The purpose of this research is to determine the effect of budget participation, information asymmetry, and autonomous budget motivation on budgetary slack directly or moderated by job relevant information. The population in this research is all village officials in Gianyar Regency who are involved in preparing the village budget in Gianyar Regency. Sampling in this research was carried out by purposive sampling with a sample size of 192 people. Research data was collected through the results of distributing questionnaires and analyzed using the Partial Least Square/PLS analysis technique. The research results state that budget participation has a positive effect on budgetary slack. Information asymmetry has no effect on budgetary slack. Autonomous budget motivation has a negative effect on budgetary slack. Job relevant information is unable to moderate the influence of budget participation on budgetary slack. Job relevant information is unable to moderate the influence of information asymmetry on budgetary slack. autonomous budget motivation against budgetary slack.

This paper explores the transformative impact of Big Data Analytics on Customer Relationship Management (CRM), focusing on its role in enhancing customer engagement and retention. The study highlights how Big Data enables businesses to create personalized customer experiences, anticipate customer needs through predictive analytics, and respond promptly with real-time data analysis. Additionally, the paper discusses using sentiment analysis to refine engagement strategies and applying predictive models to prevent customer churn. The effectiveness of loyalty programs is also examined, demonstrating how Big Data can tailor incentives to boost customer loyalty. The conclusion emphasizes the need for future research into advanced machine learning techniques, ethical considerations, and developing more sophisticated real-time analytics tools. The findings underscore the pivotal role of Big Data in transforming CRM strategies, driving customer satisfaction, and ensuring long-term business success.

Pyrimidine derivatives' many biological functions and possible therapeutic uses have attracted a lot of research in the field of medicinal chemistry. Recent developments in the synthesis, biological assessment, and therapeutic uses of molecules based on pyrimidines are highlighted in this review. The significance of pyrimidine derivatives in treating a range of ailments, including cancer, infectious diseases, and metabolic disorders, is discussed, along with innovative synthesis approaches and important pharmacological findings. In order to give a thorough picture of the present status of pyrimidine derivative research and its implications for upcoming medication development, this review will analyze recent literature and case studies.

The study examined the challenges and prospects of Igbo apprenticeship system in the modern world: The specific objectives were to: determine the challenges of Igbo apprenticeship system in the modern world and examine the prospects of Igbo apprenticeship system in the modern world. The research design was descriptive survey method. Study Area was Enugu State. The sample size of 163 respondents were taken from population of 276 apprentices from different major markets – Kenyetha market (44), Ogbete market (41), Timber market Abakpa (53), Artisans markets (64) and Gariki market (74) Enugu Metropolis business clusters in Enugu state, Nigeria. Research questions of the study were answered using mean score and standard deviation. The hypotheses stated would be tested with chi-square and single regression analysis. The empirical result showed that there are significant challenges of Igbo apprenticeship system in the modern world (Chi-square: 33.62 > Critical-value: 0.000) and there are significant prospects of Igbo apprenticeship system in the modern world (Chi-square: 98.48 > Critical-value: 0.000). The study recommended that Nigerian government should formulate policy that enforce justice between apprentice master and his apprentice to control non-settlement of apprentice after several years of patience.

This study reviews the literature on antenna design in mobile applications, analyzing research, theses, and academic papers to summarize current developments, identify gaps, and suggest future research lines. The review aims to compile the most recent findings on mobile antenna design from respected English-language journals. The study analyzes forty articles discussing both advanced and traditional antenna designs, focusing on efficiency, noise reduction, SAR compliance, size restrictions, polarization, and gain. It emphasizes the importance of innovation and multidisciplinary methods to meet the changing needs of the global communication network. The review uses keywords such as "Antenna," "Antenna Design," "Mobile Antenna," and "Mobile Antenna Design" to find relevant studies across IEEE Xplore, Scopus, Web of Science, and Google Scholar.

Sentiment analysis is the task of automatically identifying the sentiment expressed in text. It has become increasingly important in many applications such as social media monitoring, product reviews analysis, and customer feedback evaluation. With the advent of deep learning techniques, sentiment analysis has seen significant improvements in performance and accuracy. This paper presents a comprehensive survey of machine learning and deep learning methods for sentiment analysis at the document, sentence, and aspect levels. We first provide an overview of traditional machine learning approaches to sentiment analysis and their limitations. We then look into various machine learning and deep learning architectures that have been successfully applied to this task. Additionally, we discuss the challenges of dealing with different data modalities, such as visual and multimodal data, and how both techniques have been adapted to address these challenges. Furthermore, we explore the applications of sentiment analysis in diverse domains, including social media, product reviews, and healthcare. Finally, we highlight the current limitations of deep learning approaches for sentiment analysis and outline potential future research directions. This survey aims to provide researchers and practitioners with a comprehensive understanding of the state-of-the-art deep learning techniques for sentiment analysis and their practical applications.

