Garuda - Garba Rujukan Digital

Frugal Innovation in Education: Designing and Evaluating Low-Bandwidth, Asynchronous Learning Systems for Remote Indonesian Schools Hesti Putri; Maya Enderson; Jasmila Tanjung; Matilda Munoz; Sarah Armalia; Jovanka Andina; Kevin Setiawan; Sudarto Sudarto; Khalil Jibran; Jasmine Alieva
Enigma in Education Vol. 3 No. 1 (2025): Enigma in Education
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/edu.v3i1.95

The promise of educational technology (EdTech) to democratize learning in Indonesia is consistently undermined by a profound digital divide, particularly in remote and archipelagic regions where internet connectivity is poor and infrastructure is limited. This study explores the application of frugal innovation principles as a direct and context-aware strategy to address this challenge. A multi-phase, mixed-methods Design-Based Research (DBR) methodology was employed over 18 months. The study involved the collaborative design, development, and implementation of "Lentera," a low-bandwidth, asynchronous, and offline-first learning system, in six remote primary schools in the Maluku Islands. A quasi-experimental design compared three intervention schools with three control schools over one academic year. Data collection was extensive, including pre- and post-intervention literacy and numeracy assessments, System Usability Scale (SUS) surveys, system usage logs, semi-structured interviews with 18 teachers, and over 80 hours of classroom observation. Data were analyzed using a two-level Hierarchical Linear Model (HLM) to account for the clustered nature of students within schools. The Lentera system demonstrated high feasibility and positive user adoption, with offline peer-to-peer sharing proving to be a critical feature for content distribution. Quantitative analysis revealed a statistically significant and substantial improvement in learning outcomes for the intervention group in both literacy (γ = 11.85, p < 0.001) and numeracy (γ = 12.91, p < 0.001) compared to the control group, after controlling for pre-test scores. The mean System Usability Scale (SUS) score was 78.5, indicating well-above-average usability. Qualitative findings, drawn from a wide range of teacher interviews and classroom observations, highlighted the system's effectiveness in supporting student-centered, differentiated instruction and fostering teacher collaboration, aligning with the core principles of Indonesia's Kurikulum Merdeka. The study provides compelling evidence that frugal innovation, embodied in a context-aware learning system, presents a viable, effective, and scalable pathway to enhancing educational quality and equity in resource-constrained environments.

Integrating Kearifan Lokal (Local Wisdom) with Climate Adaptation Strategies: A Participatory Action Research on Enhancing Community Resilience and Achieving SDG 13 in Indonesia's Coastal Communities Jasmila Tanjung; Caelin Damayanti; Neva Dian Permana; Andi Fatihah Syahrir; Hesti Putri; Aman Suparman; Susi Diana
Indonesian Community Empowerment Journal Vol. 5 No. 2 (2025): Indonesian Community Empowerment Journal
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/icejournal.v5i2.45

Coastal communities in Indonesia face existential threats from climate change. Conventional top-down adaptation strategies often fail due to a disconnect from local socio-ecological realities, overlooking a critical resource: traditional ecological knowledge, or kearifan lokal. This study investigates a knowledge co-production model that synergizes kearifan lokal with modern climate science to build community resilience. We employed a 24-month, mixed-methods Participatory Action Research (PAR) design in three highly exposed coastal villages in North Java, Indonesia. Ethical protocols, including Free, Prior, and Informed Consent (FPIC), were foundational. Qualitative data were gathered from in-depth interviews (n=30), focus groups (n=12), and ethnographic observation. Quantitative data came from a pre-test/post-test household survey (n=450) measuring a validated, multi-dimensional Community Resilience Index (CRI). Interventions were co-designed, blending traditional practices like the pranata mangsa (ethno-astronomical calendar) and the wana tirta (mangrove philosophy) with scientific recommendations. A linear mixed-effects model was used to analyze changes in CRI scores. The co-designed strategies led to a statistically significant increase in the mean CRI from a baseline of 2.8 (SD=0.65) to 4.2 (SD=0.48) post-intervention (p<0.001). Significant improvements were observed across all resilience dimensions, most notably in Economic Capital (+59.1%) and Adaptive Capacity & Governance (+51.7%). The revitalization of practices such as the restoration of 50 hectares of mangroves, guided by both wana tirta principles and scientific species selection, enhanced coastal protection and local livelihoods. In conclusion, the co-production of knowledge, facilitated through a PAR framework, is a potent mechanism for building effective, culturally embedded, and sustainable climate resilience. This model empowers communities as active agents in their adaptation journey and offers a scalable, evidence-based pathway for achieving SDG 13 in Indonesia and other climate-vulnerable nations.

