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Journal of Social Science Utilizing Technology
Published by Yayasan Adra Karima Hubbi
ISSN : 30265959     EISSN : 3026605X     DOI : 10.70177/jssut
Core Subject :
Journal of Social Science Utilizing Technology focused on new research addressing Information, Management, Educational Technology, eLearning, Media Management, Human Resources, Fine and Applied Arts, Humanities Social Sciences, General and CrossDisciplinary and Communications Technologies as Applied to the Digital Worlds of Business, Government and Non-Governmental Enterprises. The Journal publishes work from all disciplinary, theoretical and methodological perspectives. It is designed to be read by researchers, scholars, teachers and advanced students in the fields of Information Systems, Management and Information Science, as well as information technology developers, consultants, software vendors, and senior business and information technology executives seeking an update on current experience and future prospects in relation to contemporary information and communications technologies.
Arjuna Subject : -
Articles 124 Documents
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AI-Powered Governance: Exploring the Role of Artificial Intelligence in Shaping Public Service Innovation Ngr. Putu Raka Novandra Asta; Vinto Rizalfi; Sun Wei
Journal of Social Science Utilizing Technology Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i2.2288

Abstract

Background. The rapid advancement of Artificial Intelligence (AI) has significantly transformed various sectors, including public governance. In the face of increasing demands for efficiency, transparency, and citizen-centric services, governments around the world are turning to AI to reimagine the structure and delivery of public services. Purpose. This research explores how AI technologies are being integrated into public governance systems to drive innovation, enhance administrative performance, and foster participatory governance. The objective of this study is to analyze the extent to which AI-powered tools contribute to the modernization of public service delivery and to identify the challenges and ethical considerations arising from this transformation. Method. This study employs a qualitative research approach using a systematic literature review method. A comprehensive analysis of academic articles, policy reports, and case studies was conducted, focusing on AI applications in public service innovation across multiple countries. Results. The results reveal that AI has played a pivotal role in automating administrative tasks, improving data-driven decision-making, and enabling predictive services. However, the implementation of AI also introduces concerns regarding algorithmic transparency, data privacy, and accountability. Conclusion. The study concludes that while AI holds immense potential to reshape public governance and stimulate service innovation, its success depends on the alignment of technological capabilities with inclusive policy frameworks and ethical standards. Future governance models must prioritize human oversight, regulatory compliance, and equitable access to ensure sustainable innovation.
Blockchain for Social Trust: Rebuilding Transparency in Public Sector Transactions through DLT I Putu Astawa; Rachmat Prasetio; Sofia Lim
Journal of Social Science Utilizing Technology Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i2.2290

Abstract

Background. The erosion of public trust in government institutions has become a critical global concern, driven largely by persistent issues of corruption, inefficiency, and opaque administrative processes. Amid this trust deficit, blockchain technology—especially Distributed Ledger Technology (DLT)—has emerged as a promising tool to rebuild transparency, accountability, and citizen engagement in the public sector. Purpose. This study aims to examine how blockchain can be strategically implemented to restore social trust by enhancing transparency in public sector transactions. Method. This study uses a qualitative method supported by several case studies, this study analyzes the initiative of real world blockchain adoption in countries such as Estonia, the United Arab Emirates, and Indonesia. Data was collected through analysis of policy documents, expert interviews, and comparative evaluation of the DLT -based public administration framework. Results. The findings indicate that blockchain’s immutable and decentralized architecture significantly mitigates information asymmetry, reduces opportunities for fraud, and enables real-time auditing of government activities. Moreover, smart contract integration allows for automatic enforcement of public service agreements, further reinforcing institutional integrity. However, the study also highlights critical challenges such as legal uncertainties, technological literacy gaps, and resistance to institutional change that may hinder effective implementation. Conclusion. In conclusion, while blockchain is not a panacea for all governance issues, it presents a powerful foundation for restoring social trust when embedded within a broader ecosystem of legal reform, digital literacy, and civic participation. This research contributes to the growing discourse on digital governance by offering a conceptual and empirical basis for blockchain-enabled transparency in the public sector.
Digital Social Enterprises: How Technology Empowers Grassroots Economic Movements Hiras Pasaribu; Adam Mudinillah; Krim Ulwi
Journal of Social Science Utilizing Technology Vol. 3 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i3.2291

