Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Information Systems and Informatics
Segooa, Mmatshuene Anna
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis Mogoale, Phumzile Dorcus; Pretorius, Agnieta Beatrijs; Mogase, Refilwe Constance; Segooa, Mmatshuene Anna
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1035

Abstract

Artificial Intelligence (AI) tools can revolutionize literature review practices by transforming the research landscape towards more efficient and reliable review processes. While conducting literature can be challenging and time-consuming, there is a plethora of AI powered tools which uncover potential solutions to the challenge. AI tools may reduce the time spent on repetitive tasks, allowing scholars to focus more on critical analysis and interpretation. Due to the rising abundance of AI tools, it is difficult to decide which AI tools are best for individual research problems or projects. While concerns exist around the ethical and quality consequences of using AI. The study aims to explore the usage of AI tools on the systematics literature review process, specifically focusing on their effectiveness in various stages and ethical concerns. IEEE and MDPI Journal papers from 2020 to 2024 were reviewed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RobotReviewer, Covidence and EPPI-Reviewer are AI tools commonly used. These AI tools are designed to support different aspects of the systematic literature review process by offering capabilities such as problem formulation, literature search, inclusion screening and quality assessment. AI tools demonstrate improved effectiveness of literature searches, screening processes and data extraction. Language and content presentation, incorrect citation and plagiarism, grammar and spelling errors may be ren when utilizing AI. Concerns related to data quality, biases, and the need for human oversight were identified.
Robotic Process Automation Readiness Barriers and Enablers in South Africa’s Energy Supply Chain Motsoeneng, Mariah Thokozile; Segooa, Mmatshuene Anna; Motjolopane, Ignitia; Kgopa, Alfred Thaga
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1281

Abstract

South Africa’s energy industry faces ongoing challenges including power shortages, ageing infrastructure, and supply chain inefficiencies, while, limited empirical evidence exists on how organisations in this industry prepare for Robotics Process Automation (RPA) adoption. This study examines the RPA readiness barriers and enablers within the supply chain of South Africa’s energy industry. The research adopts a qualitative design grounded in the Technology-Organisation-Environment (TOE) framework and the Awareness, Desire, Knowledge, Ability, Reinforcement (ADKAR) change management model to connect technological capability with individual and organisational readiness for change. Data were gathered through semi-structured interviews with 18 professionals representing eight stakeholder groups, including supply chain managers, IT specialists, process improvement leads, and employees affected by automation. Four key readiness barriers emerged: readiness gaps (61 mentions), organisational misalignment (158), infrastructure strain (83), and job security and resistance (60). Corresponding enablers included leadership accountability, RPA governance and alignment frameworks, readiness checklists, structured communication protocols, KPI frameworks, capability audits, investment planning, psychological safety, and regulatory alignment mechanisms. The integration of TOE and ADKAR offers a novel dual-lens perspective that extends existing knowledge. The findings provide practical guidance for managers and policymakers seeking to strengthen organisational systems and structures with human readiness factors in emerging economies.
Co-Authors Kgopa, Alfred Thaga Mogase, Refilwe Constance Mogoale, Phumzile Dorcus Motjolopane, Ignitia Motsoeneng, Mariah Thokozile Pretorius, Agnieta Beatrijs