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IAIC Transactions on Sustainable Digital Innovation (ITSDI)
Published by Pandawan Sejahtera Indonesia
ISSN : 26866285     EISSN : 27150461     DOI : https://doi.org/10.34306/itsdi
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science Materials Science & Nanotechnology
IAIC Transactions on Sustainable Digital Innovation (ITSDI e-ISSN : 2715-0461 , p-ISSN : 2686-6285 ) managed by Indonesian Association on Informatics and Computing (IAIC) and supported by Alphabet Incubator . ITSDI provides media to publish scientific articles from scholars and experts around the world related to the Computer Science/informatics, Computer engineering/computer systems, Software Engineering, Information Technology, and Information Systems, Circular Digital Economy, Cyber Security, Data Science, and Artificial Intelligence topics. All URL of published articles will have a digital object identifier (DOI).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 142 Documents
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Data-Driven Innovation for Circular Digital Economy in Sustainable Urban Development Chandra Lukita; Tessa Handra; Fitra Putri Oganda; Mackenzie Laurens
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 1 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i1.710

Abstract

The rapid advancement of digital technology has transformed how cities innovate and sustain their growth, making data-driven innovation a crucial element in achieving sustainable urban development. This study aims to examine the integration of data analytics, artificial intelligence, and Internet of Things within the framework of a circular digital economy to promote smarter, greener, and more resilient cities aligned with the Sustainable Development Goals. Using a Systematic Literature Review method, the research collected and analyzed publications from 2015 to 2024 obtained from major academic databases such as Scopus, ScienceDirect, and IEEE Xplore. The results show that data accessibility, interoperability, and digital infrastructure enhance efficiency in energy, mobility, and waste management, while digital tracking supports circularity and resource optimization. Governance that applies human-centered design further ensures inclusivity and transparency in urban systems. Overall, the findings highlight that data serves not only as a technological asset but also as a strategic driver for sustainable transformation. The study concludes that integrating data-driven innovation with circular economy principles strengthens collaboration among governments, industries, and communities, enabling cities to achieve long-term sustainability and contribute effectively to global goals such as innovation, responsible consumption, sustainable cities, and climate action.
The Implementation of ISO 9001:2015 in Drainage Project Execution Based on Failure Mode and Effect Analysis (FMEA) Mira Wikoyati; Endah Kurniyaningrum
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.713

Abstract

Urban drainage projects play a strategic role in controlling runoff and mitigating flooding. However, construction quality issues often arise during implementation, leading to channel failure. This study aims to analyze the impact of implementing the ISO 9001:2015 Quality Management System on the quality of drainage projects using the Failure Mode and Effect Analysis (FMEA) approach, through a case study of the Rasuna Said drainage channel in Kuningan, Jakarta. The research methodology combines primary and secondary data obtained through field observations, interviews, questionnaires based on ISO 9001:2015 clauses, and project document analysis. Quality risk identification is conducted using the FMEA method, with severity, occurrence, and detectability parameters assessed to determine the Risk Priority Number (RPN). The results show that the main failure modes with the highest risk levels include mismatched channel elevation and slope, loosely fitting channel element connections, uneven subgrade compaction, and initial sedimentation due to weak work environment controls. These risks are generally related to the field operational stage and the suboptimal application of the risk based thinking principle in ISO 9001:2015. The integration of the FMEA method with ISO 9001:2015 has been proven to identify and prioritize quality risks more systematically and support the development of measurable mitigation actions. This study concludes that the implementation of ISO 9001:2015, integrated with FMEA, can improve the effectiveness of quality control, minimize the risk of construction failure, and support the sustainability of urban drainage projects.
Customer Purchase Patterns and Loyalty in MSME Catering Businesses Using the RFM Method Suzyanty Mohd Shokory; Nadratun Nafisah Abdul Wahab; Jihan Zanubiya; Zuraidah Zainol
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.724

Abstract

The increasing competition in the catering industry necessitates a data-driven understanding of consumer behavior to support effective customer retention strategies. This study aims to identify customer purchase patterns and loyalty in MSME Catering using the RFM (Recency, Frequency, Monetary) method based on transaction data from January 2025 to May 2026. This research addresses a gap in the literature regarding the application of transaction-based analytics for customer loyalty in MSMEs, which previously relied more on surveys or subjective perceptions. A total of 564 transactions from 80 unique customers were analyzed quantitatively, processed using Google Sheets, and visualized with Tableau. The results indicate that 55 customers (68.75%) are classified as loyal, while 25 customers (31.25%) are new customers. RFM segmentation grouped customers into Champions, Loyal Customers, Potential Loyalist, Need Attention, and Lost Customers, with the majority in the Potential Loyalist, Need Attention, and Lost segments. In addition to descriptive statistics, the relationship between purchase frequency and monetary value was examined to provide deeper insights into customer behavior. The findings demonstrate that the RFM approach provides a structured understanding of customer loyalty and transaction value, supporting the development of targeted marketing strategies, including loyalty programs, reminder promotions, reactivation campaigns, and customer engagement initiatives. This study contributes a practical RFM-based analytical framework applicable to MSMEs to enhance retention and marketing effectiveness.
Artificial Intelligence Enhancing Financial Regulatory Compliance Through RegTech Governance Applications Wisnu Wira Atmadja Effendi; Maswanto Maswanto; Ma’mun Murod; Isabella Maria
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.716

