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Science Information System and Technology
Published by Westscience Press
ISSN : 30261120     EISSN : 30255120     DOI : https://doi.org/10.58812/wsist.v1i02
Core Subject : Science,
Computer Science & IT
West Science Information System and Technology is a scholarly journal dedicated to the exploration and advancement of knowledge in the field of information systems and technology. The journal aims to publish high-quality research articles that contribute significantly to the understanding and development of information systems and technologies in the Western world. The journal covers a wide range of topics related to information system design, development, implementation, and management. It encompasses areas such as information systems development methodologies, database management systems, information technology infrastructure, enterprise systems, decision support systems, information systems security and privacy, human-computer interaction, and ethical and social implications of information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 150 Documents
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Analysis of Privacy Protection Mechanism and Information Security Policy as Antecedents of User Trust in E-Commerce Platforms in Indonesia Agus Purwanto; Joko Santoso; Affan Irfan Fauziawan; I Wayan Karang Utama; Anggun Nugroho
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3045

Abstract

The rapid growth of e-commerce in Indonesia has increased the importance of personal data protection and information security in building consumer confidence. This study analyzes the effects of Privacy Protection Mechanisms and Information Security Policies on User Trust in e-commerce platforms in Indonesia. A quantitative research approach was employed using a cross-sectional survey involving 150 respondents who had experience using e-commerce platforms. Data were collected through a structured questionnaire measured using a five-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling with SmartPLS 3. The measurement model demonstrated satisfactory reliability and validity. The structural model showed that Privacy Protection Mechanisms had a positive and significant effect on User Trust, while Information Security Policies also had a positive and significant effect on User Trust. The model explained 61.7% of the variance in User Trust, with an R² value of 0.617 and a Q² value of 0.428, indicating satisfactory explanatory and predictive relevance. Information Security Policies emerged as the strongest predictor of User Trust. These findings confirm that both privacy governance and information security management are essential for strengthening consumer confidence in e-commerce platforms. E-commerce providers should therefore improve privacy transparency, user control, authentication, transaction security, fraud prevention, and incident response mechanisms to support sustainable digital trust.
Exploring the Mechanisms of Efficiency and Scalability in Blockchain: A Qualitative Study of Distributed Ledger Algorithms in Decentralized Networks in Bintan, Riau Islands Dodi Setiawan; Sri Sutjiningtyas; A. Eka Hermia Fitrianingsy; Ronald Naibaho; Yusup Ridwan
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3046

Abstract

Blockchain consensus mechanisms are critical for ensuring security, efficiency, and scalability in decentralized networks. This study qualitatively examines ten widely used consensus algorithms—Proof of Work (PoW), Proof of Stake (PoS), Delegated PoS (DPoS), PBFT, Raft, Proof of Authority (PoA), Hybrid PoW/PoS, DAG/IOTA, Hashgraph, and Tendermint—within the research context of Bintan, Riau Islands, Indonesia. Performance was evaluated through literature review and simulated network observations, focusing on transaction throughput (TPS), latency, energy consumption, and network stability. Results indicate that DAG/IOTA and Hashgraph achieve the highest throughput with minimal latency, making them suitable for IoT and enterprise-scale applications. PoS and PoA offer energy-efficient alternatives, while PoW provides high security at the cost of high energy usage. Hybrid PoW/PoS demonstrates balanced performance across multiple metrics. Qualitative analysis highlights trade-offs among energy efficiency, throughput, latency, and decentralization. These findings provide practical guidance for selecting consensus mechanisms according to network requirements, operational constraints, and sustainability considerations, contributing a consolidated perspective on blockchain efficiency and scalability.
Analysis of Technology and Organizational Readiness for Cloud-Based LMS Implementation in Higher Education Laila Qadriah; Istiarsyah Istiarsyah
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3061

Abstract

This study examines the technological and organizational readiness of higher education institutions in Indonesia for the implementation of a cloud-based Learning Management System (LMS). A quantitative approach with a cross-sectional survey design was employed involving 155 respondents consisting of lecturers, academic and administrative staff, information technology personnel, and academic managers. Data were collected using a structured questionnaire measured on a five-point Likert scale and analyzed using IBM SPSS Statistics version 25. The analysis included descriptive statistics, validity and reliability tests, classical assumption tests, Pearson correlation, and multiple linear regression. The results indicate that technological readiness was categorized as high, with a mean score of 4.03, while organizational readiness recorded a mean score of 3.91. Overall cloud-based LMS implementation readiness also reached a high level, with a mean score of 3.98. Technological readiness had a positive and significant effect on LMS implementation readiness, while organizational readiness demonstrated a stronger significant effect. Together, both dimensions explained 61.5% of the variance in implementation readiness (R² = 0.615). These findings indicate that successful cloud-based LMS implementation requires not only adequate technological infrastructure but also strong managerial commitment, institutional policies, human resources, training, financial support, and inter-unit coordination.
Are Synthetic Data and Privacy Protection the Future of Artificial Intelligence Development? Istiarsyah Istiarsyah; Tina Isnaeni; Rival Pahrijal
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3091

