In the era of globalization and intense business competition, the quality of products and services is crucial for competitiveness, particularly for Micro, Small, and Medium Enterprises (MSMEs) like Angkringan, a traditional culinary business in Indonesia. The article explores Total Quality Management (TQM) as a strategy for these businesses to enhance operational efficiency, reduce waste, and improve customer satisfaction. The study involved direct interviews with the owner of Angkringan D’Amerta to analyze TQM application covering quality control procedures, customer satisfaction, and continuous improvement. Results indicated a deeper understanding of customer preferences and the importance of maintaining quality standards through the training of staff and development of operational procedures. The findings suggest that effective quality management can significantly enhance business performance and customer engagement in the digital era. The paper advocates for routine training, implementation of standard operating procedures, and regular quality assessments to ensure consistent service and product quality.

Public open space can provide a special identity for a city. Generally, the shape of public open spaces must be able to accommodate a variety of user activities and have characteristics that attract people to come. The purpose of this study is to determine the correlation between motivation and atmosphere characteristics in public open spaces in Palembang City. This research uses quantitative methods that are explanatory. The data collected by using the semantic-differential (SD-method) with the sample selection using snowball-non-random-sampling. The results of the latent variable analysis and Multivariate Correlation Analysis are in the form of a relationship between motivation and the atmosphere in public open spaces in Palembang City. The results of this study indicate that the motivation of the people who come to open public spaces has reasons, that are refreshment, achievement and interaction. This motivation is supported by the influence of the atmosphere in public open space which is assessed from two aspects, such as orderliness and natural environment.

Rubber productivity is very important for the life and welfare of rubber farmers in Pangkalan Balai Sub-district, Banyuasin, where most of the population is rubber farmers. In this study, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis was used to analyze the influence of the internal and external environment of rubber farmers that affect the strategies used to increase rubber productivity in Pangkalan Balai Sub-district. This study used a descriptive-qualitative method by conducting interviews with 10 rubber farmers spread across Pangkalan Balai Sub-district. The results of this study are known based on IFAS and EFAS and the SWOT matrix is ??in quadrant III, namely using a defensive strategy. The implications of this study are used to increase rubber productivity in Pangkalan Balai Sub-district, namely by synergizing with the local government with a defensive strategy.

Childbirth causes pain due to shortening of the uterine muscles. Normal childbirth occurs because of pain, which is an important part of labor. During labor, pain can influence uterine contractions through the secretion of catecholamines and cortisol. It improves the function of the sympathetic nervous system, changing blood pressure, heart rate, breathing, and length of labor. The aim of this research is to find out how warm compresses impact how severe the pain of labor during the first active phase is. This research design is pre-experimental with a one group pre test and post test design. The population in this study were all mothers giving birth at BPM Nursehan Dahliana Birayang (Hulu Sungai Tengah Regency, South Kalimantan Province), using an accidental sampling technique and a sample size of 30 respondents was obtained. A warm compress is placed on the lower abdomen using a hot bladder. Data analysis used the Paired T - test. Based on the research results obtained, the average pain score before treatment was 8.13 and the average pain score after treatment was 4.66. The results of statistical analysis of tests of differences in pain intensity before and after treatment showed significant differences (p=0.000; 95% CI -3.900-(-3.031). The conclusion of this study is: warm compresses can reduce the intensity of labor pain in the active phase of the first stage. Warm compresses can be used as a way to reduce the intensity of labor pain.

Optimal growth of broiler chickens and effective health monitoring are the main challenges in the livestock industry. Deep learning technologies, such as Differential Recurrent Neural Networks (DRNN), Long Short-Term Memory (LSTM), and Improved Feature Fusion Single Shot MultiBox Detector (IFSSD), offer innovative solutions for predicting chicken growth and detecting health conditions in real-time. This research aims to review the application of deep learning in growth forecasting and health monitoring of broiler chickens through systematic analysis using the PICO and PRISMA methods. Of the 150 studies identified, 30 met inclusion criteria for further analysis. The results show that DRNN and LSTM achieve high accuracy in processing temporal data, with an average growth prediction error of 1.8%. IFSSD excels in detecting chicken health via digital images, achieving 99.7% accuracy. Although the results are promising, challenges such as the need for high computing resources and the quality of data required for model training are major obstacles. This research suggests the need for investment in technological infrastructure, farmer training, and development of more efficient models to support the application of deep learning in broiler chicken farming. This technology has great potential to significantly improve production efficiency and animal welfare.

The purpose of this research is to know and analyze the influence of authentic leadership and servant leadership partially and simultaneously on performance of health workers in Batam City. The method used in this research uses a method, namely the type of research used in this research is a quantitative research method. This research uses an analytical tool is SPSS Version 23. The population in this study is all health workers spread across Batam City whose numbers cannot be known and recorded with certainty. The sampling method in this study used accidental sampling technique. By using the Zikmund formula, the final sample size used was 100 people. The results of this research are (1) Authentic leadership partially has a positive and significant effect on performance of health workers, (2) Servant leadership partially has a positive and significant effect on performance of health workers (3) Authentic leadership and servant leadership together or simultaneously have a positive effect and significant to the performance of health workers. The coefficient of determination (adjusted R square) is 0.669 or equal to 66.9%. This figure means that the independent variables consisting of authentic leadership and servant leadership affect performance of health workers variable while the remaining 29.1% of the performance of health workers variable is influenced by other variables not examined in this study

This study aims to explore the impact of supply chain automation on workers’ well-being in the sustainable industrial sector through a Systematic Literature Review (SLR) approach. The transformation driven by Industry 4.0 technologies such as artificial intelligence (AI), Internet of Things (IoT), and blockchain, has presented significant challenges and opportunities. This study identifies the impacts of automation on workers’ economic, social, and psychological aspects, including changes in skills requirements, reduction of manual employment, and its effects on mental health. In addition, this study also highlights the importance of sustainability in automation implementation, by balancing economic efficiency, environmental preservation, and social welfare. By integrating the results of studies from various literatures, this study provides recommendations for policies that support sustainability and social inclusiveness, as well as strategic guidance for industries in adopting supply chain automation sustainably.

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.

This research is a Systematic Literature Review (SLR) aimed at analyzing the application of Artificial Intelligence (AI) technology in the management of information technology (IT) projects. This study focuses on identifying the AI technologies employed, the benefits gained, and the challenges faced in implementing these technologies. The study gathers and analyzes literature from various leading databases, including Scopus, IEEE Xplore, and SpringerLink, within the timeframe of 2015–2025. The findings reveal that AI technologies such as machine learning, predictive analytics, and natural language processing play a significant role in improving efficiency, reducing risks, and supporting decision-making in IT project management. However, challenges such as data quality, organizational resistance, and implementation costs remain major obstacles in adopting this technology. This review provides comprehensive insights into trends, benefits, and barriers associated with AI utilization, along with recommendations for more effective implementation in the future.

A healthy and charming personality is an important element in socializing in the family, society and organization. Efforts that need to be developed so that the personality is charming must function fully by recognizing the weaknesses and strengths that are owned such as being open to experience, self-confident, living existentially, having a sense of freedom, physical and spiritual needs are met, and being able to develop oneself. And having broad insight, skills, good personality and a charming appearance that can not only utilize its advantages optimally, but is willing to face the shortcomings that exist within itself.