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Corporate insolvency regimes have long been designed around efficiency, creditor recovery, and procedural certainty, frequently marginalizing the human, social, and distributive consequences of corporate failure. This qualitative literature review seeks to reconceptualize insolvency as a multidimensional institutional process by integrating the principles of humanity, resilience, and equity, with the objective of developing fairness metrics for more inclusive insolvency systems. Drawing on interdisciplinary scholarship from insolvency law, corporate governance, economic sociology, and normative political theory, this study systematically synthesizes peer reviewed literature published between 2000 and 2024 using a structured qualitative thematic analysis. The review identifies three interrelated dimensions shaping inclusive insolvency outcomes. First, humanity-oriented approaches emphasize stakeholder vulnerability, dignity preservation, and procedural justice, particularly for employees, involuntary creditors, small suppliers, and local communities affected by corporate collapse. Second, resilience based perspectives frame insolvency not merely as an endpoint of failure but as an adaptive governance mechanism that enables organizational recovery, institutional learning, and broader systemic stability. Third, equity focused frameworks highlight the importance of proportional and context sensitive loss allocation, stakeholder participation, and intertemporal fairness in distributing the economic and social costs of insolvency. By integrating these dimensions, the study develops a conceptual framework of fairness metrics that extends beyond traditional efficiency-driven indicators, offering normative and analytical tools for evaluating insolvency systems in a more holistic manner. The findings contribute to insolvency scholarship by bridging fragmented theoretical strands and advancing a human-centered and resilience oriented understanding of corporate failure. The review further suggests that insolvency regimes embedding humanity, resilience, and equity are more likely to enhance institutional legitimacy, stakeholder trust, and long term economic sustainability, thereby providing a robust foundation for future empirical research and policy reform.

Various floods in Jayapura City in early 2025 have caused a number of losses. The problem of the impact of this flood can be solved by reducing the occurrence of flooding again, especially in the long term through the formation of children's character who care about the environment. Activities to increase environmental awareness were carried out by planting flowers focused on children studying at the Rumbel Pelita located at Kali Sunyi, Polda Bhayangkara Public Housing Complex, Buper Waena. The purpose of this community service activity was to increase children's awareness of the surrounding environment through flower planting. The problem posed was how to change children's behavior to care about the environment to prevent flooding. The solution was to increase children's awareness through flower planting at the Kali Sunyi location, Polda Bhayangkara, Buper Waena, Heram District. The method used was through counseling, question and answer sessions, and flower planting activities accompanied by their care. This care was carried out primarily during the learning process at the Rumbel that took place in the future after the community service activity. The results of this community service have been carried out by planting approximately 165 flowers at the Rumbel location, planted by 50 children.

Flood disasters that struck Cikahuripan Village significantly affected the physical, psychological, and learning motivation conditions of elementary school students, particularly at SD N 1 Cikahuripan. In the post-disaster period, students experienced a decline in learning motivation caused by psychological trauma, loss of a sense of security, and limited learning facilities. This Community Service Program (Pengabdian kepada Masyarakat/PkM) aimed to restore students’ psychological conditions while strengthening their learning motivation through an integrated psychosocial and pedagogical approach. The implementation methods included an initial assessment of students’ conditions, trauma healing activities based on play therapy, and the application of Fun Learning methods combined with the “Tree of Dreams” activity to rebuild students’ intrinsic motivation. The program was conducted from 15 to 22 November 2025 and involved 31 elementary school students as well as teachers as sustainability partners. The evaluation results showed significant positive changes, indicated by increased cheerfulness, active participation, confidence in social interaction, and improved learning focus among students. In addition, teachers’ capacity to implement trauma-sensitive teaching practices also improved. This program demonstrates that post-disaster learning motivation recovery requires a holistic approach integrating psychological and academic recovery, and it has the potential to serve as a replicable model for educational interventions in disaster-prone areas.

This research aims to develop a multiclass flower image classification system using the Convolutional Neural Network (CNN) algorithm with the EfficientNet architecture. The main problem addressed is the difficulty of manual identification of flower species that share high visual similarity. The research stages include collecting 17,299 flower images across 19 classes, performing data preprocessing such as image resizing, pixel normalization, and augmentation, followed by model training using the EfficientNet transfer learning approach. The model was trained for 10 epochs with an 80:20 training-validation data split. The evaluation results show that the model achieved a validation accuracy of 98.05% with a loss value of 0.0968, and an average precision, recall, and F1-score of 0.98. The trained model was then implemented into a web-based application built using the Next.js framework, enabling users to upload flower images and obtain real-time classification results via the Hugging Face API. The system successfully identified flower species with a confidence level of 99.87%. These findings demonstrate that combining a modern CNN architecture with transfer learning provides efficient and highly accurate flower classification performance, which can be effectively implemented for educational and digital conservation purposes.

Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.