Abstract

The rapid advancement of Artificial Intelligence (AI) has created increasing dependence on large-scale datasets, while simultaneously generating significant legal challenges related to privacy protection, data governance, and individual rights. This study examines whether synthetic data and privacy protection mechanisms can become the future foundation of responsible AI development through a normative legal analysis approach. The research analyzes relevant legal frameworks, regulatory principles, and conceptual developments concerning personal data protection, AI governance, and the utilization of synthetic data as a privacy-preserving alternative. The findings indicate that synthetic data provides substantial potential to reduce privacy risks by minimizing direct exposure to identifiable personal information while improving data accessibility for AI training and innovation. However, synthetic data does not automatically eliminate legal concerns, particularly regarding re-identification risks, accountability allocation, transparency, and regulatory uncertainty. The analysis demonstrates that effective AI governance requires a shift from traditional data protection approaches toward adaptive frameworks based on risk assessment, privacy-by-design principles, and responsible technology development. The study argues that synthetic data should not be viewed as a complete replacement for real-world data but as a complementary mechanism within a broader privacy-preserving AI ecosystem. Therefore, the future of artificial intelligence development depends on the integration of technological innovation and legally enforceable privacy protection frameworks that ensure transparency, accountability, and respect for fundamental rights.
Bibliometric Analysis of Hybrid Cloud Computing Loso Judijanto
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3092

Abstract

Hybrid cloud computing has emerged as a critical technological paradigm that enables organizations to combine the flexibility of public cloud services with the control and security of private cloud infrastructures. This study aims to examine the intellectual development, research trends, collaboration patterns, and emerging themes in hybrid cloud computing literature using a bibliometric analysis approach. Data were collected from the Scopus database and analyzed using VOSviewer to identify publication trends, influential literature, author and country collaboration networks, and keyword co-occurrence patterns. The findings reveal that hybrid cloud computing research has expanded significantly, with major contributions focusing on computation offloading, cloud-edge integration, Internet of Things (IoT), resource management, task scheduling, and optimization algorithms. Citation analysis highlights those influential studies primarily address improving computational efficiency, reducing latency, and optimizing resource utilization in distributed cloud environments. The collaboration analysis demonstrates that countries such as China, India, and the United States play central roles in advancing hybrid cloud research, although global collaboration remains concentrated within specific research networks. Furthermore, keyword analysis indicates a transition from traditional cloud infrastructure studies toward advanced research areas involving artificial intelligence, edge computing, cybersecurity, energy efficiency, and green computing. This study provides valuable insights into the evolution of hybrid cloud computing research and identifies future opportunities for developing intelligent, secure, and sustainable cloud ecosystems.
Zero Trust Architecture Research Trends: A Bibliometric Study Loso Judijanto; Rizki Dewantara
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3093

Abstract

Rapid evolution of cyber threats, cloud computing and digital transformation have led to increased need for adaptive and resilient cybersecurity framework. Zero Trust Architecture (ZTA) has been developed as an advanced security model that is designed to overcome limitations of the existing approaches based on perimeter-based security through its features of continuous verification, least-privilege access, and identity-centric protection. This paper is devoted to analyzing the global research development, intellectual structure and trends of Zero Trust Architecture through the use of bibliometric analysis methodology. The data for analysis were collected from Scopus database by means of keywords relating to “Zero Trust Architecture” and “Zero Trust Security” and then were analyzed using VOSviewer tool. The aspects that are covered by the analysis include the dynamics of publications, citation impact, influential authors, international and country collaboration, co-occurrence of keywords, themes and research patterns. It can be concluded from the findings that ZTA research has expanded greatly and is mostly concentrated on topics of network security, authentication, trusted computing, network architecture, and access control. Also, the recent trends in ZTA research indicate increased use of ZTA in combination with new technologies, including artificial intelligence, machine learning, blockchain, IoT, federated learning and cloud computing. Collaboration analysis reveals the international and interdisciplinary character of ZTA research, which involves contributions from different countries, scientific institutions and cybersecurity communities. The results of the research allow understanding the evolution of ZTA and identifying future opportunities in the area of intelligent, adaptive and decentralized cybersecurity architectures.
Data Stewardship Research Trends in Organizations Loso Judijanto
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3094

