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Empirical Legal Research Methods: Applications in Legal Research in Indonesia Widyani, Retno; Wei, Li; Jun, Wang
Rechtsnormen: Journal of Law Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/rjl.v3i2.2095

Abstract

Background: Empirical legal research methods have gained increasing significance in legal scholarship, offering insights into the real-world application and outcomes of laws. In Indonesia, the use of these methods remains relatively underexplored despite the growing need for evidence-based policy and legal reforms. Legal research in Indonesia has traditionally relied on doctrinal methods, but empirical approaches have the potential to enhance the understanding of how legal systems function in practice and how laws impact society. Objective: This study aims to explore the applications of empirical legal research methods in legal research in Indonesia. The research focuses on examining how these methods can be effectively implemented in the context of Indonesian legal research to address pressing legal issues and improve the legal system's overall effectiveness. Method: A qualitative research design was employed, combining a review of existing literature, case studies, and interviews with legal scholars, practitioners, and policymakers. The study also analyzed existing empirical research on legal issues in Indonesia to identify current trends and gaps in research. Results: The findings suggest that empirical methods, such as surveys, interviews, and case studies, are increasingly being adopted in Indonesian legal research, though challenges remain in terms of resources, training, and institutional support. Conclusion: Empirical legal research holds significant potential for advancing legal scholarship in Indonesia. There is a need for greater integration of these methods to enhance the quality and relevance of legal research and inform legal reforms.
Evaluation of the Effectiveness of Welfare Programs in Academic Environments: Quantitative Study and Data Analysis Musmulyadin, Musmulyadin; Jun, Wang; Mei, Chen
Research Psychologie, Orientation et Conseil Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/rpoc.v2i1.1857

Abstract

The effectiveness of welfare programs in academic environments plays a crucial role in enhancing faculty performance, student satisfaction, and overall institutional development. Despite their significance, limited studies comprehensively analyze the impact of such programs using robust quantitative methods. This study aims to evaluate the effectiveness of welfare programs implemented in academic settings, focusing on their influence on academic stakeholders' well-being and productivity. A quantitative approach was employed, involving a structured survey distributed to 500 faculty members and administrative staff from 10 universities across different regions. Data analysis was conducted using descriptive statistics, regression modeling, and structural equation modeling to identify key factors contributing to program success. The findings revealed that well-structured welfare programs significantly improve job satisfaction, reduce burnout, and enhance institutional loyalty. Factors such as accessibility, inclusivity, and alignment with stakeholders' needs emerged as critical determinants of program effectiveness. Programs promoting work-life balance and professional development showed the highest impact on participants' well-being and performance. In conclusion, this study underscores the necessity for tailored welfare programs that address the specific needs of academic environments. Future research should explore longitudinal impacts and incorporate diverse cultural contexts to broaden understanding.
FOREST-BASED INDUSTRIES AND RURAL DEVELOPMENT IN SOUTHEAST ASIA Wei, Li; Li, Zhang; Jun, Wang
Journal of Selvicoltura Asean Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v2i2.2033

Abstract

Forest-based industries play a crucial role in the economies of Southeast Asia, particularly in rural development. The region is rich in forest resources, which have long been a source of livelihood for many rural communities. However, there is growing concern about the sustainability of these industries, with deforestation and environmental degradation posing challenges to long-term economic development. Understanding the link between forest-based industries and rural development is vital for promoting sustainable practices that benefit both the economy and the environment. This study aims to explore the relationship between forest-based industries and rural development in Southeast Asia, focusing on the economic, social, and environmental impacts. The research seeks to assess how these industries contribute to rural livelihoods, economic growth, and sustainability while addressing the challenges posed by deforestation and unsustainable practices. A mixed-methods approach was used, combining qualitative interviews with stakeholders, including industry representatives, government officials, and rural communities, with quantitative data on economic indicators from forest-based industries in several Southeast Asian countries. The study also includes a comparative analysis of case studies from Indonesia, Malaysia, and Thailand. The study finds that forest-based industries contribute significantly to rural economic growth, providing employment opportunities and improving infrastructure. However, unsustainable logging practices and weak enforcement of environmental regulations have led to environmental degradation and social inequalities. The research concludes that while forest-based industries have the potential to support rural development, their sustainability depends on the adoption of responsible management practices and stronger governance structures.
THE ECONOMICS OF REDD+ (REDUCING EMISSIONS FROM DEFORESTATION AND FOREST DEGRADATION): A POLICY ANALYSIS OF ITS IMPLEMENTATION IN INDONESIA Judijanto, Loso; Jun, Wang; Mei, Chen
Journal of Selvicoltura Asean Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v2i5.2486

