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Dedi Purwanto Indra Kusuma
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Journal of Community Action
Published by Lembaga Penelitian dan Pendidikan (LPP) Kalibra
ISSN : -     EISSN : 31102549     DOI : https://doi.org/10.70716/joca
Core Subject : Economy, Humanities, Health, Education, Social, Engineering,
Humanities Economics, Econometrics & Finance Education Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences
Journal of Community Action (JOCA) is a journal that is a scientific forum for community service, published by Lembaga Penelitian dan Pendidikan (LPP) Kalibra with the online registered number of e-ISSN 3110-2549. This multidisciplinary scientific journal in the field of community service with the aim of publishing the results of community service activities related to the development and application of science and technology research results, which include concepts, models and its implementation as an effort to increase community participation in development. JOCA is a scientific publication in the field of community service and empowerment with coverage of areas: Human development and nation competitiveness, local resource-based poverty alleviation, management of rural and coastal areas of local wisdom, economic development, entrepreneurship, cooperatives, creative industries, education, animal husbandry, fisheries, marine, public health, UMKM, development of environmentally sound technologies, health, nutrition, tropical diseases, herbal medicines, art, literature, and culture.
Arjuna Subject : Umum - Umum
Articles 25 Documents
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Determinants of Digital Market Expansion Among Fisheries-Based Small Enterprises Muhammad Arifin; Hamdan Zaenuri
Journal of Community Action Vol. 2 No. 3 (2026): Journal of Community Action, July 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/joca.v2i3.360

Abstract

This study examines the determinants of digital market expansion among fisheries-based small enterprises. It focuses on how technological, organizational, socio-economic, and policy-related factors influence market access, competitiveness, and business sustainability in the digital economy. The research employs a systematic literature review of 30 peer-reviewed articles and indexed repositories covering fisheries MSMEs, digital transformation, and e-commerce adoption. The findings indicate that technological factors such as e-commerce platforms, social media utilization, search engine optimization, and digital advertising significantly enhance market visibility and consumer engagement. Organizational factors, including branding, packaging innovation, managerial capability, and financial literacy, strengthen firms’ ability to implement digital strategies effectively. Socio-economic conditions, particularly digital literacy, education level, and income status, determine the degree of technology adoption among fisheries-based enterprises. Policy-related factors, including government subsidies, training programs, institutional support, and infrastructure availability, play a critical role in enabling digital inclusion and reducing adoption barriers. The study concludes that digital market expansion is a multi-dimensional process that requires an integrated ecosystem approach. Technology adoption alone is insufficient without supporting organizational capacity, socio-economic empowerment, and institutional backing. Strengthening these interconnected determinants is essential to enhance competitiveness and ensure sustainable market growth for fisheries-based small enterprises.
Machine Learning-Based Assessment of Climate-Induced Changes in Coastal Fisheries Productivity in Tropical Archipelagic Regions Ahmad Baihaki; Syarifah Jauzi; Ramdanul Hakim
Journal of Community Action Vol. 2 No. 3 (2026): Journal of Community Action, July 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/joca.v2i3.361

Abstract

Coastal fisheries in tropical archipelagic regions are increasingly affected by climate-induced environmental changes that alter fish distribution and productivity. This study develops a machine learning-based framework to assess the impact of climate variability on fisheries productivity using multiple environmental predictors, including sea surface temperature, chlorophyll-a concentration, dissolved oxygen, and climate oscillation indices. Several machine learning algorithms were evaluated, including Random Forest, SVR, ANN, XGBoost, and LightGBM. Model performance was assessed using R², RMSE, and MAE, while SHapley Additive exPlanations (SHAP) were applied to identify key environmental drivers. Results show that LightGBM achieved the highest predictive accuracy (R² = 0.92), outperforming other models in capturing nonlinear relationships between environmental variables and fisheries productivity. Sea surface temperature emerged as the most influential predictor, followed by chlorophyll-a concentration and dissolved oxygen. Scenario analysis indicates that continued ocean warming may reduce fisheries productivity by 10–25% in vulnerable coastal zones. The study highlights strong nonlinear interactions between climate variables and fisheries dynamics, emphasizing the importance of integrating machine learning into ecosystem-based fisheries management. The proposed framework provides a robust tool for predicting climate-induced changes in fisheries productivity and supporting adaptive management strategies in tropical marine ecosystems.
Sustainable Fisheries and Community Nutrition Improvement Rafi Ahmad; Nadia El-Masry
Journal of Community Action Vol. 2 No. 3 (2026): Journal of Community Action, July 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/joca.v2i3.363