Abstract

Background. The growing digitalization of global economies has opened new pathways for economic inclusion, particularly at the grassroots level. Traditional economic development models often fail to reach marginalized communities due to structural barriers, limited resources, and top-down intervention frameworks. In response, digital social enterprises (DSEs) have emerged as transformative agents that leverage technology to drive local entrepreneurship, community resilience, and inclusive innovation. These enterprises utilize digital tools such as mobile applications, blockchain, e-commerce, and social media platforms to empower underserved populations and promote sustainable livelihoods. Purpose. This study aims to examine how technology-enabled social enterprises contribute to the empowerment of grassroots economic movements across diverse socio-economic contexts. Method. The research adopts a qualitative multiple case study design, analyzing six DSEs operating in Southeast Asia, Sub-Saharan Africa, and Latin America. Data were collected through in-depth interviews with founders and beneficiaries, field observations, and analysis of digital engagement metrics. Results. Findings indicate that digital social enterprises significantly enhance economic agency at the grassroots by reducing transaction costs, increasing market access, and facilitating peer-to-peer support networks. Furthermore, technology fosters adaptive capacity and local ownership, enabling communities to co-create solutions tailored to their socio-cultural realities. Conclusion. In conclusion, DSEs represent a viable bottom-up model of economic empowerment where technology serves as both a tool and a catalyst for systemic change. The study offers insights for policymakers, educators, and development practitioners seeking to scale inclusive, tech-driven economic solutions that bridge the digital divide and promote social equity.
Digital Epidemiology: Using Social Media Data and Machine Learning to Forecast Influenza Outbreaks and Inform Public Health Responses Benny Novico Zani; Ravi Raj Pandey; Le Thi Lan Anh
Journal of Social Science Utilizing Technology Vol. 3 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i3.2735

Abstract

Background. Traditional influenza surveillance systems inherently suffer from a critical one-to-two-week reporting lag, severely hindering timely public health interventions and resource allocation. Purpose. This research aims to develop and validate a hybrid digital epidemiology model using unstructured social media data and advanced Machine Learning (ML) to provide accurate, long-range influenza outbreak forecasts. Method. The methodology involved quantitative time-series forecasting, training Long Short-Term Memory (LSTM) and XGBoost models on five years of social media data, and benchmarking against official clinical reports. Results. The optimized LSTM model achieved significantly superior accuracy, recording a Root Mean Square Error (RMSE) of 0.145 for the four-week forecasting horizon, less than half the error of the traditional ARIMA baseline. This high predictive power confirms that social media is a statistically reliable, non-clinical leading indicator. Conclusion. The study establishes a transparent policy translation framework, linking predicted incidence rates (e.g., exceeding 0.20) directly to required operational responses (e.g., hospital surge activation). This model offers a robust, actionable template for transforming public health surveillance from a reactive system into a proactive intelligence platform for epidemic preparedness.
Fintech and Financial Inclusion: A Study on the Role of P2P Lending Platforms for Unbanked MSMEs (UMKM) in Indonesia I Putu Astawa; Kabelo Dube; Charles Ndikumana
Journal of Social Science Utilizing Technology Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i4.2831

