This community service activity aimed to provide guidance and capacity building for micro, small, and medium enterprises (MSMEs), specifically chicken satay vendors operating in the parking area of Taman Anggrek Mall, Jakarta. These culinary MSMEs have strong potential due to their strategic location, which attracts high foot traffic. However, many of these business owners still face challenges in managing and developing their businesses, particularly in terms of managerial skills, financial record-keeping, and marketing strategies. Therefore, this program was designed to enhance their business competitiveness by improving their managerial abilities, introducing simple bookkeeping practices, and promoting the use of digital platforms for marketing. The implementation of the program began with an initial observation to identify the specific needs and challenges faced by the MSME actors. This was followed by interactive training sessions covering topics such as the importance of basic financial management, how to create simple financial reports, and effective yet low-cost digital marketing strategies. In addition to the training, the team also provided intensive one-on-one mentoring to ensure that participants could apply the materials in their daily business operations. The outcomes of the program showed positive developments. The MSME participants began to recognize the importance of keeping financial records as a basis for making business decisions. They were also able to identify internal management issues such as inventory control and business planning. In terms of marketing, most of the vendors have started using digital platforms like WhatsApp Business and Instagram to promote their products, allowing them to reach a wider audience.It is expected that this community engagement initiative will continue and serve as a model for similar training programs targeting culinary MSMEs in other busy urban areas. Such efforts are essential to developing more independent, professional, and competitive MSMEs in the digital era.

This study aims to analyze the role of management accounting in supporting strategic decision making at PT ABC, a manufacturing company. Management accounting is seen as an important tool in providing relevant financial and non-financial information for planning, controlling, and evaluating performance (Langfield-Smith, 2008). The research method used is a case study with a qualitative approach, where data is collected through in-depth interviews with management and accounting staff, as well as analysis of internal company documents. The results of the study indicate that management accounting plays an important role in providing production cost information, profitability analysis, and performance reports, which are the basis for management in making strategic decisions such as determining selling prices, allocating resources, and planning production capacity (Chenhall & Moers, 2015). However, the study also identified several challenges, such as limitations in information systems and data integration between departments. The implication of this study is the need to improve management information systems and staff training to maximize the benefits of management accounting in strategic decision making. These findings are expected to contribute to the development of more effective management accounting practices in manufacturing companies (Hall, 2010).

The development of Augmented Reality (AR) technology in the e-commerce sector offers new opportunities to enhance online shopping experiences through immersive and interactive features. This study aims to analyze the influence of AR characteristics—interactivity, vividness, novelty, and informativeness—on consumer perceptions (perceived enjoyment, perceived usefulness, and hedonic value), and how these perceptions affect attitudes, satisfaction, and purchase intention on the Shopee platform. A quantitative approach was employed, with data collected from 100 active Shopee users who have experienced using AR features. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that most AR characteristics significantly affect consumer perception. Furthermore, perceived enjoyment, usefulness, and hedonic value were found to influence user attitudes and satisfaction, ultimately increasing purchase intention. This study contributes theoretically to the understanding of AR integration in consumer behavior within e-commerce, and provides practical implications for businesses in designing immersive technology-based marketing strategies.

In the rapidly evolving digital economy, small and medium sized enterprises (SMEs) are increasingly using digital marketing strategies to overcome traditional barriers to internationalization. However, despite growing accessibility to digital platforms, many SMEs struggle with strategic integration, limited technological readiness, and institutional constraints. This study investigates how digital marketing tools such as search engine optimization (SEO), social media, e-commerce, and customer relationship management (CRM) can be effectively leveraged to support SME international growth. The research adopts a qualitative methodology using literature review and thematic analysis of over twenty peer reviewed studies from 2020 to 2024, aimed at developing a conceptual model that maps the interaction between digital tools, internal mediating capabilities (digital trust and technological readiness), and external moderating factors (institutional barriers and market volatility). The findings indicate that while digital tools facilitate market visibility, customer engagement, and transactional efficiency, their success is significantly influenced by internal readiness and external conditions. The resulting conceptual model offers a comprehensive framework for SMEs to align their digital strategies with internationalization goals and highlights the role of policymakers in supporting digital infrastructure and capability development. This research contributes to both theory and practice by bridging digital marketing and international entrepreneurship, proposing a roadmap for sustainable global expansion through adaptive digital strategies.

Fundamentally, every individual has two basic needs that must be fulfilled, namely physical and spiritual needs. One of the physical needs that has grown significantly in the digital era is the need for convenience in conducting financial transactions. This study aims to analyze the comparison of satisfaction levels among students of UIN Sunan Gunung Djati toward the four largest e-wallets in Indonesia: Dana, Ovo, ShopeePay, and Gopay. The research employed a quantitative method with a sample size of 20 respondents. The instrument used was a questionnaire distributed via Google Form. As consumers, students not only consider ease of use and low transaction fees, but also pay attention to service quality, security, and transaction speed. Therefore, e-wallet service providers are expected to continuously improve their service quality in order to meet users’ expectations and needs optimally.

