by design, support adaptive tutoring, and align AI-driven learning ecosystems with sustainable, well-being-centered educational goals.
Co-Authors Anugrah, Rio Wahyudin Arthur Simanjuntak Bangun, Cicilia Sriliasta Bennet, Daniel Daeli, Ora Pertiwi Davies, Mary Farisha Andi Baso, Farisha Andi Irma Shantilawati Leffia, Abigail Martono, Dedi Marviola Hardini Maulana, Sabda McCarthy, Ryan Meilinda, Vivi Nuche, Asher Purwanti Qurotul Aini Rakhmansyah, Mohamad Ridwan , M Robert, Dariari Rodriguez, Marta Ruli Supriati, Ruli S, Sondang Visiana Sanjaya, Yulia Putri Ayu Sihotang, Sondang Visiana Sithole, Precious Sitorus, Santa Lusianna Sunarjo, Richard Andre Suri, Oryza Intan Sutarman, Asep Untung Rahardja Wijaya, Surta