Abstract

Data stewardship has become an increasingly important research area as organizations recognize data as a strategic asset requiring effective governance, quality management, and responsible utilization. This study aims to examine the development, intellectual structure, and emerging trends of data stewardship research in organizational contexts through a bibliometric analysis approach. Data were collected from the Scopus database using relevant keywords related to data stewardship and organizations, followed by performance analysis and science mapping using VOSviewer. The findings reveal that data stewardship research is strongly influenced by foundational studies on the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, data governance, and research data management. Keyword analysis indicates that data stewardship is closely associated with data management, metadata, data quality, information management, data sharing, privacy, and artificial intelligence. The temporal analysis shows a shift from traditional data management practices toward broader organizational capabilities involving ethical data governance, responsible data sharing, and digital transformation. Collaboration analysis demonstrates that research contributions are concentrated in leading countries and institutions, particularly in the United States and healthcare-related research environments, while international collaboration continues to expand. This study contributes by providing a comprehensive overview of the intellectual development of data stewardship research and identifying future opportunities for integrating governance, technology, and organizational capability perspectives.
Internet of Things Infrastructure Research Mapping Loso Judijanto
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3095

Abstract

The fast pace of developing the concept of digital transformation made the Internet of Things infrastructure a crucial basis for connected systems, intelligent applications, and sustainable technological ecosystems. The purpose of this study is to conduct a bibliometric analysis and identify the patterns of development, intellectual structure, collaboration, and current research trends in the IoT infrastructure. Scientific publications related to the topic were gathered and analyzed using the software VOSviewer in order to investigate citation performance, co-authorship network, collaborations between institutions and countries, co-occurrence of keywords, thematic dynamics, and patterns of research density. It was found out that there has been a considerable increase in the amount of IoT infrastructure research, with cybersecurity, secure communication, edge computing, fog computing, smart cities, and intelligent infrastructure being identified as leading research topics. Citation analysis suggests that papers dedicated to IoT security framework, intrusion detection system, critical infrastructure protection, and distributed computing architecture have had a significant impact on this field. Collaboration analysis has indicated the presence of strong international research networks with China, India, USA, Germany, and the UK being recognized as the key contributors. Finally, it has been found out that the research has evolved from addressing connectivity challenges to advanced research which includes artificial intelligence, machine learning, privacy protection, energy efficiency, and autonomous IoT systems.
Bibliometric Analysis AI-Based Decision Analytics Loso Judijanto; Hanifah Nurul Muthmainah
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3096

Abstract

The rapid advancement of artificial intelligence (AI) has transformed decision-making processes across various domains by enabling data-driven insights, predictive capabilities, and intelligent automation. This study aims to examine the development, intellectual structure, and emerging trends of research on AI-based decision analytics through a bibliometric analysis approach. Data were collected from the Scopus database using relevant search terms related to artificial intelligence and decision analytics. The study applies bibliometric techniques, including performance analysis, citation analysis, co-authorship analysis, keyword co-occurrence analysis, thematic evolution analysis, and density visualization using VOSviewer. The findings indicate that artificial intelligence, machine learning, deep learning, and clinical decision support systems represent the dominant research themes shaping this field. Highly cited studies demonstrate increasing scholarly attention toward ethical considerations, explainability, transparency, and trust in AI-driven decision systems. The collaboration analysis reveals that research development is supported by extensive international networks, with countries such as Germany, the United States, India, and China serving as influential contributors. Furthermore, the temporal analysis indicates a shift from algorithm-focused research toward human-centered and responsible AI applications. This study contributes to the literature by providing a comprehensive mapping of AI-based decision analytics research and identifying future directions related to explainable AI, trustworthy decision systems, and interdisciplinary applications across healthcare, business, and other complex decision environments.
Modular Integration of Raw NASA-TLX and VisAWI-S in UIX-Probe: An Analytics Dashboard for Supporting UX Evaluation Anugrah Nur Rahmanto; Retno Damayanti; Muhammad Abel Rif'at Nandito
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3060

Abstract

Evaluation of User Interface (UI) and User Experience (UX) typically relies on several questionnaire instruments that are administered and scored separately, making score aggregation and cross-method triangulation labor-intensive. UIX-Probe is a web-based multi-method UI/UX assessment platform that already integrated the System Usability Scale (SUS), the Technology Acceptance Model (TAM), A/B testing and the Web Content Accessibility Guidelines (WCAG), but lacked instruments for two constructs central to user experience: subjective mental workload and perceived visual aesthetics. This paper reports the design, implementation and workflow of two new modules integrated into UIX-Probe Raw NASA-TLX and the Short Visual Aesthetics of Websites Inventory (VisAWI-S) with a focus on the analytics dashboard that turns raw responses into interpretable output for developers and interface designers. The dashboard provides a composite score with automatic classification, a per-dimension mean comparison, per-question response distributions, a per-respondent results table, respondent demographics, and automatically generated narrative descriptions, all exportable to Excel. The system was built using the Waterfall SDLC on a Laravel 10 + React.js (Inertia.js) architecture. Functionality was verified under real-world deployment: five independent developer teams created and distributed their own evaluation surveys on the platform, collecting 115 responses across five surveys. The four surveys using the new modules produced Raw NASA-TLX composite scores of 10.99–21.75/100 (all Moderate) and VisAWI-S composite scores of 4.23–5.81/7 (Positive to Very Positive). All three verification criteria were met: 5/5 teams configured a survey successfully, every survey obtained real respondents, and every dashboard rendered without error.

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