This study aims to describe the forms of emotional trauma experienced by adolescent victims of verbal violence in Tuntungan Village 1. The study used a qualitative approach with a case study method on three adolescents who were purposively selected based on their experiences of verbal violence in their family environment. Data collection techniques included in-depth interviews, participant observation, and documentation to obtain a comprehensive picture of the psychological condition of the research subjects. The obtained data were then analyzed descriptively qualitatively through the processes of reduction, presentation, and drawing conclusions. The results of the study indicate that verbal violence has a significant impact on the emotional health of adolescents, including decreased learning motivation, the emergence of withdrawal behavior from social environments, and the loss of a sense of security and comfort within the family. In addition, harsh, demeaning, and repetitive family communication patterns form a negative self-concept in adolescents, which has the potential to affect personality development and social relationships in the future. The findings of this study emphasize the important role of families, schools, and communities in creating a supportive environment, as well as the need for preventive efforts and psychosocial interventions to prevent and address emotional trauma in adolescents on an ongoing basis.

Children living in orphanages face various psychological pressures, such as the loss of attachment figures, unstable social dynamics, and difficulty expressing emotions adaptively. These conditions require appropriate coping strategies to build emotional resilience. This community service activity utilizes a Service Learning (SL) approach, which integrates academic learning with community service. It aims to provide psychoeducation on emotions and coping strategies, and implements expressive writing as a means of emotional processing. The activity methods included interactive lectures, a pretest and posttest to measure understanding, an expressive writing therapy session, and a reflective interview at the end of the activity. Results showed an increase in understanding of emotions and coping strategies, as evidenced by improved posttest scores. Furthermore, expressive writing helped children express previously suppressed emotions, reduced psychological tension, and fostered a sense of relief, calm, and insight into personal problems. Overall, expressive writing has proven effective as a coping strategy in building emotional resilience in orphanage children, and the Service Learning approach has the potential for sustainable application in psychosocial support programs.

This community service activity aims to improve the financial literacy of Micro, Small, and Medium Enterprises (MSMEs) through targeted training in calculating the Break Even Point (BEP) as a financial control tool. BEP, or break-even point, is the specific point at which total revenue equals total costs, allowing businesses to determine the minimum sales volume required to avoid losses. The activity was held in the Curug Tourism Village in Bogor Regency, with 27 MSMEs from various business sectors actively participating. The implementation method included outreach, training sessions, practical BEP calculations using participants' actual business data, and post-training mentoring to ensure long-term learning. The results of the activity demonstrated a significant improvement in participants' understanding of the BEP concept and its practical application in determining selling prices, production volumes, and cost control. Therefore, the application of BEP analysis is a crucial and effective strategy in supporting the sustainability and operational efficiency of MSME businesses.

Myalgia is a muscle pain condition that can occur in a specific area of the body or spread to several regions. Its main symptoms include pain, soreness, or discomfort in the muscles, whether during movement or at rest. The pain may range from mild to severe and is sometimes accompanied by stiffness, muscle tension, or even cramps that interfere with daily activities. This condition is commonly experienced by the elderly due to aging, loss of muscle mass, improper physical activity, stress, lack of stretching, or an unhealthy lifestyle. This community service activity aimed to provide education and raise awareness about myalgia among 10 elderly participants in the Elderly Community of Kalirejo, Malang, to help them better understand prevention, pain management, and self-care strategies. The method used was service learning (SL) with achievement parameters measured through pre-test and post-test evaluations. The results showed an increase in participants’ knowledge regarding the definition, causes, and rehabilitation of myalgia from 10% to 90%, demonstrating that this program effectively improved the elderly’s understanding and awareness of myalgia.

This study examines the revitalization of the Qur’anic Education Center (TPA) in Mekar Jaya Village, which had ceased operating due to the loss of its main teacher and limited volunteer support. Using a Participatory Action Research (PAR) approach, the program engaged community members, volunteers, religious leaders, and parents in collaborative efforts to restore regular Qur’an learning activities and strengthen the TPA’s function as a vital center of Islamic education. The intervention led to increased student participation, including the return of former learners and the enrollment of new participants, as well as improved learning motivation through active engagement and parental support. This collaborative revitalization not only revived essential Islamic learning for children but also fostered sustained community involvement, highlighting the critical role of volunteers and local leadership in sustaining nonformal religious education. The model developed through this initiative provides practical implications for other rural communities seeking to maintain and strengthen Islamic educational institutions.

This study presents a machine learning approach for predicting the dimensions of microstrip antenna slots based on antenna performance parameters such as frequency, gain, directivity, return loss (S11), radiation efficiency, and VSWR. A two-phase methodology was employed. In the first phase, ten regression algorithms were evaluated, and Random Forest was identified as the most effective model based on Mean Absolute Error (MAE) and R-squared (R²) scores. In the second phase, hyperparameter tuning was conducted using Grid Search to further improve the model’s performance. The optimized Random Forest model demonstrated consistent improvements in predictive accuracy, with R² values increasing across all output variables. These results indicate that the combination of regression-based modeling and systematic hyperparameter tuning is effective for capturing complex relationships in antenna design tasks. The proposed approach offers a promising data-driven alternative for geometric prediction in microstrip antenna development, particularly when analytical models are insufficient.

