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Decentralized Data Storage Using IPFS for Sustainable Blockchain Availability Improvement Aswadi Jaya; Muh Fahrurrozi; Susy Alestriani Sibagariang; Vinkan Likita; Henry Zainarthur
Blockchain Frontier Technology Vol. 5 No. 2 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i2.860

Abstract

The rapid expansion of digital ecosystems has highlighted the limitations of centralized data storage systems, which often struggle with data loss, censorship, and single points of failure. To address these challenges, this study explores the InterPlanetary File System (IPFS) as a decentralized data management solution that enhances security, availability, and sustainability in distributed information environments. Using the IPFS-KI framework, a descriptive qualitative methodology, this research examines the architectural design, operational mechanisms, and real-world implementations of IPFS. Through literature analysis, node simulations, and case based evaluation, the study investigates IPFS performance in maintaining data integrity, fault tolerance, and resilience against network disruptions and censorship. The findings reveal that IPFS provides improved data reliability, transparency, and scalability compared to conventional centralized architectures, although certain limitations remain in terms of node stability and hidden centralization. This study contributes to a broader understanding of how decentralized storage technologies like IPFS can support the development of more secure, equitable, and sustainable digital infrastructures.
Data Driven UI Colour Selection for Enhanced User Engagement Sandy Setiawan; Titih Nursugiharti; Fitra Putri Oganda; Henry Zainarthur
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1057

Abstract

This study highlights the importance of color selection in user interface (UI) design, as it can influence users’ perceptions, emotional responses, and levels of engagement. Many applications still rely on designers’ intuition without strong empirical evidence. The objective of this research is to develop a data-driven framework for UI color selection that can measurably enhance user engagement and satisfaction. The method involves collecting a large dataset of color schemes from various popular applications, followed by preprocessing steps such as normalization, clustering, and analysis of the relationships between colors and emotional responses. In addition, user interaction metrics and engagement data are analyzed to evaluate the impact of specific color combinations. The results show that certain color palettes consistently generate higher levels of engagement, with specific hues and contrast levels improving users’ attention and effectiveness in completing tasks. The analysis also identifies patterns that can serve as guidelines for designers in selecting colors that balance aesthetic appeal and functional performance. The conclusion of this study is that adopting a data-driven approach to UI color selection leads to a significant improvement in user engagement, while also providing practical guidance for designers and developers to optimize digital interface experiences.