Abstract

Reducing Emissions from Deforestation and Forest Degradation (REDD+) is a pivotal international climate change mitigation mechanism, with Indonesia being a key implementing country due to its vast tropical forests. Despite significant international investment, the economic viability and effectiveness of REDD+ in achieving its goals are contingent upon the design and implementation of national policies. This study aimed to conduct a comprehensive economic policy analysis of REDD+ implementation in Indonesia, evaluating its efficiency, cost-effectiveness, and the equity of its benefit-sharing mechanisms. A policy analysis framework was employed, integrating economic principles with a review of national and sub-national REDD+ policies, regulations, and project implementation documents from 2010 to 2024. The analysis was supplemented by a meta-synthesis of financial reports from REDD+ pilot projects and existing academic literature to assess transaction costs, financial flows, and benefit distribution. The analysis reveals significant economic challenges. High transaction costs, coupled with unclear carbon tenure and property rights, have created substantial inefficiencies and deterred private sector investment. Furthermore, the absence of a consistent national carbon price has undermined the financial incentives for land-use change. Benefit-sharing mechanisms were often found to be ad-hoc, leading to inequitable outcomes that failed to adequately compensate local communities for their opportunity costs. For REDD+ to become an economically viable and effective climate mitigation strategy in Indonesia, significant policy reforms are imperative. Future policies must focus on reducing transaction costs, providing clear and secure carbon tenure, and establishing transparent, equitable, and efficient benefit-sharing mechanisms that reflect the true costs borne by local stakeholders.
Surpassing the Standard Quantum Limit in Force Sensing via Squeezed Light Injection in a Cavity Optomechanical System Jun, Wang; Mei, Chen; Reyes, Maria Clara
Journal of Tecnologia Quantica Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i5.3195

Abstract

The Standard Quantum Limit (SQL) sets a fundamental barrier on the precision of force sensing due to quantum fluctuations. Surpassing this limit is crucial for advancing the sensitivity of force sensors, especially in applications like gravitational wave detection and quantum metrology. This study explores the potential of squeezed light injection into cavity optomechanical systems to surpass the SQL in force sensing. The main objective is to develop a method that enhances the precision of force measurements by leveraging quantum squeezing, thereby reducing quantum noise in one quadrature of the light field. The research employs both theoretical modeling and experimental techniques to study the effects of squeezed light on the force sensitivity of a cavity optomechanical system. The system was tested with varying squeezing levels and optomechanical coupling strengths. Force sensitivity was measured using a heterodyne detection setup, with the results compared to the SQL. The findings demonstrate that force sensitivity can indeed surpass the SQL by utilizing squeezed light, with a significant improvement in precision observed at higher squeezing levels. At 12 dB of squeezing, the system achieved a sensitivity of 3.1 × 10?¹³ N/?Hz, well below the SQL. This research confirms that squeezed light injection, combined with optimized optomechanical coupling, is a viable technique for quantum-enhanced force sensing.  
THE USE OF MULTISPECTRAL DRONE IMAGERY AND ARTIFICIAL INTELLIGENCE FOR THE EARLY DETECTION OF LEAF BLIGHT DISEASE IN INDONESIAN RICE PADDIES Wei, Sun; Jun, Wang; Yang, Liu
Techno Agriculturae Studium of Research Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i5.2961