Abstract

Background. In Indonesia, micro, small, and medium enterprises (MSMEs), which represent a significant portion of the economy, often face challenges in accessing traditional financial services due to limited access to banking and credit facilities. Peer-to-peer (P2P) lending platforms have emerged as a viable alternative to address the financing gap for unbanked MSMEs. Purpose. This study investigates the role of P2P lending platforms in promoting financial inclusion among unbanked MSMEs in Indonesia, focusing on their potential to provide easier access to capital and foster economic growth. Method. The research adopts a mixed-methods approach, combining quantitative surveys and qualitative interviews with MSME owners and financial experts. A total of 200 MSMEs across various sectors were surveyed, and 15 in-depth interviews were conducted to explore the experiences of MSME owners using P2P lending services. Data analysis includes descriptive statistics and thematic analysis to understand the impact of P2P lending on business performance, financial inclusion, and economic empowerment. Results. The findings reveal that P2P lending platforms have significantly improved access to capital for unbanked MSMEs, enabling them to expand their operations and enhance their financial stability. However, challenges such as high-interest rates, limited awareness, and lack of financial literacy remain. Conclusion. The study concludes that P2P lending platforms play a crucial role in enhancing financial inclusion for MSMEs in Indonesia. To maximize their impact, there is a need for more targeted financial literacy programs and policy support to improve the accessibility and sustainability of these platforms for unbanked MSMEs.
The Impact of Artificial Intelligence and Automation on Employment in Indonesia’s Manufacturing Sector: A Sociological Analysis Ngr. Putu Raka Novandra Asta; Azamat Nazarov; Joao Silva
Journal of Social Science Utilizing Technology Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i5.2832

Abstract

Background. The rapid advancement of Artificial Intelligence (AI) and automation has revolutionized various industries globally, including Indonesia’s manufacturing sector. The integration of these technologies has raised concerns about their impact on employment, particularly regarding job displacement and skill requirements. While AI and automation offer opportunities for increased productivity and efficiency, they also pose challenges for workers, especially in a developing economy like Indonesia. Purpose. This study aims to explore the sociological impact of AI and automation on employment in Indonesia’s manufacturing sector, focusing on the potential changes in the labor market, skill gaps, and social implications for workers. Method. The research employs a mixed-methods approach, combining both qualitative and quantitative techniques. Surveys were conducted with workers in the manufacturing industry, and in-depth interviews with industry experts and sociologists were also carried out. Data was analyzed using thematic coding for qualitative data and statistical analysis for quantitative data to examine the relationship between technological advancements and employment trends. Results. The findings indicate that AI and automation are contributing to job displacement, especially for low-skilled workers, while creating new opportunities for highly skilled labor in areas such as robotics maintenance and data analysis. However, there is a significant gap in workers’ ability to adapt to new technologies due to insufficient training and education. Conclusion. The study concludes that there is a need for strategic policies focused on reskilling and upskilling the workforce to mitigate the adverse effects of automation on employment.
Bridging the Digital Divide: A Study on the Challenges of E-Learning Implementation in Rural and Remote Schools in Indonesia I Wayan Rediyasa; Syafiq Amir; Zandra Flowers
Journal of Social Science Utilizing Technology Vol. 3 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i3.2833

Abstract

Background. The digital divide remains a significant challenge in the context of education in Indonesia, especially in rural and remote areas. While urban schools have increasingly adopted e-learning platforms, many rural schools continue to struggle with limited access to digital resources, inadequate infrastructure, and a lack of digital literacy among both students and teachers. Purpose. This study aims to investigate the challenges faced by rural and remote schools in Indonesia in implementing e-learning and to propose potential solutions to bridge the digital divide. Method. The research utilizes a mixed-methods approach, combining surveys, interviews, and field observations. Data were collected from 15 rural schools across different provinces, involving 300 teachers and 500 students. The quantitative data were analyzed using descriptive statistics, while qualitative data were analyzed through thematic coding. The study identifies key challenges, including unreliable internet connectivity, lack of appropriate devices, low levels of digital literacy, and inadequate teacher training. Results. The results highlight that while there is a strong desire to integrate e-learning, the lack of infrastructure and support systems significantly hinders its effectiveness. Despite these challenges, there are instances of innovative solutions, such as community-based internet sharing and local training programs, that have improved the adoption of e-learning in some areas. Conclusion. The study concludes that bridging the digital divide in rural and remote schools in Indonesia requires a comprehensive approach, including infrastructure development, teacher training, and community involvement. Government policies should prioritize equitable access to digital resources to ensure inclusive education for all.
The Impact of Ride-Hailing Platforms on the Livelihoods and Social Welfare of Gig Economy Workers in Indonesia Ratu Agung Bagus Ngurah Putra; Nandar Hlaing; Sevda Kara
Journal of Social Science Utilizing Technology Vol. 3 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i6.2834

