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All Journal Smart Society: Community Service and Empowerment Journal Mandalika Journal of Business and Management Studies Journal of Supply Chain and Entrepreneurship Lentera Negeri
Raden Roro Lia Chairina
Politeknik Negeri Jember, Indonesia
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Community-Based Circular Agribusiness: Market Validation, Pricing Logic, and Value-Chain Coordination for Village Livestock Waste Fertilizer in Rural Indonesia Dhanang Eka Putra; Hariyono Rakhmad; Huda Ahmad Hudori; Raden Roro Lia Chairina; Mochamad Rizal Umami
Smart Society Vol. 5 No. 2 (2025): Smart Society
Publisher : FOUNDAE (Foundation of Advanced Education)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/smartsociety.v5i2.815

Abstract

Village livestock waste presents both an environmental burden and an underutilized resource capable of strengthening rural livelihoods when transformed into marketable organic fertilizer. This study develops a community-based circular agribusiness model that integrates market validation, pricing analysis, and value-chain coordination to improve the commercial feasibility of waste-to-fertilizer initiatives in rural Indonesia. A convergent mixed-methods design was implemented, combining a Price Sensitivity Meter survey with Cost–Volume–Profit and Break-Even Point calculations, supported by a simplified Value Chain Analysis involving farmers, processors, kiosks, and local cooperative actors. Data were collected from 60 small-scale livestock households, 150 fertilizer users, and 12–15 key informants across Arjasa District. Findings indicate an acceptable price range of IDR 40,000–80,000 per 25-kg bag, with an optimal price point near IDR 60,000. At this level, contribution margins remain positive across direct, cooperative, and kiosk channels, with the break-even requirement estimated at 180–230 bags per month. The value-chain assessment reveals constraints related to moisture variability, inconsistent granulometry, and high last-mile distribution costs. Proposed coordination measures include minimum quality standards, scheduled collection and delivery routes, and simple offtake agreements with a 3–5% quality-based incentive. Together, these elements form a replicable empowerment-oriented model that enhances income stability, reduces waste, and supports community-driven resource governance. The study demonstrates that circular agribusiness, when anchored in market evidence and locally manageable coordination mechanisms, can contribute to socio-economic resilience and strengthen community participation in sustainable rural development
The Impact of Artificial Intelligence Adoption on Human Resource Management Practices Today Fitra Mulya; Raden Roro Lia Chairina; Sulistiyanto Sulistiyanto
Mandalika Journal of Business and Management Studies Vol 4 No 1 (2026): Mandalika Journal of Business and Management Studies
Publisher : Mandalika Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/mjbms.v4i1.455

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology that significantly influences contemporary Human Resource Management (HRM) practices. This study examines the impact of AI adoption on HRM functions, focusing on its opportunities, challenges, ethical implications, and strategic contributions to organizational performance. The research employed a qualitative approach using library research and a narrative literature review. Twenty peer-reviewed publications published between 2021 and 2026 were systematically selected based on predefined inclusion criteria, including relevance to AI-enabled HRM, publication period, academic quality, and full-text availability. The selected literature was analyzed using thematic analysis to identify recurring patterns, major themes, and emerging trends related to AI implementation in HRM. The findings indicate that AI adoption has transformed recruitment and selection, employee training and development, performance management, workforce analytics, and strategic workforce planning by improving efficiency, supporting data-driven decision-making, enabling personalized employee development, and enhancing organizational agility. However, significant challenges remain, including algorithmic bias, privacy concerns, lack of transparency, accountability issues, and employee resistance. Successful AI adoption depends not only on technological capabilities but also on organizational readiness, ethical governance, leadership support, and employee acceptance. Unlike previous reviews that primarily examine individual HR functions or specific AI applications, this study provides an integrated synthesis of technological, organizational, strategic, and ethical dimensions within a unified analytical framework, offering a more comprehensive understanding of AI-driven HRM transformation. The findings highlight the importance of balancing technological innovation with human-centered management practices to ensure sustainable and responsible AI implementation.
Agile leadership in digital transformation: strengthening resilience, performance, and trust in indonesia’s fintech industry Gairah Sinulingga; Reina A. Hadikusumo; Syech Idrus; Raden Roro Lia Chairina; Moch Aminudin Hadi
Lentera Negeri Vol. 7 No. 1 (2026): Lentera Negeri
Publisher : Indonesian Institute For Counseling, Education and Therapy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/992240

