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All Journal Startupreneur Business Digital (SABDA Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi BEAM AI, Innovation, and Resilience for the Environment Journal
Elda Diah Safitri
State University of Jakarta
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Other

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SWOT Analysis is Used in the Startup Business Development Strategy Elda Diah Safitri; Sausan Raihana Putri Junaedi; Ari Priono
Startupreneur Business Digital (SABDA Journal) Vol. 2 No. 2 (2023)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v2i2.341

Abstract

Fast-growing startups in Indonesia have an effect on the economy of the country. The fact that Indonesia is one of the five nations with the most startups in the world attests to the high level of public interest. Numerous firms that have strong financial valuations fall under the category of unicorns or even decacorns. One of the funding options in the capital process, which, of course, cannot be isolated from the company's strategies, is to execute an Initial Public Offering (IPO) on the Indonesia Stock Exchange (IDX). Up till 2022, two startups, PT. Bukalapak.com (BUKA) and PT. Goto Gojek Tokopedia (GOTO), have held initial public offerings. Analyze the two companies' strengths, weaknesses, opportunities, and threats (SWOT) in order to determine their respective business strategies. This study used a descriptive qualitative method, and it collected its data by completing literature reviews from reliable sources of scholarly literature and online news.
Innovations in Technology and Data Systems to Strengthen Fisheries Management Rifqi Fahrudin; Royani; Asher Nuche; Elda Diah Safitri
Startupreneur Business Digital (SABDA Journal) Vol. 5 No. 1 (2026)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v5i1.1045

Abstract

Fisheries management faces critical pressures from overexploitation, climate change, and illegal, unreported, and unregulated (IUU) fishing. Conventional monitoring systems often rely on fragmented and delayed data, which significantly limit effective decision-making. This study examine how emerging digital technologies and advanced data systems enhance governance, transparency, and sustainability in the sector. A mixed-method approach was employed, combining a systematic literature review and a comparative case assessment of technology adoption. The results demonstrate that integrating Electronic Monitoring (EM) and Vessel Monitoring Systems (VMS) can expand monitoring coverage by up to 100% in industrial fleets compared to human observers, while reducing long-term operational costs. Digital reporting platforms (e-logbooks) were found to significantly reduce data transcription errors and shorten the feedback loop between data collection and regulatory action. Furthermore, Artificial Intelligence (AI)-assisted species identification improves the speed of processing catch data from EM footage. However, successful implementation depends on institutional readiness, regulatory alignment, and ensuring equitable digital access for small-scale fishers. This research concludes that while technology holds transformative potential, long-term effectiveness requires integrated governance frameworks and collaborative implementation strategies.
Beyond Digitization Blockchain Data Governance for Trustworthy Academic Ecosystems Hanny Safitri; Elda Diah Safitri
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 5 No 1 (2026): September
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v5i1.1129

Abstract

The study involved a total of 217 respondents. consisting of key stakeholders in higher education, including undergraduate and postgraduate students, academic staff, and administrative personnel. The respondents were selected using a purposive sampling technique to ensure they had relevant experience and understanding of academic data management systems. Among the participants, the majority were students, representing approximately 65%, followed by academic staff at 20%, and administrative personnel at 15%. In terms of gender distribution, 54% were female and 46% were male. Most respondents were aged between 18 and 30 years, reflecting a digitally active population familiar with emerging technologies. Additionally, a significant proportion of respondents reported prior exposure to digital academic systems, while a smaller percentage demonstrated awareness of blockchain technology applications in education. This distribution ensures that the collected data reflects diverse perspectives within the academic ecosystem and supports the reliability of the analysis conducted using Structural Equation Modeling-Partial Least Squares (SEM-PLS).
A Framework for Data-Informed Content Creation Elda Diah Safitri; Fitra Putri Oganda; Carlos Perez
AI, Innovation, and Resilience for the Environment (AIR) Vol. 1 No. 1 (2026): AI, Innovation, and Resilience for the Environment Journal (AIR)
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/air.v1i1.128

Abstract

The rapid growth of digital platforms has transformed content creation into a data-rich activity where audience interactions generate valuable insights. De- spite the availability of large volumes of data, many content creators still rely heavily on intuition and use analytics only for superficial performance monitor- ing. This study addresses the gap between data availability and its practical inte- gration into the content creation process by proposing a structured framework for data-informed content creation. The research reviews existing literature on dig- ital marketing, content strategy, and data analytics to identify key stages where data can effectively guide creative decision-making. The proposed framework integrates audience analysis, data-driven content planning, content production, and performance evaluation into a continuous cycle of improvement. By com- bining analytical insights with creative processes, the framework helps organi- zations develop more relevant, engaging, and strategically aligned content. The findings highlight that a data-informed approach not only improves engagement and efficiency but also supports better collaboration between creative and analyt- ical teams. Ultimately, this study contributes both theoretically and practically by providing a systematic model that enables marketers and content creators to leverage data more effectively throughout the entire content lifecycle.
QoE Aware Semantic Computing and Edge Intelligence forAdaptive XR Broadcasting over 6G Networks Elda Diah Safitri; Muhtarom Muhtarom; Aulia Wellington
Bridging of Emerging AI and Media Broadcasting (BEAM) Vol. 2 No. 1 November (2026): Bridging of Emerging AI and Media Broadcasting
Publisher : Sundara Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/beam.v2i1.267

Abstract

The rapid evolution of Extended Reality (XR) broadcasting over sixth-generation (6G) networks introduces significant challenges related to ultra-low latency, heterogeneous traffic, intensive computation, and dynamic Quality of Experience (QoE) requirements. As a Background, conventional resource allocation and edge computing approaches often process immersive content uniformly, resulting in inefficient bandwidth and computational utilization while failing to prioritize semantically important XR information. The Object of this study is to develop a QoE-aware semantic computing and edge intelligence framework that enables adaptive XR broadcasting by prioritizing perceptually and contextually important content according to network conditions and user experience requirements. The Method integrates semantic feature extraction, intelligent edge processing, QoE-aware resource allocation, and adaptive transmission within a simulated 6G edge network environment. The proposed framework is evaluated under different traffic loads and network conditions using end-to-end latency, bandwidth consumption, computational efficiency, QoE score, and transmission reliability as the primary performance indicators and is compared with a conventional resource allocation approach. The Result demonstrates that the proposed approach reduces transmission latency and unnecessary bandwidth consumption while maintaining higher QoE stability, particularly under congested and highly dynamic network conditions. Semantic prioritization further enables edge resources to focus on XR components with greater perceptual importance without significantly degrading overall immersive quality. The Conclusion confirms that combining semantic computing with edge intelligence provides an effective mechanism for adaptive XR broadcasting and offers a scalable foundation for delivering responsive, resource-efficient, and QoE-oriented immersive media services over future 6G networks.
Co-Authors Ari Priono Asher Nuche Aulia Wellington Carlos Perez Fitra Putri Oganda Hanny Safitri Muhtarom Rifqi Fahrudin Royani Sausan Raihana Putri Junaedi