Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Artificial Intelligence and Digital Business
Julaeha, Lia Siti
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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

Found 2 Documents
Search

 1 
Smart Service Design in Urban Rail: AI-Enhanced Blueprint, Digital Servicescape, and Passenger Experience at Jabodebek LRT Jatimulya Station Julaeha, Lia Siti; Riyandi, Irwan; Umbaran, Mohammad Dewa Lintang
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2386

Abstract

Urban rail systems are increasingly positioned as vital components of sustainable mobility, enabling modal shifts from private to public transport while reducing congestion and fostering urban growth. In Indonesia, the Jabodebek Light Rail Transit (LRT) represents a flagship project to modernize metropolitan transportation, yet its success depends not only on infrastructure but also on the quality of service design at the station level, where passengers evaluate safety, reliability, and comfort. Jatimulya Station, as a type-A terminal in the Bekasi corridor, highlights persistent challenges such as ticketing inefficiencies, overcrowding, inadequate wayfinding, and accessibility barriers, which undermine user satisfaction and expose the limitations of conventional operational frameworks. This study investigates how artificial intelligence can be integrated into service blueprinting and digital servicescape design to enhance passenger experience at Jatimulya Station. Using a qualitative approach supported by literature review, observations, interviews, and document analysis, the research employs thematic analysis to map passenger journeys, identify service encounter bottlenecks, and assess environmental factors affecting user perceptions. Findings demonstrate that AI-enhanced blueprinting enables predictive congestion management, dynamic staff allocation, and real-time adjustments, while digital servicescape innovations improve wayfinding, inclusivity, and transparency by synchronizing physical and digital touchpoints. Theoretically, this study extends established frameworks of service blueprint, servicescape, and service encounters into AI-driven contexts, while practically offering recommendations for PT Kereta Api Indonesia and policymakers to optimize station-level service delivery, improve passenger trust, and advance sustainable urban mobility.
The Role of AI-Driven Marketing Insights in Enhancing Financial Performance and Competitive Advantage Julaeha, Lia Siti; Ramdhan, Dadan; Winanto, Sujoko
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.5278

Abstract

This study explores the role of AI-driven marketing insights in enhancing financial performance and competitive advantage from an interdisciplinary business perspective. As organizations increasingly operate in data-intensive environments, artificial intelligence has emerged as a strategic tool capable of transforming marketing data into actionable insights that support managerial and financial decision-making. Using a qualitative research design with a library research approach, this study synthesizes conceptual and empirical literature from marketing, finance, and strategic management to examine how AI-driven marketing insights contribute to firm performance. The analysis reveals that AI-driven marketing insights play a critical role in improving decision quality, marketing efficiency, and financial accountability by linking marketing activities directly to measurable financial outcomes such as revenue growth, cost optimization, and return on investment. Furthermore, the integration of AI capabilities into marketing analytics strengthens firms’ ability to develop sustainable competitive advantage through superior customer understanding, faster market responsiveness, and enhanced strategic alignment between marketing and finance functions. The findings also highlight the importance of organizational integration and data-driven culture in maximizing the financial value of AI adoption. This study contributes to the literature by offering a holistic conceptual framework that positions AI-driven marketing insights as a strategic capability rather than a purely technological tool. The research provides valuable implications for academics and practitioners seeking to understand how artificial intelligence can be leveraged to align marketing strategies with financial performance and long-term competitiveness.
Co-Authors Ramdhan, Dadan Riyandi, Irwan Sujoko Winanto, Sujoko Umbaran, Mohammad Dewa Lintang