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All Journal Blockchain Frontier Technology (BFRONT) Journal of Computer Science and Technology Application
Lase, Steven Harazaki
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Computer Science & IT Control & Systems Engineering Education Library & Information Science Other

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Decentralized Solutions for Intellectual Property Security Using the InterPlanetary File System Shofiyul Millah; Andri Waskito; Ester Ananda Natalia; Lase, Steven Harazaki; Marta Rodriguez
Blockchain Frontier Technology Vol. 5 No. 1 (2025): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i1.833

Abstract

In the digital era, protecting intellectual property rights (IPR) presents major challenges due to the vulnerabilities of centralized storage systems, which are susceptible to data breaches, manipulation, and unauthorized access. This study explores the adoption of the InterPlanetary File System (IPFS) as a decentralized alternative for securing IPR, with a focus on user-centric factors that are often neglected in prior research. Specifically, the research examines how five key constructs security, transparency, persistence, ease of use, and cost efficiency influence adoption decisions among non-technical users. A quantitative method was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with data collected from 110 digital business students. The findings reveal that all five constructs significantly impact users’ willingness to adopt IPFS. This is supported by strong outer loading values (>0.70), high Average Variance Extracted (AVE >0.50), and high reliability scores (Cronbach’s alpha and composite reliability >0.70). These results validate the proposed adoption model and underscore the importance of behavioral and perceptual considerations in decentralized technology acceptance. Furthermore, the study highlights the relevance of integrating IPFS in academic and SME environments, aligning with Sustainable Development Goals (SDG 4, 9, and 16) by promoting secure, inclusive, and innovative digital infrastructure. Future studies are encouraged to include more diverse demographic groups and address regulatory and interoperability challenges to enhance scalability and adoption.
Data Driven A or B Testing Methodology for Website Effectiveness Qurotul Aini; Aulia Khanza; Vinkan Likita; Lase, Steven Harazaki; Kareem, Yasir Mustafa
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/t04mab20

Abstract

Website design and optimization decisions are often driven by subjective opinions, internal organizational preferences, or prevailing industry trends rather than empirical evidence derived from large-scale user interaction data, resulting in suboptimal performance and inconsistent user experiences. In digital environments characterized by high data volume and velocity, the absence of a structured experimentation methodology limits organizations’ ability to effectively leverage Big Data for continuous website improvement. This paper presents a comprehensive and systematic methodological guide to A or B testing as a data-driven approach for enhancing website effectiveness in data-intensive contexts. Unlike existing A or B testing guides that focus mainly on tools or isolated experimental outcomes, this study proposes an end-to-end framework integrating hypothesis formulation, scalable experimental design, statistical rigor, iterative learning, and practical decision-making into a unified and replicable process. The methodology outlines the complete A or B testing lifecycle, including alignment of business objectives with measurable data signals, development of testable hypotheses, controlled experiment implementation, large-scale data collection, and statistical analysis to ensure validity and significance of findings. The results demonstrate that a disciplined and continuous A or B testing program supported by Big Data analytics enables incremental yet compounding improvements in website performance. Through illustrative case examples, the study shows that relatively small, data-informed changes to website elements such as headlines, calls-to-action, images, and layout structures can lead to statistically significant gains in conversion rates, user engagement, and overall user experience. The paper concludes that A or B testing serves as a strategic Big Data analytics mechanism that supports evidence-based website optimization decisions grounded in empirical user behavior rather than intuition.
Co-Authors Andri Waskito Aulia Khanza Ester Ananda Natalia Kareem, Yasir Mustafa Marta Rodriguez Qurotul Aini Shofiyul Millah Vinkan Likita