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Systematic Literature Review Journal
Published by International Forum of Researchers and Lecturers
ISSN : 30895162     EISSN : 3089428X     DOI : https://doi.org/10.70062/slrj.v1i1
Core Subject : Health, Science, Education, Social,
Computer Science & IT Health Professions Nursing Public Health Social Sciences Other
Systematic Literature Review Journal (SLRJ) is an academic journal published by IFREL, focusing on the publication of research findings derived from Systematic Literature Reviews (SLR). This journal provides a platform to showcase research that incorporates SLR methodologies across various disciplines, including computer science, technology, healthcare, education, and social sciences. Mission and Focus SLRJ aims to be a platform that unites diverse studies employing systematic and methodological literature reviews. The journal highlights the importance of objective processes for searching, selecting, and analyzing literature while contributing to identifying research gaps, key trends, and areas requiring further study. Objectives of SLRJ: Provide a platform for researchers to publish findings from systematic literature reviews in their respective fields. Enhance understanding of trends and patterns in existing scientific research. Serve as an essential reference for researchers, academics, and practitioners seeking comprehensive information on specific topics. Topics Covered SLRJ covers a wide range of topics related to SLR methodologies, including but not limited to: Cybersecurity Systems Artificial Intelligence and Machine Learning Information and Technology Management Healthcare and Medical Sciences Education and Curriculum Development Technological Advancements and Innovation Social Sciences and Psychology Submission and Review Process Articles submitted to SLRJ must adhere to high standards in terms of SLR methodology and critical analysis of the existing literature. The journal ensures a transparent and objective review process, guaranteeing the publication of only high-quality research. Each accepted article undergoes a rigorous peer-review process to ensure its validity, quality, and contribution to its respective field.
Arjuna Subject : Umum - Umum
Articles 26 Documents
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Can Artificial Intelligence Generate Convincing Accounting Research Articles? An Empirical Investigation Abalaka, James Nda; Sulaiman Taiwo Hassan; Abdullahi Ya'u Usman
Systematic Literature Review Journal Vol. 1 No. 3 (2025): July : Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i3.218

Abstract

This study investigates whether artificial intelligence (AI) can generate credible accounting research articles. If AI is capable of producing high-quality academic work, the authenticity and reliability of scholarly research could be at risk. Design/methodology/approach – Using ChatGPT, a research paper was generated on a meta-analysis examining the link between sustainability reporting and value relevance. After the initial draft was produced, references were manually inserted based on the citations provided by ChatGPT. The paper was then submitted unchanged for peer review. Findings – The AI-generated paper was of reasonably high quality, receiving two major revisions from independent experts in accounting and finance. While concerns remain about the accuracy of references and the validity of results, there is a possibility that reviewers might deem the paper publishable, as they are not obligated to verify every citation or replicate findings if the methodology appears sound. Originality/value – AI’s role in academic writing is still emerging, and its long-term implications for research integrity remain unclear. This issue is particularly pressing given the rapid advancements in AI technology.
A Comprehensive Study of Ethical Frameworks, Privacy Concerns, and Technological Implications for Secure Distributed Systems Sinaga, Rudolf; Frangky Frangky
Systematic Literature Review Journal Vol. 1 No. 4 (2025): October: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i4.150