Abstract

Leaf blight disease remains one of the major threats to rice production in Indonesia, causing significant yield losses and threatening national food security. Conventional detection methods rely heavily on manual field inspection, which is time-consuming, labor-intensive, and often ineffective for early-stage identification. Recent advances in multispectral drone imagery and artificial intelligence (AI) offer new opportunities for precision agriculture by enabling rapid, accurate, and large-scale crop health monitoring. However, the practical application of these technologies in Indonesian rice paddies is still limited and requires empirical validation. This study aims to examine the effectiveness of multispectral drone imagery integrated with AI-based classification models for the early detection of leaf blight disease in Indonesian rice fields. The research focuses on improving detection accuracy and supporting timely disease management decisions for farmers and agricultural stakeholders. The study employs an experimental research design using multispectral drone data collected from rice paddies in West Java during the growing season. Vegetation indices such as NDVI and GNDVI were extracted and analyzed using machine learning algorithms, including Random Forest and Convolutional Neural Networks (CNN). Ground truth data were obtained through field observations and laboratory confirmation to validate the model outputs. The results demonstrate that the AI-based model achieved high classification accuracy, exceeding 90% in detecting early-stage leaf blight symptoms. The integration of multispectral data significantly improved detection performance compared to visual RGB imagery alone. The study concludes that multispectral drone imagery combined with AI provides a reliable and efficient approach for early detection of leaf blight disease in rice paddies. This approach has strong potential to support precision agriculture, reduce crop losses, and enhance sustainable rice production in Indonesia.
Synthesis and Characterization of a Graphene Oxide-Chitosan Nanocomposite for the Adsorption of Heavy Metals From Industrial Wastewater Minho, Kim; Jun, Wang; Koch, Sebastian
Research of Scientia Naturalis Vol. 2 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i6.2923

Abstract

The contamination of industrial wastewater with heavy metals such as lead (Pb), cadmium (Cd), and chromium (Cr) poses a significant environmental threat, requiring effective removal methods. Traditional water treatment techniques often suffer from inefficiency and environmental harm. This study aims to synthesize and characterize a graphene oxide-chitosan nanocomposite for the efficient adsorption of heavy metals from industrial wastewater. Graphene oxide (GO) was combined with chitosan to form the nanocomposite, which was characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) surface area analysis. The adsorption capacity was evaluated through batch experiments using simulated industrial wastewater, and the effects of pH, contact time, and metal concentration on adsorption were examined. The results showed that the nanocomposite demonstrated excellent adsorption efficiency, with the highest removal rate observed for Pb, followed by Cd and Cr. The adsorption capacity was significantly influenced by pH, with optimal performance at pH 5. The nanocomposite exhibited high metal removal efficiency and stability, indicating its potential as an eco-friendly solution for wastewater treatment. This study highlights the potential of graphene oxide-chitosan nanocomposites as effective adsorbents for heavy metal removal, offering a sustainable alternative to traditional treatment methods.
Virtual Tourism as a Social Entrepreneurship Model for the Economic Recovery of Tourism Villages (Desa Wisata) in Bali Wei, Li; Jun, Wang; Na, Li; Suryani, Ni Kadek
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i5.3063

Abstract

Tourism villages (desa wisata) in Bali have long been integral to the island’s economy, providing local communities with income through tourism activities. However, the COVID-19 pandemic severely impacted the tourism industry, prompting a need for innovative solutions to support economic recovery. Virtual tourism has emerged as a promising tool, allowing tourism villages to maintain cultural engagement and reach global audiences despite travel restrictions. This research explores the potential of virtual tourism as a social entrepreneurship model for the economic recovery of desa wisata in Bali. Using a mixed-methods approach, the study examines the effectiveness of virtual tourism initiatives in generating revenue, enhancing market reach, and empowering local communities. The research found that villages with higher levels of digital engagement saw significant increases in online visitors and revenue, with virtual tours and live-streamed events being particularly successful. However, challenges such as digital infrastructure limitations and generational divides in digital literacy were also identified. The study concludes that virtual tourism can serve as a viable and sustainable model for supporting the economic recovery of desa wisata, but requires continuous innovation, training, and community involvement to ensure long-term success.