The growth of big data has driven the need for efficient data processing methods, especially in cloud computing environments. This study evaluates distributed computing frameworks like Apache Hadoop and Apache Spark for optimizing big data processing. By analyzing different configurations, we demonstrate how distributed systems can significantly reduce processing time and improve resource utilization, making them ideal for handling complex datasets in cloud environments.

This research investigates the impact of corporate governance practices on the financial performance of banks. By analyzing data from various banking institutions, the study reveals that effective governance mechanisms, such as board diversity and regulatory compliance, positively influence profitability and risk management. The results provide insights into how banks can enhance their performance through improved governance structures.

Obtaining high-quality, diverse, accurate datasets for sentiment analysis has always been a significant challenge. Traditional approaches include annotators, which may introduce bias to datasets and are also time-consuming and expensive. These types of datasets may also not represent the variety needed to train robust and generalizable sentiment analysis models. This study introduces a novel combination of techniques to approach the problem with a novel solution. The proposed system, SentiGEN includes the use of a transformer, T5, fine-tuned and optimized using an evolutionary algorithm to generate high-quality, diverse, accurate data for sentiment analysis. The generated data is validated using XLNet to ensure high sentiment accuracy. This combination of technologies has proven successful based on the results derived from evaluating multiple models. From complex transformers such as BERT to more straightforward approaches like KNN, those trained using synthetic data demonstrated superior performance compared to their counterparts trained on real data. This enhancement in predictive accuracy was observed when evaluated on benchmark datasets such as SST-2 and Yelp. SentiGEN can generate high-quality, diverse, accurate, realistic data for sentiment analysis and successfully increased the performance of models trained on synthetic data compared to the same model trained on real data.

This article explores the relationship between mental health outcomes and social determinants of health among immigrant populations. By analyzing survey data, the research identifies key factors such as socioeconomic status, access to healthcare, and social support that influence mental health. The findings suggest that addressing social determinants is essential for improving mental health outcomes and providing effective support services for immigrants.

This research was conducted with the aim of finding out the role of Balinese culture, strategy and impact on improving human resources for craftsmen in Tenganan Pegringsingan Village. The data analysis technique used is a non-statistical analysis technique because the data in this research is qualitative data which prioritizes descriptions and arguments from researchers and sources. The results of the research state that Balinese culture, especially gringsing woven cloth, has an important role for the world, namely being a cultural asset and can be used as a means of improving the regional economy. Balinese culture, especially gringsing woven cloth, has a big impact on improving human resources for gringsing woven cloth craftsmen. Based on this research, it is necessary to preserve culture, increase human resources and utilize large events such as the G20 Presidency. In order to be able to provide reference contributions in the field of management economics and be able to provide suggestions and criticism to Gringsing woven fabric entrepreneurs to always maintain and improve product quality. 

This research is entitled “Effectiveness of Subsidized Sharia Mortgage Financing for Low- Income Communities at BTN Syariah Langsa City. This study uses a qualitative descriptive method, with the formulation of the problem, 1) How is the implementation of Islamic mortgage financing for low-income customers at Bank BTN Langsa City?, 2) How is the effectiveness of Islamic mortgage financing for low-income people at Bank BTN Langsa City?, from the results of the research of the bank and the dispatcher have followed the regulations from the government from the housing mortgage program, but with regulations from the government, the depeloper is an obstacle they cannot freely choose customers, with regulations made by the government even though people who are gardeners are farmers and fishermen even though they are able to take mortgage housing, there are also people who feel helped by the KPR program from thegovernment.

Hemoglobin (Hb) is an erythrocyte tetrameric protein that binds to non-protein molecules, namely the iron porphyrin compound called heme. Hb is one of the laboratory tests on pregnant women which can support the diagnosis or occurrence of complications in pregnant women, these complications can be detected through danger signs of pregnancy. Danger signs of pregnancy are signs that indicate dangers that can occur during pregnancy (antenatal), which if not detected can cause death. The aim of this community service is to facilitate Hb checks and to increase knowledge of pregnant women through education about the danger signs of pregnancy. The method of this activity is carried out by checking hemoglobin levels using the Sahli method and providing counseling using the discussion method to pregnant women about the danger signs of pregnancy and using the KIA book as the medium. This counseling was carried out at the Batursari Village Posyandu which was attended by 10 pregnant women. The results of the counseling showed that 8 pregnant women had normal Hb, 1 pregnant woman was in the mild anemia category, and 1 pregnant woman was in the severe anemia category. and after education regarding the danger signs of pregnancy, all pregnant women have good knowledge.

The eyes are crucial tools for human observation and perception, facilitating various tasks in daily life. Individuals, including those with visual impairments or blindness, engage in currency transactions, posing challenges in recognizing notes and preventing mishaps with counterfeit money. Despite government efforts, features like embossing on banknotes have limited effectiveness due to the circulated currency's disheveled condition. Addressing the visually impaired community's needs is imperative. An innovative solution, the "all-in-one smart white cane," integrated with machine learning supports daily activities, enhancing independence for visually impaired individuals. The YOLOv8 algorithm is employed for the precise detection of monetary denominations, subsequently recorded through a camera and seamlessly integrated into a smart cane, resulting in a consolidated device. This device, designed with standout features, excels in detecting Indonesian Rupiah banknote denominations. Detection performance testing, incorporating methods like object rotation, utilized a dataset divided into training (70%), validation (20%), and test (10%) segments. Modifications to contrast and variability rotation are essential in the context of real-time nomination recognition. These adjustments are implemented to ensure accurate and swift identification in dynamic, real-world scenarios. Testing results reveal a 99% average accuracy in recognizing currency note denominations, presenting an effective solution for the visually impaired community.

Whistleblower protection in the context of the environmental and Natural Resources sector is a key element in efforts to prevent corruption and sustainable management. This sector has a direct impact on human lives and societal well-being, and therefore, maintaining its integrity is essential. This research outlines the importance of whistleblower protection in the environmental and natural resources sectors. The method used in this research is normative with a doctrinal approach. Protection of whistleblowers has an important role in maintaining transparency and accountability in the environmental and natural resources sectors. Through the protection provided to whistleblowers, corrupt practices can be exposed and accountability can be realized. However, challenges and limitations still exist, and concerted efforts are needed to improve the implementation and effectiveness of these laws. With continued efforts, whistleblower protection laws can become a powerful tool in promoting transparency and accountability in the environmental and natural resources sectors.

This study investigates the effects of e-commerce growth on traditional retail businesses in emerging economies, focusing on market share shifts, consumer behavior, and sales trends. Analyzing data from Southeast Asian and African markets, the research reveals how e-commerce platforms are reshaping customer preferences, posing both challenges and opportunities for traditional retailers. Findings suggest that the rise of e-commerce is leading to a transformation of the retail landscape, with significant implications for future business models and strategies.