Abstract

This systematic literature review examines the philosophy of science approaches to user security in distributed devices, such as IoT and Federated Learning. The review was conducted in response to the exponential growth of connected devices and the increasing security threats, including cyberattacks, data breaches, and unauthorized access. As distributed systems become more complex, traditional security approaches, such as cryptography and differential privacy, are often insufficient to address the ethical, philosophical, and contextual challenges that arise in these ecosystems. Distributed devices, especially in IoT and Federated Learning contexts, rely on vast amounts of personal data. This data, often stored or processed in decentralized environments, creates significant risks to user privacy and system integrity. As the number of connected devices grows, security risks multiply, creating challenges in maintaining user trust, privacy, and overall system resilience. Conventional techniques, such as encryption, only focus on technical aspects, often neglecting the deeper philosophical dimensions, such as the nature of knowledge, privacy, and fairness in these systems. These gaps highlight the need for a more nuanced approach that incorporates philosophical perspectives into security frameworks. This study uses a systematic literature review method based on the PICOC (Population, Intervention, Comparison, Outcome, Context) framework to analyze the relevance of epistemology, ontology, and ethics in strengthening system security. By examining the foundational principles of how knowledge is constructed (epistemology), what entities exist in the system (ontology), and the ethical considerations around data and user privacy (ethics), the review provides a comprehensive understanding of how philosophical concepts can be integrated into the design and implementation of security systems in distributed environments. The results reveal that epistemological principles, such as the verification and validation of data sources and models, can significantly improve the reliability and trustworthiness of distributed systems.  
Digital Health Innovations in Environmental Risk Monitoring: A Literature Review Augustinus Robin Butarbutar; Jilly Toar; Priscilia Pingkan Mamuaja
Systematic Literature Review Journal Vol. 1 No. 3 (2025): July : Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i3.225

Abstract

Environmental health risks, including air pollution, unsafe water, and climate-sensitive diseases, remain pressing global challenges that continue to threaten public well-being. Conventional monitoring systems are typically manual, costly, and geographically limited, making it difficult to provide timely and accurate data for intervention. This study explores how digital health technologies—specifically mobile health (mHealth), the Internet of Things (IoT), artificial intelligence (AI), and remote sensing—are applied to strengthen the monitoring and management of environmental health risks. A structured literature review was carried out by synthesizing 87 peer-reviewed articles published between 2013 and 2024, using an evaluation framework built on keyword clustering, metadata filtering, and multi-criteria scoring to assess usability, scalability, interoperability, and relevance to health outcomes. Findings show that mHealth platforms are highly accessible and user-friendly but often face limitations in integration with broader health systems. IoT and AI technologies offer strong scalability and predictive capability, particularly in real-time risk detection, though they are hindered by interoperability issues across platforms. Meanwhile, remote sensing is powerful for capturing large-scale environmental data but lacks direct connections to health-specific applications. The analysis identifies a critical gap in the integration of these technologies, emphasizing the need for cross-sector collaboration to build more robust, interoperable systems. Additionally, the findings highlight the importance of ethical considerations, validation processes, and interdisciplinary approaches to ensure sustainable and impactful implementation. Overall, this study provides not only a comparative synthesis of current practices but also a methodological roadmap to guide future digital innovations in environmental health. By bridging technological potential with practical application, it underscores the urgent need for integrated strategies that can better address the growing complexity of environmental health risks in the modern era.
The Impact of Artificial Intelligence on the Accounting Profession : A Conceptual Analysis at OAGF Abalaka James Nda; Sulaiman Taiwo Hassan; Abdullahi Ya'u Usman
Systematic Literature Review Journal Vol. 1 No. 4 (2025): October: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i4.226

Abstract

This paper explores the transformative influence of artificial intelligence (AI) on the accounting profession, particularly within the Accountant General of the Federation (OAGF). The research investigates how AI-driven innovations are reshaping traditional accounting practices and redefining the role of accountants. By conducting a systematic literature review, this study identifies three primary dimensions of AI’s impact: the automation of repetitive tasks such as data entry, transaction processing, and reconciliation; enhanced data analytics capabilities, which include predictive modeling and real-time decision support; and the evolution of accountants' roles toward more strategic and value-added activities, such as financial advisory and risk management. The automation of routine processes through AI allows accountants to focus on higher-level tasks that require judgment, creativity, and expertise, ultimately enhancing the overall efficiency of the accounting function. Furthermore, AI’s advanced data analytics tools provide more accurate insights, enabling accountants to offer more effective financial guidance and make more informed decisions. As AI reduces the time spent on manual processes, accounting professionals can improve their role in advising on business strategy, improving risk management, and identifying new growth opportunities. The study’s findings underscore the importance of embracing AI in the accounting profession, not only to improve operational efficiency, reduce costs, and scale operations but also to enable accountants to stay competitive in a rapidly evolving technological landscape. The paper concludes by emphasizing that adopting AI is essential for accountants to remain relevant and continue providing valuable contributions to their organizations. Future research should focus on the long-term implications of AI on accounting ethics and the development of necessary skills for accounting professionals to thrive in the age of AI.
Development Strategy of Intensive System of Vaname Shrimp (Litopenaeus vannamei) Cultivation Business at CV Jaya Tirta Vannamei, Probolinggo, East Java Andi Rusdi Walinono; Rieke Nur Safitri; Ilyas
Systematic Literature Review Journal Vol. 1 No. 4 (2025): October: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i4.227

