IAIC Transactions on Sustainable Digital Innovation (ITSDI)

The Implementation of ISO 9001:2015 in Drainage Project Execution Based on Failure Mode and Effect Analysis (FMEA)

Mira Wikoyati — 2026-03-03

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.

Decision Making on Breakwater Type Selection on Tidung Island, Thousand Islands

Bram Soepradono — 2026-03-05

Tidung Island, a major tourist destination in the Thousand Islands, faces coastal erosion caused by wave energy, tidal currents, and anthropogenic activities, which threaten coastal ecosystems, marine tourism quality, and residential areas. Coastal protection measures have been implemented through wave protection structures. However, their performance has been suboptimal due to limited maintenance, design incompatibility with local hydro-oceanographic conditions, and the absence of a systematic approach for selecting breakwater types. This study aims to identify the criteria and sub-criteria influencing breakwater selection and determine the most suitable structure for Tidung Island using the Analytic Hierarchy Process (AHP). The AHP model integrates technical, environmental, socio-economic, field condition, and construction method aspects, based on secondary hydro-oceanographic data (tides, wind, wave height, and effective fetch) and expert judgments through pairwise comparisons. The results show that technical aspects have the highest priority (0.312), followed by environmental aspects (0.268), field conditions (0.201), socio-economic factors (0.127), and implementation methods (0.092), with all consistency ratio values below 0.10. The selected structure is a hollow cube breakwater with a filter-coated rockfill foundation, as it provides an optimal balance between technical performance, cost efficiency, ease of implementation in shallow waters, and manageable environmental impacts. This AHP-based model can support sustainable coastal protection decision-making.

Analyzing the Gender Gap in Digital Financial Services Access

Dwi Andayani — 2026-04-01

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 — 2026-04-07

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 market
conditions. 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.

The Influence of Brand Awareness and Social Media Marketing on Purchase Intention through Brand Trust

Marviola Hardini — 2026-04-10

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.

Leadership, Workload, and Culture: Impact on Organizational Performance through Service Quality

Marvel Marvel — 2026-04-14

Organizational performance in the healthcare sector is a multidimensional construct that includes financial outcomes, internal processes, learning and growth, and customer-related indicators. This study examines the effects of leadership style, workload, and organizational culture on hospital organizational performance, with service quality as a mediating variable. A quantitative cross-sectional design was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS. Data were collected from nurses and patients at a leading private hospital in Tangerang, Indonesia, during November–December 2024. The analysis was conducted using valid responses from nurses and patients, supported by secondary data obtained from financial reports, press releases, and quarterly company presentations. The findings reveal that organizational culture has a significant positive effect on service quality and contributes to selected dimensions of organizational performance, particularly financial performance and learning and growth, through service quality mediation. In contrast, leadership style and workload do not show significant effects on service quality, indicating that hospital service quality may be more strongly shaped by shared organizational values, standardized procedures, and institutional culture than by individual leadership practices or perceived workload. Several performance dimensions, including internal process and customer-related outcomes, also show weak explanatory power, suggesting that these outcomes may be influenced by other factors beyond the proposed model, such as clinical interaction, patient expectations, operational efficiency, and external service conditions. This study contributes to organizational behavior and healthcare management literature by demonstrating the central role of organizational culture and service quality in strengthening hospital performance. The findings offer practical implications for hospital managers to develop a strong, structured, and service-oriented culture to improve healthcare delivery and organizational sustainability.

Customer Purchase Patterns and Loyalty in MSME Catering Businesses Using the RFM Method

Suzyanty Mohd Shokory — 2026-04-19

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.

A Qualitative Case Study on Fintech-Driven Modernization of Capital Market Infrastructure

Untung Rahardja — 2026-04-17

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 — 2026-04-19

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.