Systemic Contagion or Digital Diversifier? A Dynamic Quantification of the Cryptocurrency Market's Evolving Role in Global Financial Risk Transmission Abdul Malik; Gayatri Putri; Hesti Putri; Ahmad Badruddin
Enigma in Economics Vol. 3 No. 2 (2025): Enigma in Economics
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/economy.v3i2.99

The proliferation of crypto-assets has raised critical questions about their impact on global financial stability. This study rigorously investigates the structural evolution of the cryptocurrency market's role within the global financial system, testing the hypothesis that it has transitioned from a peripheral, shock-absorbing entity into a systemically significant transmitter of financial risk. We employ a Time-Varying Parameter Vector Autoregression (TVP-VAR) model on daily data from January 1, 2017, to December 31, 2024, examining the dynamic connectedness between a bespoke, rebalanced cryptocurrency index (CRIX20) and key global financial indicators (S&P 500, MSCI World, VIX, DXY). The econometric framework utilizes a Bayesian estimation approach with standard priors, a 200-day rolling window, and a 10-day forecast horizon for Generalized Forecast Error Variance Decompositions (GFEVD). Methodological robustness is confirmed through structural break tests and sensitivity analysis of the forecast horizon. Our findings reveal a profound structural transformation. Prior to mid-2020, the cryptocurrency market was a consistent net receiver of financial spillovers. A structural break, formally identified in the third quarter of 2020, marks a definitive regime shift. Post-break, the crypto market has become a significant and persistent net transmitter of risk to the traditional financial system. The total connectedness index for the entire system shows a marked secular increase, with the crypto market's contribution to systemic risk growing substantially. Gross spillover analysis confirms this shift is driven by a dramatic increase in risk transmission from the crypto market to other assets. In conclusion, the cryptocurrency market can no longer be considered an isolated ecosystem; it is now an integral and potentially destabilizing component of the global financial architecture. The era of crypto-assets as reliable diversifiers has waned, replaced by a new reality where shocks originating within this market pose a credible threat to broader financial stability. These findings present urgent challenges for regulatory oversight, systemic risk monitoring, and portfolio management.

The Algorithmic Gaze: Deconstructing Authorship and Aesthetics in Generative Artificial Intelligence (AI) Art Hesti Putri; Dais Susilo; Ervin Munandar; Hanifah Yasin; Idris Atmaja
Enigma in Cultural Vol. 3 No. 1 (2025): Enigma in Cultural
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/cultural.v3i1.106

The proliferation of advanced text-to-image generative AI represents a paradigmatic shift in visual culture. It instigates a profound crisis for established concepts of authorship and aesthetics while also raising critical questions about artistic labor and the political economy of cultural production. This study investigates the complex negotiations between human creators and algorithmic systems. This study employed a qualitative, multi-modal methodology. A visual semiotic analysis was conducted on a curated corpus of 300 artworks from Midjourney, DALL-E 3, and Stable Diffusion, sampled to mitigate platform-specific biases. This was triangulated with a thematic analysis of semi-structured interviews with a purposive sample of 15 artists and designers actively using these tools. The methodological limitations, specifically the sample's "adopter-centric" bias, are explicitly acknowledged. The visual analysis identified a distinct "algorithmic gaze" characterized by hyper-compositing, surreal corporeal logic, and stylistic convergence, reflecting both the system's non-human perspective and the biases of its training data. The thematic analysis of artist interviews revealed three dominant experiential themes: the artist's role being reframed as curatorial, the creative process as a form of dialogue, and the interaction as an exploration of the system's "latent space". These participant narratives often frame the interaction in terms of empowerment and collaboration. In conclusion, generative AI reconfigures authorship into a distributed network phenomenon. However, this study argues that this posthuman collaboration occurs within a system structured by significant power asymmetries. The aesthetics of the algorithmic gaze are not neutral but are shaped by the commercial and ideological imperatives of the platforms. The artist's experience of empowerment coexists with broader material processes of deskilling, alienation, and the centralization of cultural production. Understanding this new paradigm requires a critical synthesis of posthumanist theory and political economy.

