p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Multifinance Toplama
Claim Missing Document
Check
Articles

Found 2 Documents
Search

DESIGNING 360-DEGREE VIDEO-BASED JOURNALISTIC CONTENT: AN ANALYSIS OF NEEDS AND CHALLENGES Reza Saeful Rachman; Daniel Paulus Evert; Nina Lestari; Tanto Trisno Mulyono
TOPLAMA Vol. 3 No. 3 (2026): TOPLAMA
Publisher : PT Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/tla.v3i3.542

Abstract

Digital transformation is driving mass media to adopt more interactive news formats, one of which is immersive journalism based on 360° video. This study aims to analyze the needs and challenges of developing 360° journalistic content by linking three theoretical foundationsaffordance, presence, and journalistic ethics to formulate an effective design approach. The method used is the 4D R&D model (Define, Design, Develop, Disseminate) with a mixed approach: a questionnaire to map public interest and perception, a literature review to map the latest technical ethical findings, and in-depth interviews with journalists to understand industry needs, production constraints, and technology adoption strategies. The results show a growing demand for 360° content; journalists consider this format to open up opportunities for richer and more empathetic storytelling, while 85% of audience respondents expressed interest in trying/watching 360° content due to the more immersive experience and navigation control. However, significant barriers include device and training costs, post-production complexity, reliance on network infrastructure, adoption challenges for older users (approximately 30% report dizziness/difficulty wearing VR headsets), and ethical risks associated with potential emotional manipulation. This study proposes a 360° prototype design framework that integrates affordance (free navigation, rotation, and visual focus), presence enhancement for cognitive empathy, and ethical guidelines (transparency of source, context, and privacy). Practical implications include the need for technical training, funding support, and cross-platform dissemination strategies for more inclusive adoption.
AI IN PREDICTIVE BUSINESS ANALYTICS: EVIDENCE AND IMPLICATIONS FOR PRIVATE HIGHER EDUCATION IN THAILAND Chanidapha Nunualvuttiwong; Nurhaeni Sikki; Yuyun Yuniarsih; Adi Permana Sidik; Reza Saeful Rachman
Multifinance Vol. 4 No. 1 (2026): Multifinance
Publisher : PT. Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/mfc.v4i1.573

Abstract

Digital transformation has driven higher education institutions to adopt data-driven approaches to support strategic decision-making, performance measurement, and improvements in the quality of academic services. This study aims to synthesize developments in data-driven business analysis in higher education, focusing on the use of Key Performance Indicators (KPIs), the Balanced Scorecard (BSC), learning analytics, artificial intelligence (AI), internationalization, and data governance, particularly at private universities in Thailand and the ASEAN region. The study employed a narrative scoping review of relevant academic literature, drawing on sources from various databases and scholarly publications in the fields of management, education, and analytics. The synthesis results reveal five main themes: aligning KPIs with institutional strategies; utilizing learning analytics to enhance student success; the dynamics of internationalization and competition in the higher education market; the need to strengthen data governance and ethics; and the use of AI to support business analysis and decision-making. Integrating the BSC with learning analytics enables universities to link strategic objectives with operational indicators more systematically. However, the effectiveness of this approach depends on data quality, analytical capacity, data-driven leadership, digital infrastructure, and responsible AI governance. This study underscores the importance of an integrated, data-driven decision-making ecosystem to enhance the effectiveness, competitiveness, accountability, and sustainability of higher education institutions.