Journal of Applied Business and Technology

The Impact of Government Accounting Standards Implementation, Internal Control Systems, and Human Resource Competence on Regional Financial Report Quality

Elfita Yenni — 2024-09-30

This study introduces a comprehensive model that simultaneously investigates the interplay of Government Accounting Standards Implementation, Internal Control Systems, and Human Resource Competence in determining regional financial report quality. This study employs a quantitative research design. The sample size for this study is 96 respondents, meeting the minimum requirement for Structural Equation Modeling (SEM) analysis. Only human resource competence can improve regional financial report quality. These findings align with Agency Theory, emphasizing that competent agents (human resources) are critical for reducing information asymmetry and improving financial reporting. They also connect to Institutional Theory, illustrating that formal systems like GAS and ICS require human agency to operationalize institutional norms effectively. Finally, the results support Resource-Based Theory (RBT), highlighting HRC as a strategic resource that drives organizational success in financial reporting. Future studies should explore the impact of external audits, political stability, and organizational culture on financial report quality.

Comparison of Feature Selection with Information Gain Method in Decision Tree, Regression Logistic and Random Forest Algorithms

Muhammad Sholeh — 2024-09-30

One of the approaches that can be done is to perform feature selection. Feature selection is done by identifying the most informative features and not using features that do not directly contribute to the target feature. The purpose of feature selection is to increase the accuracy of the model. The research was conducted by comparing the performance of the model by comparing the accuracy results of the model without any feature selection with the model that has done feature selection. The process is done by comparing the accuracy results with decision tree, random forest and SVM algorithms. In the research method of feature selection on science data, the steps include understanding the domain and dataset, exploratory analysis, data cleaning, measuring feature relevance with criteria such as Information Gain, and feature ranking. The results are evaluated and validated using model performance metrics before and after feature selection. This process ensures selection of relevant features, improving accuracy. The research process used the Lung Cancer Prediction datasheet which consists of 306 rows and 16 attributes. The results show that feature selection can improve the performance of the classification model by reducing features that do not contribute to the target. Comparison results using decision tree, Regression Logistic and random forest classification model algorithms and feature selection resulted in a high accuracy value of 0.968 in the Regression Logistic algorithm with a feature selection of 5.

Impact of Stock Split on Stock Return in Companies Listed on the India Stock Exchange

Ahmed Ahmed A. Mahmood — 2025-01-10

The aim of this research is to evaluate the impact of a company's announcement, which in this case is a stock split, on the return of a company's stock listed on the Indian stock market. basing on this, the extent and significance of the effect is measured and examined through parametric and non-parametric tests. due to the aim of the paper is to test if the stock split will have a positive influence on the stock price around the implementation of the policy, we use the event study method and set regression model. In order to test the effect of the strategy, we picked estimation period and event period from each stock, and conduct regression analysis respectively. As suggested by the cumulative average AR value, the precision weighted CAAR and the ABHAR, the results imply that during the short window event of pre- and post-10 days of stock splits, the selected company have witnessed significant ARs so we reject H0 and accept H1, which suggests the presence of ARs within the event window. Similarly, other tests such as Patell_z, Cross-sectional Test-t, Generalized Sign_z, Std. Cross-sectional Test_z and Adjusted Patell_z also suggest to reject H0 stating that there are ARs during the study window of the stocks splits. However, these findings are based on the 10-days event and 90-days estimation windows used for analysis and impact of the stocks splits on the stock returns of the selected company.

Revisiting the Future of International Marketing Strategy in the Digital Age

Muhammad Adrian Agusta — 2024-09-30

This paper explores the opportunities and challenges of the digital era in international marketing strategy. Focus on designing and implementing internet-based strategies, including internal company factors, external environment, market selection, mix marketing, and strategic control. Conceptual study This compiles and analyzes factors that influence marketing international use of digital technology. Digital technology influences decisions on foreign market selection, implementation, and control of marketing strategies. This allows the company to design effective marketing programs, support the implementation of digital devices, and improve performance internationally. This study gives a framework Work for marketing strategy internationally digital based and identifies opportunities for future research in the digital era.

The Bright Side of Artificial Intelligence in Corporate Leadership: A Rapid Literature Review of the Past Five Years

Nyoto Nyoto — 2024-09-30

Artificial intelligence (AI) has emerged as a transformative force in corporate leadership, significantly reshaping how organizations operate and adapt in an increasingly digital world. As AI continues to evolve, understanding its impact on leadership practices is crucial for organizations seeking to stay competitive. This study employs a Rapid Literature Review approach to explore AI's beneficial impacts on corporate leadership over the last five years, synthesizing findings from 21 research articles. The PRISMA 2020 framework is used to select the articles for review, and Atlas.ti is applied to identify patterns in the literature and label the findings. The analysis reveals five key domains where AI demonstrates significant benefits, including building trust and ethical governance, enhancing decision-making and strategic insights, improving collaboration and team dynamics, increasing operational efficiency and productivity, and fostering emerging leadership dimensions. The findings highlight how AI embeds transparency and accountability, supports data-driven decision-making, and optimizes human resource processes. Additionally, AI fosters innovation by enabling leaders to adopt inclusive practices. This study provides valuable insights for leaders seeking to leverage AI for sustainable growth, emphasizing its potential in reshaping corporate leadership. By understanding and implementing these benefits, organizations can position themselves to thrive in the era of digital transformation.

Blue Innovation, Value Creation, and Decision-making on Digital Performance and Sustainability

Nicholas Renaldo — 2024-09-30

This study proposed model framework introduces a novel approach by positioning Blue Innovation as a primary driver of Value Creation and Decision-Making, which in turn mediate the relationship between Digital Performance and Sustainability. In this quantitative research, data will be collected using a structured questionnaire. The sample size will be 155 respondents. This study uses Structural Equation Modeling (SEM) analysis to analyze the influence of independent, intervening, and control variables on the dependent variable. The findings provide significant insights into how these variables interact and influence one another, summarized as blue innovation significantly enhances digital performance, value creation has a strong positive impact on digital performance, decision-making significantly improves digital performance, blue innovation positively influences sustainability, value creation cannot directly increase sustainability, decision-making has a significant positive impact on sustainability, digital performance significantly enhances sustainability, blue innovation increases sustainability through digital performance, value creation indirectly increases sustainability through digital performance, decision-making positively influences sustainability through digital performance.