Abstract

This study explores the role of agile leadership in fostering resilience, performance, and trust within Indonesia’s fintech industry during its digital transformation. Using a qualitative research approach through a literature review, the study synthesizes findings from existing research to examine how agile leadership supports fintech organizations in adapting to rapid technological advancements and evolving market demands. The findings indicate that agile leadership enhances organizational resilience by promoting flexibility and adaptability, improves performance through iterative decision-making and continuous learning, and strengthens customer trust by encouraging transparency and continuous improvement. Furthermore, agile leadership enables fintech companies to respond effectively to external disruptions, thereby improving their competitiveness in a dynamic business environment. The study highlights the importance of collaborative, adaptive, and innovative leadership in driving successful digital transformation and provides valuable insights for fintech leaders seeking to sustain organizational performance, resilience, and customer trust in an increasingly competitive industry.
Community-Owned Circular Business Models for Livestock Waste: Participatory Value-Chain Design and Determinants of Adoption Readiness in Rural Indonesia Dhanang Eka Putra; Hariyono Rakhmad; Huda Ahmad Hudori; Raden Roro Lia Chairina
Journal of Supply Chain and Entrepreneurship Vol. 2 No. 2 (2026): Journal of Supply Chain and Entrepreneurship
Publisher : CV. SPDFHarmony

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64268/josce.v2i2.114

Abstract

Background: Livestock manure is simultaneously an environmental liability and a locally available nutrient resource, yet technical conversion into organic fertilizer does not automatically create a viable circular enterprise. Aims: This study examined how participatory value-chain design and a community-owned business model can reduce operational uncertainty and strengthen household readiness to engage in livestock-waste valorization in Arjasa Village, East Java, Indonesia. Methods: A Year-1 participatory mixed-methods case study combined a structured baseline survey of 60 livestock-keeping households, multi-actor discussions, process walkthroughs, value-chain mapping, and Business Model Canvas co-design. An exploratory logistic model assessed associations between adoption readiness and five designable mechanisms: access to an offtake memorandum of understanding, microfinance, perceived relative advantage, governance trust, and short training, with contextual controls. Results: Forty-six percent of households met the operational definition of early adoption or firm participation commitment. Offtake access showed the largest association with readiness (OR = 3.40), followed by microfinance (OR = 2.60), perceived relative advantage (OR = 2.20 per 1 SD), governance trust (OR = 1.90 per 1 SD), and short training (OR = 1.80). The model showed useful exploratory discrimination (AUC = 0.81), while participatory mapping identified feedstock variability, inconsistent processing endpoints, weak quality records, and uncertain market absorption as the main value-chain frictions. Conclusion: The findings support a risk-reduction architecture in which market assurance, light finance, credible governance, clear product value, and compact learning mechanisms are designed together rather than treated as separate interventions. Because the sample is small and cross-sectional, the regression estimates are interpreted as preliminary associations that require confirmation in subsequent implementation cycles.
Economic Order Quantity for Raw Material Inventory Optimization in a Small-Scale Milkfish Floss Agroindustry: A Case Study in Indonesia Zarin Taj; Raden Roro Lia Chairina
Journal of Supply Chain and Entrepreneurship Vol. 2 No. 1 (2026): Journal of Supply Chain and Entrepreneurship
Publisher : CV. SPDFHarmony

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64268/josce.v2i1.112

Abstract

Background: Efficient raw material inventory management is a critical challenge for small-scale agroindustries, particularly those with limited managerial resources and fluctuating production demand. Many micro and small enterprises rely on traditional purchasing practices that often lead to overstocking, stockouts, and unnecessary holding costs. In agro-based processing industries such as milkfish floss production, ineffective inventory control can reduce operational efficiency and weaken business sustainability. The Economic Order Quantity (EOQ) model offers a systematic approach to determine optimal order quantities that minimize total inventory costs while ensuring the availability of production inputs. However, empirical applications of EOQ in small-scale agroindustry contexts remain limited. Aims: This study aims to analyze the efficiency of raw material inventory management and determine the optimal order quantity using the EOQ model in a small-scale milkfish floss agroindustry in Indonesia. Methods: This research employed a quantitative case study approach. Data were collected through direct observation, production records, and interviews with the enterprise owner. Inventory-related data, including annual demand, ordering cost, and holding cost, were analyzed using the EOQ model to determine optimal order quantity, ordering frequency, and total inventory cost. Result: The findings indicate that the existing inventory practice is less efficient compared with the EOQ-based calculation. By applying the EOQ model, the enterprise can determine a more optimal ordering quantity and reduce total inventory costs. The analysis also reveals improvements in ordering frequency and better control of raw material availability for production continuity. Conclusion: This study demonstrates that the application of the EOQ model can significantly improve raw material inventory efficiency in small-scale agroindustries. The results highlight that systematic inventory planning not only reduces operational costs but also enhances production stability and supply chain reliability. For micro and small enterprises in agro-processing sectors, adopting analytical inventory management tools such as EOQ can serve as a practical strategy to strengthen business competitiveness. Furthermore, the findings emphasize the importance of integrating basic operations management techniques into small-scale entrepreneurial practices to support sustainable agroindustrial development. Implementing structured inventory management frameworks can help small enterprises transition from intuitive decision-making toward data-driven operational strategies, ultimately contributing to improved efficiency, resilience, and long-term business sustainability.
Co-Authors Fitra Mulya Gairah Sinulingga Hariyono Rakhmad Hudori, Huda Ahmad Moch Aminudin Hadi Mochamad Rizal Umami Putra, Dhanang Eka Reina A. Hadikusumo Sulistiyanto Sulistiyanto Syech Idrus Zarin Taj