This research is motivated by the importance of promoting environmentally friendly behavior (Employee Green Behavior) in the state-owned construction service industry. The study aims to examine the influence of Green Organizational Culture (GOC), Green Work Engagement (GWE) and Green Human Resource Management (GHRM) as the antecedent of EGB. The research methodology employs a quantitative approach through surveys conducted with employees of construction service companies under state-owned enterprises (BUMN). The sampling technique used in this study is simple random sampling, involving a total of 386 permanent employees from construction companies. The analysis method utilized in this research is Structural Equation Modeling (SEM) based on Partial Least Squares (PLS), using the SmartPLS 3.0 analysis tool. The results indicate that GHRM, GOC, and GWE directly influence EGB. These findings reinforce the AMO and NAM theories. This research contributes theoretically to the literature on sustainable human resource management and provides practical benefits for companies sustainable strategies.

Fibrosis hati merupakan kondisi yang berpotensi berkembang menjadi sirosis atau kanker hati jika tidak terdiagnosis dengan tepat. Prosedur biopsi hati yang invasif sering digunakan dalam diagnosis, namun memiliki risiko dan keterbatasan biaya. Penelitian ini bertujuan untuk membandingkan kinerja model deep learning, yaitu Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), dan Feedforward Neural Network (FNN) dalam klasifikasi fibrosis hati menggunakan citra medis. Metode yang digunakan adalah evaluasi kinerja model berdasarkan metrik akurasi, presisi, recall, F1-score, dan loss pada dataset citra medis fibrosis hati. Hasil penelitian menunjukkan bahwa CNN memberikan kinerja terbaik dengan akurasi 98%, diikuti oleh LSTM dengan akurasi 97%, dan FNN dengan akurasi 80%. CNN unggul karena kemampuannya dalam mengekstraksi fitur spasial secara otomatis dari citra medis, sementara LSTM lebih cocok untuk data sekuensial dan FNN terbatas dalam menangani data citra kompleks. Penelitian ini menyimpulkan bahwa CNN lebih efektif dalam klasifikasi fibrosis hati dan dapat menjadi alternatif non-invasif yang lebih efisien dibandingkan metode konvensional seperti biopsi. Teknologi ini berpotensi mempercepat diagnosis fibrosis hati dengan akurasi tinggi dan tanpa risiko komplikasi invasif.
 
Kata kunci: Fibrosis hati, CNN, LSTM, FNN, klasifikasi citra medis.

Food security and community economic empowerment are major challenges in many rural areas, including Sukolilo Village. This research aims to develop and analyze the effectiveness of an aquaponic system, a combination of hydroponics and fish farming, as an innovative sustainable solution. The methods used include observation, experimentation, and interviews with the local community. The results showed that the aquaponic system is able to increase agricultural productivity with better water use efficiency and provide economic benefits through crop diversification, namely vegetables and fish. In addition, the system is proven to be environmentally friendly as it utilizes organic waste from fish as plant nutrients, reduces the use of chemical fertilizers, and optimizes local resources. The implementation of the aquaponic system in Sukolilo Village not only improves food security but also opens up new business opportunities for the community, thus contributing to the improvement of local economic welfare. It is hoped that this model can be replicated in other areas as part of a sustainable agriculture-based economic development strategy.

Computer vision-based algorithms, especially Convolutional Neural Networks (CNN) and You Only Look Once (YOLO), have become the leading approaches in plant disease detection. CNN excels in extracting complex visual features for disease classification, while YOLO provides high-efficiency real-time object detection capabilities. Both algorithms have shown promising results in various studies, especially with controlled datasets. However, challenges remain in their application in real-world conditions, such as environmental diversity, overlapping symptoms, and poorly annotated data. Future research has the potential to optimize these algorithms through the development of lighter models, the use of transfer learning techniques, and multi-modal data integration. In addition, further exploration of a wider range of diseases, crops, and environmental conditions can expand the application of these algorithms. By leveraging these innovations, computer vision-based plant disease management can be improved to support sustainable precision agriculture.

Clean water is a fundamental necessity for public health, as water contamination can lead to various health problems, such as gastrointestinal infections, skin diseases, and other health issues. Screening for water contamination by Escherichia coli bacteria and Corynebacterium spp. is essential to ensure water quality remains safe. This community service activity was conducted in the Duri Kosambi area, focusing on education and water quality testing. The program included planning educational sessions on the risks of water contamination, implementing screenings using colony-forming unit (CFU) parameters to detect Escherichia coli and Corynebacterium spp., and evaluating results to provide preventive recommendations. The findings revealed variations in contamination levels across locations, with some meeting cleanliness standards, while others, such as B04, showed extreme contamination. This activity highlights the importance of community education, regular water quality monitoring, and water treatment to prevent health risks. Collaboration among communities, governments, and health organizations is crucial to maintaining sustainable access to high-quality clean water.