Hydroponic plant cultivation is booming, but stock and sales are hard to predict. Poor prediction can cause farmers to overstock and lose money. This study suggests a framework that uses several machine learning models, including Linear Regression (LR), Random Forest (RF), Decision Tree (DT), and Extreme Gradient Boosting. "Ensemble Learning," which combines these models, should yield more accurate and generalizable results than a single model. This framework is assessed using historical hydroponic plant sales data and related factors like price, weather, and market trends. The model's performance is measured by the difference between predictions and actual values using RMSE and MAE metrics. This framework should improve hydroponic plant stock and sales predictions. Farmers can make better production, inventory, and harvest distribution decisions. Besides reducing financial losses, this reduces food waste and improves food security.

One of the government programs created to realize MBKM (Free Learning and Independent Campus) activities is the Teaching Campus. This program is intended for students as agents of change to increase human resources by contributing and providing innovation to educational problems, especially in learning activities. This campus teaching activity includes several activities regarding literacy and numeracy, adapting technology to more innovative methods. The Covid-19 pandemic has caused changes in students' learning patterns (Learning Loss), which has had a major impact on children's interest in learning, understanding of the material and learning outcomes. In connection with existing problems, the aim of writing this journal is to have a direct impact on holding campus teaching programs. Research or studies from this journal were carried out using a qualitative approach in the form of collecting data on learning outcomes during the program. The results of research and studies show that there is an increase in students' interest in learning by using learning media that is more exciting and fun. Apart from that, this learning method is very effective in increasing the value of the learning outcomes of class V students at SDN Simokerto I / 134. Good learning outcomes come from good learning methods, because interest in learning is proportional to the understanding gained too.

Potential weaknesses faced by the company. So it is necessary to consider the aspects of process inefficiency, risk of work errors, delays in information, lack of transparency, high operational costs, vulnerability to data loss and difficulties in monitoring performance. In the current era of globalization and digitization, companies face pressure to increase operational efficiency and accountability in presenting financial information. By using the PALS (Pasticipatory Action Learning System) method, where this method basically involves accounting staff in the process of upgrading the Enterprise Service Bus (ESB) system from 30 accounting staff and 5 staff will be taken for the interview sample in this research. From the problems currently faced by companies in managing financial reports, they have not been able to carry out systematic recording. With better data integration using ESB, a company's various systems and applications can be connected and communicate well. In real-time reporting compared to manual (conventional) recording which requires processing time, ESB allows for better real-time financial reports.

Dampak yang paling menonjol pada pandemi Covid-19 adalah penutupan sekolah dan Pembelajaran Jarak Jauh (PJJ) daring. Guru memberikan bahan pembelajaran dengan memanfaatkan jaringan internet. Guru hanya memberikan bahan pembelajaran melalui zoom padahal peran guru di sekolah bukan hanya memberikan bahan pembelajaran tetapi juga mengasah bakat minat anak. Setiap anak itu unik dengan kemampuan yang luar biasa untuk dikembangkan sesuai dengan potensinya. Guru dalam mengembangkan bahan pembelajaran juga harus memperhatikan potensi anak.Tujuan dari jurnal non penelitian ini adalah peran guru untuk mengembangkan bakat minat siswa di sekolah. Memaksimalkan potensi anak berkaitan dengan bakat dan minat anak juga perlu berkolaborasi dengan orang tua untuk mewujudkan bakat tersebut.

The most noticeable impacts of the Covid-19 pandemic are school closures and online distance learning (PJJ). Online learning uses the Internet to provide teaching materials to students. Barriers to online learning are felt by both teachers and students, with streaming learning via Zoom sometimes having unstable internet connections. Another obstacle to online learning between teachers and students is the teacher-student relationship. You look nervous because you get stuck in the Zoom application. A barrier to online learning between students and parents is that it is difficult for working parents to tutor their children because they are working. The impact of online learning itself takes the form of reduced learning ability and changes in student behavior. The purpose of this non-research journal is that schools need new strategies to meet their post-pandemic educational goals. In order to overcome this, it is necessary to develop human resources by implementing education that reflects the cultural characteristics of the country. Education must respond not only to global requirements, but also to developments in digital technology.

Learning media applications are learning concepts that are carried out through electronic media networks in the form of mobile and non-mobile applications. The development of very advanced technology in the modern era and globalization allows various activities to be carried out quickly and efficiently. Technological developments have had a lot of influence on our way of life, one of which is in the field of education by using online or online learning media applications in learning activities in schools, colleges, courses and even online communities have started using concepts like this. The purpose of this study was to find out how the role of learning media applications in geography subjects in education was during the covid-19 pandemic. As we all know, the losses due to the COVID-19 virus have had a huge impact on all sectors, including the education sector. To achieve this goal, this research will use a qualitative research approach. This research is a type of qualitative descriptive research. Analysis of the data used in processing questionnaire data through google form by describing the results of the questionnaires distributed online.