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All Journal Ranah Research : Journal of Multidisciplinary Research and Development The Indonesian Journal of Computer Science
Fitriani, Anita Nur
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

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IT Team Project Management Transformation Plan for TIC Company’s IT Division Fauzan Aldiansyah; Raharjo, Teguh; Fitriani, Anita Nur
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4413

Abstract

Nowadays, organizations are increasingly reliant on information technology to maintain efficient and effective internal systems, stay competitive, and meet the evolving needs of their customers. However, organizations facing challenges often include delays in project delivery, difficulties in managing workflows, and issues with accurately tracking progress and performance. The Information Technology Division of one of the testing, inspection, and certification companies in Indonesia is responsible for application development but frequently encounters operational issues such as development delays, unaddressed requests, difficulties in tracking project timelines and completions, and unclear job description alignments. This study examines Waterfall, Kanban, and Scrum Agile methodologies through case studies and Design Science Research Methodology to address these issues. Scrum Agile, with its principles and practices, is selected as the preferred solution for resolving these recurring problems. The research proposes transitioning project management to Scrum Agile methods and demonstrates how these methods effectively address several existing challenges. This approach results in the development of a new system that implements Scrum Agile for project management within the department. This research can enhance the efficiency and effectiveness of application development and improve project visibility and control for the organization. Additionally, it provides learning through comparative analysis to identify appropriate new methods and systems based on the case study.
Implementasi Kecerdasan Buatan dalam Manajemen Proyek Agile dalam Mengatasi Tantangan dan Memaksimalkan Dampak Lumbanraja, Harry Leonardo; Raharjo, Teguh; Fitriani, Anita Nur
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4155

Abstract

The Agile methodology, with an 80% adoption rate, often faces challenges leading to project failures. This study investigates using artificial intelligence (AI) to overcome these challenges through a systematic literature review of 44 papers. It examines AI's impact on key Agile phases: envision, speculate, explore, adapt, and close. Findings highlight AI's critical role in improving project outcomes by addressing implementation challenges. AI tools aid in risk assessment and project selection during planning, enhance effort estimation and task allocation in speculation, improve team communication and technical issue resolution in exploration, optimize systems in adaptation, and provide valuable insights in closure. The paper offers guidance on effective AI integration to enhance Agile Project Management success.
Maintaining Confidentiality and Security in the Utilization of Generative AI for IT Project Management Indriyani, Felia Sri; Raharjo, Teguh; Fitriani, Anita Nur
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 3 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i3.2072

Abstract

The use of Generative AI has become a growing trend in project management, supporting activities such as learning, document preparation, and decision-making. However, its adoption also raises concerns related to confidentiality and security due to the involvement of sensitive project data. Therefore, this study examines how Generative AI can be safely utilized across PMBOK Knowledge Areas in IT project management while maintaining data confidentiality and security. The research was conducted in two stages. The first stage involved two systematic literature reviews following the Kitchenham method: one examining the utilization of Generative AI in project management (17 primary studies) and another focusing on ethical considerations, policy implications, and data security issues related to Generative AI (36 primary studies). The second stage involved an expert assessment with five experts to evaluate the applicability of Generative AI across PMBOK Knowledge Areas, identify relatively safe input types, and determine key considerations for maintaining confidentiality and security. The results indicate that Generative AI can be applied across all PMBOK Knowledge Areas, however not all input types and information are considered safe. Text identified as the safest, source code as high-risk, confidential data as unsuitable for sharing, and privacy and data protection as the primary concern.
Leveraging Artificial Intelligence in Supporting Remote Information Technology Project Management: A Systematic Literature Review Prasetyo, Seto Adhi; Raharjo, Teguh; Fitriani, Anita Nur
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 3 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i3.2083

Abstract

The transition to remote IT project management presents unique challenges in collaboration, resource allocation, and adaptability. While Artificial Intelligence (AI) is increasingly demanded as a strategic enabler to manage these complexities, its specific application within remote IT environments, particularly through the principles-based PMBOK7 framework, remains underexplored. To address this literature gap, this study presents a Systematic Literature Review (SLR) analyzing peer-reviewed literature published between 2021 and 2026. The review identifies 11 empirically validated studies and extracted 8 unique AI implementations, namely machine learning, natural language processing, neural network, multi-agent systems, large language model, fuzzy logic, genetic algorithm, and probability graph models. These technological implementations are systematically mapped across the eight PMBOK7 performance domains and five primary areas of change in remote IT work. The findings indicate that while empirical AI implementation in this domain is still in its infancy, it fundamentally enhances aspects like stakeholder communication, team flexibility, data-driven project planning, and holistic view of the project for project managers. Ultimately, this study serves as a foundational stepping stone for global IT organizations transitioning toward AI-assisted distributed project management
Co-Authors Fauzan Aldiansyah Indriyani, Felia Sri Lumbanraja, Harry Leonardo Prasetyo, Seto Adhi Raharjo, Teguh Yudhanto, Iman Alfathan