The Velocity of Relevance: Mapping the Structural Divergence Between Labor Market Signals and University Curricula in Indonesia via Text Mining and Network Analysis Bimala Putri; Delia Tamim; Hesti Putri
Open Access Indonesia Journal of Social Sciences Vol. 8 No. 6 (2025): Open Access Indonesia Journal of Social Sciences
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/oaijss.v8i6.310

The persistent disconnect between higher education outcomes and labor market demands, frequently termed the skills mismatch, remains a critical barrier to Indonesia's economic competitiveness in the Fourth Industrial Revolution. Traditional survey-based methodologies often lack the granularity to capture dynamic market shifts and technical nuances. This study employs a Big Data approach, utilizing automated web scraping to harvest N = 1,042,500 unique job advertisements from major Indonesian portals and N = 4,500 course syllabi from 50 top-tier Indonesian universities between 2023 and 2024. We applied Natural Language Processing, specifically Latent Dirichlet Allocation for topic modeling, and Social Network Analysis to calculate semantic overlap and centrality measures between industry demands and academic provision. We utilized the Overlap Coefficient to correct for corpus size imbalance. The analysis reveals a structural divergence: while 82% of job ads prioritize Digital Fluency and Agile Project Management, only 28% of curricula explicitly integrate these competencies. Network analysis identifies Data Analysis as a peripheral node in academic graphs but a central hub in industry networks with a Betweenness Centrality of 0.45. Conversely, theoretical constructs dominant in academia show weak linkage to employability clusters. In conclusion, the findings evidence a systemic velocity gap where industry requirements evolve three times faster than curriculum adaptation. We propose a dynamic, API-driven curriculum model to mitigate this asymmetry.

The Velocity of Relevance: Mapping the Structural Divergence Between Labor Market Signals and University Curricula in Indonesia via Text Mining and Network Analysis Bimala Putri; Delia Tamim; Hesti Putri
Open Access Indonesia Journal of Social Sciences Vol. 8 No. 6 (2025): Open Access Indonesia Journal of Social Sciences
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/oaijss.v8i6.310

The persistent disconnect between higher education outcomes and labor market demands, frequently termed the skills mismatch, remains a critical barrier to Indonesia's economic competitiveness in the Fourth Industrial Revolution. Traditional survey-based methodologies often lack the granularity to capture dynamic market shifts and technical nuances. This study employs a Big Data approach, utilizing automated web scraping to harvest N = 1,042,500 unique job advertisements from major Indonesian portals and N = 4,500 course syllabi from 50 top-tier Indonesian universities between 2023 and 2024. We applied Natural Language Processing, specifically Latent Dirichlet Allocation for topic modeling, and Social Network Analysis to calculate semantic overlap and centrality measures between industry demands and academic provision. We utilized the Overlap Coefficient to correct for corpus size imbalance. The analysis reveals a structural divergence: while 82% of job ads prioritize Digital Fluency and Agile Project Management, only 28% of curricula explicitly integrate these competencies. Network analysis identifies Data Analysis as a peripheral node in academic graphs but a central hub in industry networks with a Betweenness Centrality of 0.45. Conversely, theoretical constructs dominant in academia show weak linkage to employability clusters. In conclusion, the findings evidence a systemic velocity gap where industry requirements evolve three times faster than curriculum adaptation. We propose a dynamic, API-driven curriculum model to mitigate this asymmetry.

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