Abstract

The increasing complexity of global financial regulatory frameworks poses significant challenges for financial institutions in ensuring compliance, managing risk, and maintaining operational efficiency, particularly in environments characterized by frequent regulatory updates and cross-jurisdictional requirements. This study aims to examine how Artificial Intelligence (AI) can be effectively applied to navigate complex regulatory frameworks by enhancing regulatory interpretation, compliance monitoring, and decision-making processes. A conceptual and analytical approach was adopted, combining a systematic review of recent Regulatory Technology (RegTech) literature with an analysis of AI techniques, including machine learning, natural language processing, and automated reasoning, as applied to regulatory compliance scenarios. Qualitative insights and illustrative use cases were employed to evaluate alignment between AI capabilities and regulatory demands in areas such as regulatory reporting, risk assessment, and anomaly detection. The findings indicate that AI-based systems have the potential to improve the accuracy, speed, and adaptability of compliance processes by supporting automated regulatory interpretation, identifying potential compliance risks, and enhancing monitoring of regulatory changes. When appropriately governed, AI may reduce human error and operational costs while increasing transparency and auditability. The study concludes that AI has strong potential to transform the way financial institutions navigate complex regulatory frameworks, but its effectiveness depends on robust data governance, explainable AI models, and alignment with ethical and legal standards, and it provides strategic insights for regulators and financial institutions seeking responsible adoption of AI in highly regulated financial environments.
Design and Development of an Augmented Reality Learning Medium for the Conservation of the Endemic Flora Balikpapan Ginger (Etlingera balikpapanensis) Fulkha Tajri M; Olivia Febrianty Ngabito; Denny Huldiansyah; Azzah Nafisah Sofyan; Muhammad Bintang Kurniawan; Surya Abdi Pratama
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 8 No 1 (2026): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v8i1.728

Abstract

Balikpapan Ginger (Etlingera balikpapanensis) is an endemic flora of East Kalimantan with significant ecological, historical, and economic value, yet it remains largely unknown among the general public, particularly students. This condition highlights the need for innovative learning media to support environmental awareness and conservation education in a more engaging and accessible manner. Although Augmented Reality (AR) has been widely applied in environmental and biological education, prior studies mainly focus on general species and lack contextual integration of locally endemic flora into conservation learning. This study addresses this gap by developing a location-specific AR-based learning application that integrates scientific botanical data with interactive visualization to enhance local environmental literacy. The development process follows the Multimedia Development Life Cycle (MDLC), including concept, design, material collection, assembly, testing, and distribution. The evaluation involved 15 respondents, including administrators and adult visitors of the Balikpapan Botanical Garden, using a five-point Likert scale to assess technical feasibility, educational value, engagement potential, conservation relevance, and technical stability. The results indicate a high level of acceptance, particularly in educational value and engagement aspects, demonstrating the effectiveness of the application as a learning medium. These findings suggest that AR-based applications can support environmental education by providing immersive and interactive learning experiences aligned with constructivist learning theory and Mayer’s Cognitive Theory of Multimedia Learning
The Influence of Brand Awareness and Social Media Marketing on Purchase Intention through Brand Trust Marviola Hardini; Qurotul Aini; Fitra Putri Oganda; Sheila Aulia Anjani; Richard Andre Sunarjo
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.719

Abstract

The rapid development of digital technology has transformed how businesses interact with consumers, making brand awareness is an important strategy to strengthen brand presence and influence consumer behavior in online environments. In increasingly competitive digital markets, companies must build strong and credible brand images to foster consumer confidence and encourage purchasing decisions. This study aims to analyze the effect of brand awareness on purchase intention through brand trust as a mediating variable. A quantitative research approach is employed using a survey method to collect data from 135 consumers who interact with brands through digital platforms, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between brand awareness, brand trust, and purchase intention. The results of the study reveal that brand awareness has a significant positive effect on brand trust and purchase intention, while brand trust also significantly influences consumers’ purchase intention and acts as a mediating variable between brand awareness and purchase intention. These findings indicate that effective brand awareness strategies not only improve brand visibility but also enhance consumer trust, which ultimately increases the likelihood of consumers making purchasing decisions. Therefore, this study provides theoretical contributions to the field of digital marketing by explaining the mediating role of brand trust in the relationship between digital branding and purchase intention, while also offering practical implications for businesses to strengthen digital branding strategies in order to build stronger consumer trust and improve market competitiveness in the digital era.
Analyzing the Gender Gap in Digital Financial Services Access Dwi Andayani; Muhtarom Muhtarom; Bonar Napitupulu
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.721

