International Journal of Social Research

Sustainability Analysis of Subscription Economy Business Model on Platform Streaming Amidst Fierce Competition

Mar'atus Solikhah — Fri, 27 Mar 2026 00:00:00 +0000

The development of the digital economy has driven the adoption of the subscription economy as a primary revenue source for streaming platforms. This model offers revenue stability through recurring payment mechanisms, but amidst increasingly fierce competition between platforms, the sustainability of the subscription business model faces serious challenges. High churn rates, content homogeneity, and increasing user price sensitivity demand more adaptive and long-term sustainability strategies. This study aims to analyze the factors influencing the sustainability of the subscription business model on streaming platforms amidst intense competition, with a focus on customer retention, perceived value, pricing strategy, content differentiation, and user experience. This study uses a quantitative approach with an explanatory design. Data were collected through an online survey of active users of subscription-based streaming platforms using a purposive sampling technique. Data analysis was performed using the Structural Equation Modeling method using the Partial Least Squares (SEM-PLS) approach. The results show that customer retention is the most dominant factor in maintaining the sustainability of the subscription business model. In addition, perceived value, adaptive pricing strategy, content differentiation, and user experience have a significant influence on reducing churn and increasing customer loyalty, thus supporting the sustainability of streaming platforms.

Terminology, Policy Foundations, Purpose And Position Of Pai In The National Education System

Jajat Darojat, Hafidin Nurhadi, Arif Rohman Hakim — Wed, 25 Feb 2026 00:00:00 +0000

Human beings are pedagogical creatures who have the potential intellect, heart, and body to be educated and educated. It takes an understanding of education to be in accordance with the spirit of humanity and human needs. This article is a discussion of collaborative thinking from various points regarding the terminology, purpose and position of Islamic education. As an Islamic education figure, the author will present the views of Syed Muhammad Naquib Al Attas, Imam Al Ghazali, and other Islamic education experts. The research method in this article is qualitative with a library research approach. A study based on research on documents or texts derived from literature. From the results of the study, various Islamic educational technologies were found, namely Al Tarbiyah, al Tansyi'ah, al Ishlah, al Ta'dib or al Adab, al Tahzib, al Tazkiyyah, al Ta'lim, al Siyasah, al Nash wa al Irsyad, al Mau'idzah, and al Akhlak. This article outlines three terms of education in Islam, namely al Tarbiyah, Ta'lim and Ta'dib. Of the three terminologies, according to Naquib Al Attas, for education in Islam, it is more appropriate to use the term Ta'dib. This term is more humanistic and relevant to the subject of education, namely humans. Because basically education is for moral purposes. Even if it refers to the purpose for which man was created, which is to become a servant (abdullah) and a representative of God on earth (khalifatullah). Thus, according to Imam Al Ghazali, the purpose of education is divided into two, namely the special goal as the achievement of happiness in the hereafter (ukhrawi), and the general goal is the substance of human beings as noble beings on earth (worldly), therefore it must achieve benefits in human life in the world. The conclusion is that Islamic education is a means for students to form morals and piety in the context of happiness in this world and the hereafter. As part of National education, Islamic Religious Education is the most important part because of its role in filling the spiritual void of students, this is affirmed in Pancasila and the Indonesian State Law.

Framing Crisis and the Politics of Emotion: How Indonesian Online Media Manage Public Panic in Disaster Reporting

Ahmad Syarofi, Barokatus Sholihah — Sat, 28 Mar 2026 00:00:00 +0000

Disasters and crises are communication events that not only require the delivery of information but also the management of public emotions. In the context of digital media, news framing plays a crucial role in shaping both public perception and emotional responses to crisis situations. This study aims to analyze how Indonesian online media frame the flash flood crisis in Sumatra and how such framing functions in producing and managing public panic. This research employs a qualitative approach within a critical interpretative paradigm. The object of the study is news coverage of flash floods in Sumatra published by Kompas.com, CNNIndonesia.com, and Detik.com during the period of November 25 to December 31, 2025. Data were analyzed using Entman’s framing analysis model, with a focus on narratives of fear, risk emphasis, and the emotional solutions offered by the media. The findings reveal that online media not only define crises through the emphasis on threats, risks, and urgency, but also actively produce public emotions through dramatic diction, disaster metaphors, and threat visualizations. However, crisis framing also functions as a mechanism for panic management through strategies of normalization, rationalization, and emphasis on the role of authorities and symbolic solutions. These findings indicate that public panic is a media-mediated phenomenon, rather than merely a spontaneous response to disaster events. Theoretically, this study expands the concept of framing by integrating the dimension of the politics of emotion, positioning framing not only as a tool for constructing meaning but also as an instrument for managing public emotions in crisis communication. Practically, this study highlights the importance of strengthening crisis journalism ethics and developing media policies that are more sensitive to the emotional impact of disaster reporting within Indonesia’s digital media ecosystem.

A Business Intelligence-Based Data Governance Model to Reduce the Risk of AI Implementation Failure in Organizations

Ghina Fauziyyah, Mar'atus Solikhah — Sat, 28 Mar 2026 00:00:00 +0000

The implementation of Artificial Intelligence (AI) in organizations is increasing along with the development of digital transformation and the need for data-driven decision-making. However, various studies show that many AI projects fail due to poor data quality, lack of data integration, and weak data governance within the organization. In this context, Business Intelligence (BI) has the potential to support systematic data management through data integration, analytics, and information visualization. Therefore, a data governance model integrated with Business Intelligence is needed to improve the quality of data management and reduce the risk of AI implementation failure. This study aims to develop a Business Intelligence-based Data Governance model that can reduce the risk of Artificial Intelligence implementation failure in organizations and increase the effectiveness of data-driven decision-making. This study uses a quantitative approach with an explanatory research method. Research data were obtained by distributing questionnaires to respondents involved in data management and the implementation of organizational analytical systems. Data analysis was conducted using the Structural Equation Modeling (SEM) method with the Partial Least Squares (PLS) approach to examine the relationship between data governance variables, Business Intelligence capability, and AI implementation risk. The results of this study indicate that data governance significantly impacts Business Intelligence capabilities, which in turn contributes to reducing the risk of AI implementation failure within organizations. Furthermore, data quality is shown to be a crucial mediating factor linking data governance to successful AI implementation. This study produces a Business Intelligence-based Data Governance conceptual model that can be used as a framework for organizational data management to support more effective AI implementation.