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All Journal Technomedia Journal Aptisi Transactions on Management Startupreneur Business Digital (SABDA Journal) International Transactions on Education Technology (ITEE) Blockchain Frontier Technology (BFRONT) Journal of Computer Science and Technology Application
Bennet, Daniel
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Advancing E-commerce Smart-PLS as a Catalyst for Improved Online Shopping Services Alwiyah; Victorianda; Bennet, Daniel
International Transactions on Education Technology (ITEE) Vol. 2 No. 2 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v2i2.540

Abstract

In the fast-paced world of e-commerce, the adoption of advanced methodologies and technologies is vital to address the increasing demands and challenges of online shopping services. This paper examines the transformative impact of Partial Least Squares Structural Equation Modeling (Smart-PLS) on e-commerce. Smart-PLS is a powerful tool that offers a robust framework for analyzing and enhancing various aspects of e-commerce, such as customer experience, service quality, and business performance. This study explores how Smart-PLS facilitates a data-driven decision-making approach, resulting in better user experiences, optimized supply chains, and improved business strategies. The abstract underscores the importance of Smart-PLS as a revolutionary tool in the e-commerce sector, enabling businesses to adapt, innovate, and succeed in the digital marketplace. It highlights the potential of Smart-PLS to shape the future of online shopping services and stresses the necessity of its adoption for maintaining competitiveness in the ever-changing e-commerce landscape.
Navigating the Challenges of Digital Transformation in Traditional Organization Maratis, Jerry; Ramadan, Ahmad; Rahmania Az Zahra, Achani; Ahsanitaqwim, Ridhuan; Bennet, Daniel
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2349

Abstract

Digital transformation has become a critical strategy for traditional organiza- tions to maintain competitiveness in an increasingly technology-driven market. Technologies such as fintech, blockchain, artificial intelligence (AI), and cloud computing have significantly reshaped operational efficiency and customer en- gagement within these organizations. However, traditional organizations, characterized by their legacy systems and hierarchical structures, encounter various challenges in adopting these technologies. This study primarily aims to explore the key barriers that hinder digital transformation in traditional organizations and to propose effective strategies for overcoming these challenges. Utilizing a comprehensive literature review from 2018 to 2023, this research examines key studies on digital transformation in traditional business contexts. The find- ings reveal major challenges, including organizational inertia, skills gaps, de- pendency on outdated systems, and leadership deficiencies. To address these barriers, the study proposes strategies such as leadership development, work- force retraining, and investment in modern digital infrastructure. The results suggest that successful digital transformation requires a multifaceted approach, aligning technological adoption with organizational culture and sustainability goals. This research provides valuable insights for traditional organizations nav- igating the complexities of digital transformation.
Blockchain in Digital Transformation: Enhancing Security, Transparency, and Efficiency in Modern Systems Handra, Tessa; Purnama, Suryani; Jati Kusumo, Ariya; Bennet, Daniel
Blockchain Frontier Technology Vol. 4 No. 1 (2024): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v4i1.572

Abstract

Blockchain technology has emerged as a transformative force in the digital transformation of industries, particularly in enhancing security, transparency, and operational efficiency. This paper aims to explore the practical applications of blockchain in various sectors, including supply chain management, healthcare, and finance, and assess its ability to address challenges like decentralization, cryptographic security, and consensus mechanisms. Through a comprehensive literature review and case study analysis, this study examines how blockchain technology fosters trust, reduces fraud, and improves the efficiency of digital systems by providing tamper-proof records and automating processes through smart contracts. The research also identifies significant barriers to blockchain adoption, such as scalability issues, regulatory constraints, and interoperability problems that hinder its widespread implementation. By evaluating these obstacles, the paper offers insights into the technological and policy challenges that need to be overcome to facilitate blockchain's broader use. This study contributes to the growing body of knowledge by showcasing the potential of blockchain to revolutionize industries beyond its initial use in cryptocurrencies. The novelty of this research lies in its focus on blockchain's applications in real-world business systems, emphasizing its role in digital transformation strategies. The paper concludes by recommending further research and technological innovations to address the scalability and regulatory gaps, as well as strategies for accelerating blockchain adoption. Ultimately, blockchain's ability to enhance the security, transparency, and efficiency of modern systems positions it as a key driver of future digital transformations.
Consumer Behavior and Brand Loyalty: A Study on Digital Marketing Practices Saputra, Achmad Hidayat Dwi; Windiartono Putra, Souza Nurafrianto; Bennet, Daniel
Startupreneur Business Digital (SABDA Journal) Vol. 3 No. 2 (2024): Startupreneur Business Digital (SABDA)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v3i2.630

