Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal Startupreneur Business Digital (SABDA Journal) BEAM
Diego Abbas
iLearning Incorporation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education

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Design Thinking as a Business Model for Empowering Creative Entrepreneurs in the Digital Era Diego Abbas; Kelvin Siahaan; Muhamad Yusup
Startupreneur Business Digital (SABDA Journal) Vol. 4 No. 2 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v4i2.805

Abstract

In the rapidly evolving digital economy, creativepreneurs individuals who transform artistic and creative ideas into marketable ventures face unique challenges in sustaining innovation, meeting user needs, and creating scalable value. Traditional business models often fall short in supporting the fluid, iterative, and user centric nature of creative industries. This study explores the integration of design thinking as a strategic business model to empower creativepreneurs in the digital era. The research aims to investigate how the principles of empathy, ideation, prototyping, and testing within design thinking can foster innovation, user engagement, and business growth among creative driven entrepreneurs. A qualitative research methodology was adopted, employing in-depth interviews and case studies involving 25 selected creativepreneurs from various digital based industries, such as digital art, fashion, content creation, and digital product design. Data were analyzed using thematic analysis to identify common patterns and insights. The findings indicate that the application of design thinking significantly enhances creativepreneurs ability to identify user pain points, develop user centered solutions, and adapt quickly to market feedback. Moreover, design thinking promotes continuous innovation and resilience, two critical traits for success in the digital landscape. In conclusion, design thinking is not only a creative problem solving tool but also a robust business model that aligns with the values and needs of modern creativepreneurs. The study recommends incorporating design thinking frameworks into entrepreneurship education and incubator programs to support creative economy growth in the digital age.
Integrating Broadcasting Data Mining and Visualizationfor Effective Big Data Decision Support Diego Abbas; Arthur Simanjuntak; Thomas Sumarsan Goh
Bridging of Emerging AI and Media Broadcasting (BEAM) Vol. 1 No. 2 May (2026): Bridging of Emerging AI and Media Broadcasting
Publisher : Sundara Publishing

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Abstract

In the era of big data and digital broadcasting, organizations face increasing challenges in transforming large-scale broadcasting datasets into actionable insights for effective decision-making. This study addresses the need for an integrated decision support framework that combines broadcasting data mining and interactive visualization to improve the interpretation of complex data patterns. The objective of this research is to develop an integrated approach that applies data mining techniques to broadcasting-related data, such as audience behavior, content performance, engagement patterns, and multi-source media data, supported by visual dashboards for strategic analysis. The method employed includes clustering, classification, and association rule mining to identify meaningful patterns, audience segments, trends, and anomalies within broadcasting datasets. These analytical results are then presented through interactive visualization dashboards that enable stakeholders to explore insights more efficiently and make data-driven decisions. The results show that integrating broadcasting data mining with visualization improves the speed, accuracy, and clarity of insight extraction compared to conventional analytics approaches. User evaluation also indicates that visualized analytical outputs enhance stakeholder understanding of complex broadcasting data and support more accurate strategic decisions. The conclusion of this study confirms that the integration of broadcast- ing data mining and visualization within a big data decision support framework can bridge the gap between raw media data and practical decision-making. This research contributes to the development of more adaptive, efficient, and human centered decision support systems for broadcasting industries and digital media organizations.
Co-Authors Arthur Simanjuntak Kelvin Siahaan Muhamad Yusup Thomas Sumarsan Goh