Pemenuhan Hak Politik Warga Negara Oleh Komisi Pemilihan Umum (KPU) Kota Banjarmasin (Studi Kasus Penyandang disabilitas)

Political rights for people with disabilities are one component of Human Rights that must be fulfilled. However, if you look at the reality today, there are still many political rights for people with disabilities that are not fulfilled. The aim of this research is to see and analyze the form of fulfillment of political rights regarding socialization for people with disabilities and the form of provision of infrastructure and facilities by the General Election Commission (KPU) of Banjarmasin City. This research uses descriptive qualitative methods by conducting interviews and observations. The results of this research show that the Banjarmasin City KPU fulfills the Political Rights of Persons with Disabilities in two ways. First, by providing interpreters for deaf people in outreach activities regarding procedures and mechanisms related to general elections. Second, the provision of facilities and infrastructure for blind people with disabilities is provided with braille aids in elections. and providing wheelchair access and friendly services for people with disabilities in Banjarmasin City

Population and Habitat Characteristics of Tarsius fuscus in Resort Mallawa Bantimurung Bulusaraung, South Sulawesi

Tarsius fuscus is one of the conservation priority wildlife in the Bantimurung Bulusaraung National Park (Babul National Park). This study aims to analyze the population and habitat characteristics of T. fuscus as one of the considerations in the conservation management of its population and habitat. This research was carried out in July 2021 in the forest around Bentenge Village and Samaenre Village, Resort Mallawa, Babul National Park. The method used was direct observation, calculation of the number of individuals for each group, and vegetation analysis at the meeting points of  T. fuscus. Based on observations, the population size of 48 individuals from 13 groups was obtained with an overall population density of 0.109 individuals/Ha.  The population density in the secondary dryland forest is higher than in the scrubland. The number of juvenile and infant in both land cover were low compared to  the adults.  T. fuscus was found in two types of habitat, there are secondary dryland forests (SDF) and scrubland with specific ranges of physical parameters. Based on vegetation analysis, SDF was dominated by the mana-mana tree (Blumeodendron kurzii) with an important value index (IVI) of 57.72%, while shrubland was dominated by kemiri tree (Aleurites moluccana) with an IVI of 40.75%. The two land covers are dominated by the Moraceae family and jambu air seedlings (Syzygium aqueum)

Ownership Structure and Bank Performance

This paper provides evidence on the impact of different types of ownership structure on bank performance.Using secondary data, the empirical analysis of this study is confined to Malaysian commercial banks during the period of 2000 to 2011. Multiple regression with fixed effects model is used to test the research model.Testing on five categories of ownership structure such as insider, family, government, institutional and foreign ownership, the results suggest that bank performance varies with different types of ownership structure

Transformative Impact of Deep Learning in Stock Market Decision-Making: A Comparative Study of Convolutional Neural Networks

This research delves into the transformative impact of deep learning, specifically Convolutional Neural Networks (CNNs) such as VGG16, ResNet50, and InceptionV3, on organizational management and business intelligence. The study follows a comprehensive methodology, emphasizing the importance of high-quality datasets in leveraging deep learning for enhanced decision-making. Results demonstrate the superior performance of CNN models over traditional algorithms, with CNN (VGG19) achieving an accuracy rate of 89.45%. The findings underscore the potential of deep learning in extracting meaningful insights from complex data, offering a paradigm shift in optimizing various organizational processes. The article concludes by emphasizing the significance of investing in infrastructure and expertise for successful CNN integration, ensuring ethical considerations, and addressing data privacy concerns. This research contributes to the growing discourse on the application of deep learning in organizational management, providing a valuable resource for businesses navigating the dynamic landscape of the global market

Unleashing Deep Learning: Transforming E-commerce Profit Prediction with CNNs

This research examines the potential of Convolutional Neural Networks (CNNs), including VGG16, ResNet50, and InceptionV3, in predicting ecommerce profits. Emphasizing the importance of high-quality datasets, the study showcases the superior performance of CNN models over traditional algorithms, particularly noting a notable accuracy rate of 92.55% with CNN (VGG16). These results highlight deep learning's capability to extract actionable insights from complex ecommerce data, offering significant opportunities for revenue optimization and operational efficiency improvement. The conclusion underscores the need for investment in infrastructure and expertise for successful CNN integration, alongside ethical and privacy considerations. This research contributes valuable insights to the discourse on deep learning in ecommerce, offering guidance to businesses navigating the competitive global market landscape