Abstract

This study aims to analyze the development strategy of vannamei shrimp (Litopenaeus vannamei) cultivation business in the intensive pond system at CV Jaya Tirta Vannamei, Probolinggo, East Java. The research applied a qualitative descriptive approach combined with SWOT analysis to evaluate both internal and external factors affecting the business. Data were obtained through observation, interviews, and documentation, then processed to generate alternative development strategies. The results show that CV Jaya Tirta Vannamei possesses strong internal resources such as experienced human resources, reliable production facilities, and good management capabilities. Externally, the company benefits from the rising demand for vannamei shrimp in domestic and global markets, the availability of modern aquaculture technology, and supportive government policies. Nevertheless, some challenges exist, including fluctuating shrimp prices, vulnerability to disease outbreaks, and relatively high operational costs, which may influence business continuity if not addressed effectively. Based on the SWOT analysis, the most appropriate development strategy is the S-O (Strengths–Opportunities) strategy, with an alternative strategy score of 3.72. The recommended strategies are: (1) increasing shrimp production through the adoption of advanced and sustainable cultivation technology, (2) developing and maintaining a reliable water quality management system to enhance productivity, (3) utilizing skilled human resources to strengthen innovation in cultivation techniques, and (4) ensuring the availability of sufficient and quality feed to support continuous production growth. In conclusion, implementing the S-O strategy provides an effective pathway for CV Jaya Tirta Vannamei to optimize its internal strengths in response to external opportunities. By improving technology application, strengthening resource utilization, and enhancing production management, the company can secure competitive advantage, increase productivity, and ensure long-term sustainability in the rapidly growing aquaculture industry.
Integration of Critical Thinking in Intelligent Algorithms for Hoax Detection on Social Media Platforms Milli Alfhi Syari; Hermansyah Sembiring; Muhammad Fadlan Siregar
Systematic Literature Review Journal Vol. 1 No. 4 (2025): October: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i4.229

Abstract

The rapid growth of social media as a primary channel for information dissemination has triggered a significant surge in the distribution of hoaxes, potentially damaging social order, instigating mass disinformation, and threatening national security. This research aims to design an intelligent algorithm for hoax detection by integrating a critical thinking approach into Natural Language Processing (NLP)-based text processing. The algorithmic model is built using a combination of linguistic features, argument logic, and cognitive indicators such as the detection of unsubstantiated claims, identification of source bias, and evidence testing. To ensure accountability and transparency of the system, an Explainable AI (XAI) approach is applied so that classification results can be understood by non-technical users. The research results show that integrating critical thinking significantly improves detection accuracy to 93.1%, with an increase in precision and recall for detecting hoaxes based on emotional narratives. Beyond technical aspects, this model aligns with the mandate of Law of the Republic of Indonesia Number 11 of 2008 concerning Information and Electronic Transactions (ITE Law), particularly Article 28 paragraph (1), which prohibits the dissemination of false and misleading news that harms the public. Therefore, this system is not only scientifically relevant but also supports law enforcement and strengthens digital literacy in the post-truth era. These findings are expected to be a strategic contribution to the development of an ethical, critical, and responsible digital ecosystem.

Page 3 of 3 | Total Record : 26

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