Abstract

This study examines the relationship between sustainable fisheries and community nutrition improvement using a systematic literature review approach. The analysis integrates findings from peer-reviewed studies, policy reports, and empirical research on fisheries management, marine ecosystems, and nutritional outcomes. A total of 19 selected references were analyzed using thematic synthesis across ecological, socioeconomic, and nutritional dimensions. Results show that sustainable fisheries management, particularly through marine protected areas, can increase fish biomass by up to 15 percent and fish catch by up to 20 percent. These ecological improvements directly enhance food availability in coastal communities. Fisheries also contribute to poverty reduction by providing stable livelihoods and income sources, which improve household food security. In addition, fish consumption significantly enhances dietary diversity and micronutrient intake, especially in vulnerable populations. However, challenges remain in distribution systems, where export-oriented supply chains limit local access to nutritious fish. Community-based innovations such as small-scale aquaculture and fish processing technologies improve food access and reduce post-harvest losses. The study concludes that sustainable fisheries function as an integrated system linking ecosystem health, economic stability, and human nutrition. Policy integration between fisheries management and public health is essential to maximize nutritional benefits and ensure equitable food access in coastal regions.
Integrating Oceanographic Variability and Small-Scale Fishers’ Local Ecological Knowledge for Sustainable Fishing Ground Management in Eastern Indonesian Waters Rizal Aidil; Aisyah Najwa
Journal of Community Action Vol. 2 No. 3 (2026): Journal of Community Action, July 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/joca.v2i3.364

Abstract

This study analyzes the integration of oceanographic variability and small-scale fishers’ local ecological knowledge (LEK) for sustainable fishing ground management in Eastern Indonesian waters. The region is characterized by strong seasonal dynamics driven by monsoonal systems, sea surface temperature fluctuations, and productivity shifts that influence fish distribution patterns. These environmental conditions create highly dynamic fishing grounds that are difficult to predict using conventional scientific models alone. A systematic synthesis of interdisciplinary literature was conducted, focusing on fisheries oceanography, LEK, and adaptive management frameworks. The analysis shows that oceanographic variables such as chlorophyll-a concentration, sea surface temperature, and ocean currents strongly determine the spatial distribution of pelagic fish stocks. However, fishers’ LEK provides complementary fine-scale information based on long-term ecological observation, including environmental cues such as water color, wind patterns, bird activity, and lunar cycles. Oceanographic data provides macro-scale predictive capacity, while LEK offers micro-scale contextual accuracy. Their integration improves fishing ground identification, enhances decision-making, and reduces uncertainty in data-limited fisheries. The study concludes that hybrid knowledge systems are essential for strengthening sustainable fisheries governance in Eastern Indonesia. Integrating scientific oceanographic analysis with LEK supports adaptive management, improves ecological resilience, and enhances livelihood sustainability in small-scale fisheries.
Factors Influencing Productivity of Smallholder Goat Farming in Rural Areas Ahmad Zaki; Rozali Yahya; Minahasa Baubae
Journal of Community Action Vol. 2 No. 3 (2026): Journal of Community Action, July 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/joca.v2i3.365

Abstract

Smallholder goat farming plays an important role in supporting rural livelihoods, improving household income, and strengthening food security in developing countries. However, the productivity of smallholder goat production systems remains relatively low due to various socioeconomic, technical, institutional, and technological constraints. This study aimed to analyze the factors influencing the productivity of smallholder goat farming in rural areas and to identify the most significant determinants affecting production performance. A quantitative survey approach was employed using primary data collected from 180 smallholder goat farmers through structured interviews. The study examined several explanatory variables, including farmers’ education level, farming experience, herd size, feeding management, animal health management, market access, institutional participation, and technology adoption. Data were analyzed using descriptive statistics and multiple linear regression analysis. The results revealed that all investigated variables had positive and significant effects on goat farming productivity. Feeding management emerged as the most influential factor, followed by herd size and technology adoption. Farmers who applied improved feeding practices, implemented effective animal health management, and utilized modern technologies achieved higher productivity levels than those relying on traditional production systems.

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