Abstract

This study examines the persistent gender disparity in digital financial inclusion, where Digital Financial Services (DFS) offer transformative opportunities but remain unevenly accessed by men and women. The background reveals that despite the rapid expansion of Fintech ecosystems and increased global adoption of digital financial tools, women continue to experience lower ownership and usage of digital accounts. The object of this research is to analyze the structural and social determinants contributing to the gender gap in DFS access and utilization. The proposed method adopts a mixed-methods approach, integrating quantitative analysis of global financial inclusion datasets with qualitative case studies of policies and programs explicitly designed to support women’s financial participation. The result indicates that digital literacy limitations, entrenched socio-cultural expectations, and restricted access to essential resources such as mobile devices, financial assets, and formal identification continue to reinforce systemic barriers preventing women from fully benefiting from digital finance advancements. The conclusion highlights that addressing this inequality requires gender-intentional strategies, inclusive design principles, and evidence-based policy intervention to ensure that DFS evolves not only as a technological innovation but also as an equitable instrument for financial empowerment and social inclusion.
Simulation-Based Evaluation of Portfolio Optimization Algorithms for Robo-Advisory Systems Chandra Lukita; Meria Zakiyah Alfisuma; Natasha Leonie
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.722

Abstract

This study investigates the performance of portfolio optimization algorithms in robo-advisory systems within the digital finance landscape. The research compares three approaches Modern Portfolio Theory (MPT), Post-Modern Portfolio Theory (PMPT), and a heuristic equal-weight model using a simulation-based computational framework with synthetic financial data under controlled marketconditions. Key evaluation metrics include Sharpe ratio, Sortino ratio, and maximum drawdown to assess risk-adjusted performance and downside protection. The results show that optimization-based models outperform the heuristic approach across all metrics. MPT achieves the highest Sharpe ratio (1.25), indicating strong overall risk-adjusted returns, while PMPT provides superior downside risk management with a higher Sortino ratio (1.60) and lower maximum drawdown (0.14). The heuristic model demonstrates the weakest performance due to its lack of adaptive allocation. These findings highlight the trade-offs between return optimization and risk sensitivity across different algorithms. Despite their effectiveness, the models are limited by reliance on historical data and simplified assumptions in the simulation environment. This study suggests that future robo-advisory systems should integrate artificial intelligence and behavioral finance to enhance adaptability, personalization, and decision transparency in dynamic market conditions.
A Qualitative Case Study on Fintech-Driven Modernization of Capital Market Infrastructure Untung Rahardja; Ratna Utami Wijayanti; Yunita Christy; Gabriel Fransiso
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.725

Abstract

By addressing inefficiencies, high operating costs, and transparency constraints in conventional systems, this study investigates the role of Financial Technology (fintech) in modernizing capital market infrastructure. The study examines the impact of cloud computing, Artificial Intelligence (AI), machine learning, and Distributed Ledger Technology (DLT) on pre-trade, trade, and post-trade processes using a qualitative case study approach and thematic analysis of secondary data from exchanges, fintech companies, industry reports, and regulatory documents. Unlike previous studies that mainly focus on fintech adoption in general financial services or individual technologies, this study provides an integrated analysis of multiple fintech technologies within capital market infrastructure modernization. The findings show that fintech significantly improves post-trade efficiency by reducing operational risks, accelerating settlement processes, and minimizing reliance on intermediaries. Cloud-based infrastructure enhances scalable data analytics and market accessibility, while AI and machine learning strengthen market surveillance and risk management through real-time monitoring and early detection of anomalous trading activities. Despite these benefits, implementation remains constrained by institutional readiness, cybersecurity risks, and regulatory complexity. The study highlights the importance of collaboration among regulators, traditional financial institutions, and fintech firms to ensure sustainable integration and effective risk mitigation. Taken together, the findings indicate that fintech plays a crucial role in creating a more efficient, transparent, and resilient capital market infrastructure.
The Impact of Gamification on Retail Investor Behavior: A Behavioral Finance Perspective Tomy Prasetia; Lista Meria; Kursih Sulastriningsih; Nolan Liam
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.727

Abstract

The rapid growth of commission-free, mobile-based trading apps has made it easier for retail investors to participate in financial markets while introducing gamification features that influence how they make decisions. This study examines how these gamified elements affect trading frequency, risk-taking, and cognitive biases, as well as the ethical and regulatory implications that arise. We conducted a systematic literature review of studies published between 2021 and 2025, analyzing peer-reviewed articles and regulatory reports focused on behavioral finance, gamification psychology, and fintech governance. The research asks three main questions: How do gamification features influence trading frequency? How do they affect investors’ risk-taking behavior? Which behavioral biases are most reinforced? Based on these, we formulated hypotheses to explore the relationships in detail. The findings show that animations, rewards, and social comparison features increase trading activity, encourage higher risk tolerance, and strengthen biases such as overconfidence and the dis-position effect. Ethical concerns, including misaligned incentives, potential behavioral manipulation, and weaker investor protection, highlight the need for responsible platform design and thoughtful regulatory oversight. Overall, the study contributes by connecting behavioral finance theory with gamification psychology, offering insights into the psychological mechanisms at play in digital investing. Future research should empirically test these hypotheses, investigate long-term investor outcomes, and develop ethical guidelines that balance engagement with responsible investing practices.

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