Article Per Year (5 Year)
p-Index From 2021 - 2026
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All Journal Journal of Information Systems and Informatics Indonesian Journal of Electrical Engineering and Computer Science The Indonesian Journal of Computer Science
Esiefarienrhe, Bukohwo Michael
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : The Indonesian Journal of Computer Science

 1 
Framework for Project Sustainability for Power Installations Using Business Intelligence Approach: A Systematic Literature Review Esiefarienrhe, Bukohwo Michael; Maine, Itumeleng Michael
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i5.3402

Abstract

The growing concerns about environmental sustainability and energy conservation have led to increased interest in optimizing electricity consumption and billing processes in various projects. This research article presents a comprehensive study on the development and application of Business Intelligence (BI) frameworks for enhancing project sustainability through data-driven energy management. Through the integration of BI tools and techniques, this research investigates the analysis of electricity consumption patterns, billing accuracy, and cost-effectiveness in diverse project contexts. The article emphasizes the significance of data preprocessing, statistical analysis, and predictive modelling in uncovering valuable insights to support informed decision-making. Additionally, the review examines the concept of project sustaibility, emphasizing its significance in achieving desired outcomes, meeting stakeholder expectations, and ensuring the project’s viability in an ever-changing environment. Traditional project management approaches often fail to adequately address sustainability concerns, leading to project failures or limited long-term impact. Hence, the review highlights the growing importance of leveraging BI-driven frameworks to enhance project sustainability in various sectors, including in Information and Communication Technology (ICT) domain. The Systematic literature review (SLR) method was used involving the scooping of 230 articles from over 8 global academic databases. With the use of exclusion criteria, only 61 articles were used in the study. The analysis of the articles shows that 57% were journal articles, 39% were conference proceedings, 2% were thesis/dissertations and 2% were generic. Within the scope of this literature review, key terms and keywords were identified to provide insights into the development of a novel BI-driven framework for project sustainability. Consequently, future research directions are identified to further explore the integration of renewable energy sources, AI and machine learning applications, and behaviour-based energy management strategies within BI frameworks for sustainable project outcomes. This review lays the foundation for future research endeavours in developing innovative BI-driven frameworks that foster sustainable practices and contribute to a greener and more resilient future across diverse industries and projects.
Risk assessment using Business Intelligence framework for organizations: A Systematic Literature Review Esiefarienrhe, Bukohwo Michael; Khutswane, Thoriso
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3457

Abstract

Today many organizations are facing different kinds of risks as they are migrating towards new technologies. Risk assessment is one of the methods that were developed to help with identifying, assessing, and managing risks. Several studies have been conducted regarding risk assessment and business intelligence, however few studies have been conducted on how both can be integrated and use. A systematic literature review is conducted to understand the importance of risk assessment and business intelligence for organizations. Due to the relevance of BIS and the need for risk analysis before development and implementation, there is need to critically examine literaure to understand what has been done and the gap that exist for future researchers to implement. Therefore this study use the Systematic Literature Review methodology to collect 125 academic publications from over 6 academic, business and research databases for review. Inclusion and exclusion criteria were applied to the papers proning them to 65 and when quality assessment were applied, the total paper obtained amounted to 25 which were eventually used for the review. The results obtained from the review study showed that although there are much publication related to business intelligence and risk assessment, most of them did not incorporate quality assessment, rigorous testing, creation of new analytical tools, application of AI, and deep learning algorithms into developing their business intelligence systems. Future research focus areas resulting from this study were also highlighted in the conclusion session of this study.
Co-Authors Khutswane, Thoriso Maine, Itumeleng Michael Mamapule, Siyabonga Moemi, Thusoyaone Joseph Obagbuwa, Ibidun Christiana