Abstract

In the rapidly evolving digital landscape, understanding consumer behavior is critical for building and sustaining brand loyalty. This study explores the relationship between digital marketing practices and consumer behavior, and how these behaviors influence brand loyalty. Leveraging a comprehensive literature review and empirical analysis, this research employs a mixed-methods approach, combining quantitative surveys with qualitative interviews to gain a holistic view of the consumer-brand interaction in the digital era. Data were collected from a diverse sample of consumers who regularly engage with brands through digital platforms. The quantitative analysis, conducted using statistical tools, revealed a significant correlation between personalized digital marketing efforts and increased consumer loyalty. Qualitative findings further highlighted that consumers value brand transparency and engagement in online spaces, which in turn enhances their loyalty. The findings suggest that digital marketing practices, such as targeted advertising and interactive content, play a crucial role in shaping consumer perceptions and driving brand loyalty. These results provide valuable insights for marketers seeking to optimize their digital strategies to foster deeper connections with their audiences.
Risk Management Strategies in Blockchain Adoption within Financial Institutions Analyzing Challenges and Opportunities Dewi, Susanti; Firasati, Aoliyah; Sitoayu, Laras; Bennet, Daniel
APTISI Transactions on Management (ATM) Vol 9 No 1 (2025): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i1.2393

Abstract

The integration of blockchain technology in financial institutions has introduced both groundbreaking opportunities and significant risks, necessitating a comprehensive approach to risk management. Blockchain’s potential to enhance transparency, security, and efficiency in financial processes makes it an attractive technology for financial institutions. However, issues like regulatory uncertainty, data privacy, and technological readiness present unique challenges. This study aims to identify, evaluate, and provide insights into the primary risks associated with blockchain implementation in financial institutions, focusing on both challenges and opportunities to aid in effective risk management. Using the Structural Equation Modeling (SEM) technique with Partial Least Squares (PLS), also known as SmartPLS, this study examines data collected from financial industry stakeholders, including risk managers and IT experts. Variables assessed include data security, regulatory compliance, and technological infrastructure, allowing for a nuanced understanding of the risk dynamics within blockchain adoption. The analysis reveals that data security risks and regulatory concerns significantly impact blockchain implementation success, while technological readiness serves as a moderating factor, influencing the ease of adoption and operational success. Findings underscore the need for a balanced approach to blockchain integration in financial services, where risk management strategies address both regulatory and technological challenges. By identifying these core risks and their implications, this study contributes to the body of knowledge on blockchain risk management and offers practical recommendations for financial institutions aiming to adopt blockchain effectively while minimizing associated risks.
Pengaruh Metode Waterfall dalam Penyempurnaan Proses Pengembangan Sistem Informasi Akademik secara Sistematis: Impact of Waterfall Method on Systematic Academic Information System Development Po Abas Sunarya; Untung Rahardja; Santoso, Nuke Puji Lestari; Mulyati; Mustofa, Kenny Ilyas; Bennet, Daniel
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2421

Abstract

Academic information systems play a crucial role in supporting the operations of educational institutions, particularly in managing complex data. The main challenge in their development is ensuring that the process is structured, efficient, and aligned with user needs. The Waterfall method, as one of the sequential and systematic development approaches, is often used in information system development projects. However, its effectiveness in the context of academic information systems requires further analysis. This study aims to analyze the impact of the Waterfall method on improving the development process of academic information systems. The research focuses on three main aspects: time efficiency, cost, and the quality of the final output. Both quantitative and qualitative descriptive approaches were employed in this study. Data were collected through in-depth interviews with system developers, surveys of users (academic administration, lecturers, and students), and case studies at educational institutions using the Waterfall method. The results show that the Waterfall method provides a clear structure in the development process of academic information systems. This has a positive impact on time efficiency and the quality of the final output. However, the main drawback of this method is its lack of flexibility in addressing changing needs that often arise during the project. In conclusion, the Waterfall method is effective for academic information system development projects with stable and well-defined requirements. This study recommends exploring a hybrid approach, such as combining Waterfall with Agile, to improve responsiveness to changes in user needs in the future.
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. 
Co-Authors Ahsanitaqwim, Ridhuan Alwiyah Alwiyah Anjani, Sheila Aulia Aoliyah Firasati Bangun, Cicilia Sriliasta Daeli, Ora Pertiwi Dewi, Susanti Handra, Tessa Jati Kusumo, Ariya Maratis, Jerry Martono, Dedi Mulyati Mustofa, Kenny Ilyas Po Abas Sunarya Purnama, Suryani Rahmania Az Zahra, Achani Ramadan, Ahmad Santoso, Nuke Puji Lestari Saputra, Achmad Hidayat Dwi Sitoayu, Laras Untung Rahardja Victorianda Windiartono Putra, Souza Nurafrianto