Abstract

The rise of ride-hailing platforms has significantly transformed the labor market in Indonesia, especially within the gig economy. As a rapidly growing sector, these platforms offer flexible work opportunities, attracting millions of workers. However, the impact of ride-hailing on the livelihoods and social welfare of gig economy workers remains understudied. This research aims to explore how ride-hailing platforms influence the income stability, social security, and overall well-being of gig workers in Indonesia. A mixed-methods approach was used for this study, combining surveys and in-depth interviews with 300 gig workers from major cities like Jakarta, Surabaya, and Yogyakarta. The survey collected quantitative data on income patterns, job satisfaction, and access to social benefits, while qualitative interviews provided deeper insights into the social and psychological effects of gig work. The findings indicate that while ride-hailing platforms offer a source of income and flexible working hours, they also expose workers to income instability, lack of social protection, and job insecurity. Only 15% of workers reported having access to formal social security benefits, with many relying on informal networks for support. Additionally, mental health concerns were prevalent due to the unpredictable nature of gig work and the absence of a supportive work environment. The study concludes that while ride-hailing platforms offer significant economic opportunities, there is an urgent need for policy reforms that address workers' rights, social security, and job security to ensure the sustainability of their livelihoods and well-being.
The Algorithmic Workforce: A Qualitative Study on the Impact of AI-Driven Management on Labor Autonomy in the Gig Economy Sione Kakala; Luisa Fangatapu; Toka Tupuola
Journal of Social Science Utilizing Technology Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i4.2873

Abstract

Background. The rapid expansion of AI-driven management systems in the gig economy has transformed labor processes, reshaping how autonomy, decision-making, and work conditions are structured. This study addresses the growing concern that algorithmic oversight may simultaneously enhance efficiency while constraining workers’ control over their tasks and mobility. Purpose. The research aims to examine how gig workers interpret, negotiate, and respond to algorithmic management practices embedded in digital labor platforms. Method. Using a qualitative design, the study draws on in-depth interviews and digital ethnography involving ride-hailing and delivery workers across multiple urban regions. Results. The findings reveal a dualistic impact: algorithms streamline workflow coordination and reduce transactional ambiguity, yet they also introduce opaque decision rules, performance scoring pressures, and subtle forms of behavioral nudging that weaken workers’ perceived autonomy. Participants reported adaptive strategies, such as system gaming and collective knowledge sharing, to counterbalance algorithmic constraints. Conclusion. The study concludes that AI-driven management does not uniformly diminish autonomy but reconfigures it through dynamic tensions between control, dependency, and worker agency. These insights underscore the need for regulatory frameworks and platform design principles that ensure transparency, fairness, and human-centered governance in algorithmic workplaces.
Governing By Data: A Critical Analysis of Big Data’s Role in Urban Public Policy and Social Stratification in Southeast Asian Megacities Luca Santi; Martina Rossi; Giuseppe Lazzari
Journal of Social Science Utilizing Technology Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i4.2874

Abstract

Background. The rapid expansion of big data infrastructures in Southeast Asian megacities has reshaped the formulation and implementation of urban public policy, raising concerns about algorithmic governance and emerging forms of social stratification. Urban administrations increasingly rely on predictive analytics, biometric systems, and real-time surveillance tools to guide decision-making, yet the socio-political implications of these technologies remain insufficiently understood. Purpose. This study aims to critically examine how big data systems influence policy priorities, resource allocation, and the lived experiences of marginalized urban communities. Method. . A qualitative research design was employed, combining policy document analysis, expert interviews, and digital ethnography across three major Southeast Asian cities. Results. The findings reveal that big data governance enhances administrative efficiency but simultaneously reinforces structural inequalities through opaque categorization practices, risk scoring models, and selective visibility regimes. These mechanisms privilege affluent districts while amplifying precarity in low-income urban populations. Conclusion. The study concludes that big data functions as both a technocratic tool and a political instrument, producing uneven urban outcomes shaped by existing socio-economic hierarchies. The results underscore the need for transparent data governance frameworks and equity-oriented urban policy reforms.

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