This qualitative phenomenological study explores the lived experiences of PTA officials, teachers, and school administrators in integrated schools in Montevista, Davao de Oro, from 2017 to the present. Through in-depth interviews with nine respondents, key themes for overcoming challenges and fostering a supportive educational environment were identified: collaboration, determination, unity, and effective leadership. These elements are crucial in addressing the complexities of integrated school settings. The study recommends continuous professional development to enhance skills and knowledge, fostering an inclusive school culture, and ensuring adequate funding and resources from the Department of Education. Additionally, it suggests leveraging innovative solutions such as integrating technology into teaching, establishing mentorship programs for new teachers, and forming partnerships with external organizations for additional support. Promoting resilience and a culture of continuous improvement is also emphasized for navigating future challenges and ensuring sustained success. These findings underscore the importance of these key elements in enhancing stakeholder engagement and educational outcomes, offering valuable insights and a foundation for future research in similar contexts.

Natural Rubber is one of the world's largest commodities used for industrial needs. The price of TSR 20 rubber continues to fluctuate, which has a significant impact on some farmers in various countries. This study analyzes the price trend of TSR 20 rubber in Southeast Asia. The purpose of this study is to analyze trends and fluctuations in STR 20 rubber prices in Southeast Asia, such as Standar Thailand Rubber (STR 20), Standar Indonesia Rubber (SIR 20), Standar Vietnam Rubber (SVR 20), and Standar Malaysia Rubber (SMR 20) for 72 months from January 2017 - December 2022. This research uses trend analysis with simple linear regression method. This research uses the historical method by conducting research on a source which is then critically analyzed. Data collection techniques are obtained by tracing data and documents that have been stored by agencies including the Ministry of Agriculture, Ministry of Trade, International Rubber Study Group (IRSG), Singapore Commodity Exchange (SICOM), Association of Natural Rubber Producing Countries (ANRPC), Food and Agriculture Organization (FAO), The World Bank, and Gapkindo as well as existing literature and sites. The results obtained are positive trends where each development between countries has experienced a positive price increase, such as, STR 20 has a polynomial line equation Y = 0.0331x2 – 95,28x + 68596, then SIR 20 Y = 0.0231x2 -66,443 + 47966, SVR 20 Y = 0,0301x2 – 86,824x+ 62648, and SMR 20 Y = 0,0279x2 – 80,411x + 58010.

According to Basic Health Research, the prevalence of mental health disorders in Indonesia increased to 9.8% in 2018. Meanwhile, in Southeast Sulawesi Province, the prevalence of mental disorders reached 11% with a total of 14,819 cases. The highest cases occurred in Kendari City, namely 2,249 people with a percentage of 12.17%. This study aimed to identify the mental health disorders among adolescents in Kendari City. A descriptive cross-sectional design was conducted in this study. The population was all students of Vocational School 1 in Kendari and the sample size was 49 respondents selected by accidental sampling. Data was collected through filled out questionnaires that adopted from Global School-Based Student Health Survey (GSHS) in 2021. Data analysis was carried out univariately using the epi info 7 application. The results of the study showed that majority of respondents (79.5%), 2% of respondents had attempted suicide. The implementation of stress management in schools was in the poor category (73.5%) and 89.8% of respondents have parents who play an active role in their lives. It was concluded that the majority of students experienced mental disorders and there was even students who have suicide attempt. Lack of implementation of stress management in schools. However, most of the respondents' parents contribute active in their lives. Therefore, it is necessary to implement stress management in schools regularly such us health education, counseling and Focus Group Discussions (FGD) involving all school officials, students and parents.

Integrating Artificial Intelligence (AI) in supply chain management (SCM) signifies a significant advancement with profound implications for modern businesses, including those in Uganda. This research paper critically examines the challenges and opportunities associated with this integration, using Uganda as a case study. A comprehensive analysis of existing literature and specific insights from the Ugandan context identifies critical challenges such as data integration, technology adoption, and organizational readiness within the country. Additionally, it explores AI's diverse opportunities in optimizing supply chain processes for Ugandan businesses, including demand forecasting, inventory management, and logistics optimization within Uganda's unique operational landscape. Furthermore, the paper discusses the potential impact of AI integration on various stakeholders within Uganda's supply chain ecosystem, including suppliers, manufacturers, distributors, and customers. By synthesizing insights from academic research and industry practices in Uganda, this paper provides valuable insights for Ugandan businesses aiming to leverage AI technologies in their SCM strategies. Ultimately, this research contributes to a deeper understanding of the complexities of integrating AI in SCM within the Ugandan context and offers recommendations for addressing challenges while maximizing the opportunities presented by this transformative technology.