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THE EFFECT OF PROFITABILITY AND FINANCIAL LEVERAGE ON NET PROFIT (CASE STUDY OF BASIC INDUSTRY AND CHEMICAL SECTOR COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE 2015-2017) Riansyah, Reza Juang; Agutiyana, Sulis
Journal Economics & Business Atmajaya Indonesia Vol 4 No 1 (2020): Journal of Economics & Business (JEBI)
Publisher : Penerbit Atma Jaya Catholic University of Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (771.024 KB) | DOI: 10.25170/jebi.v4i1.63

Abstract

Net earning changeare movements in corporate profits calculated by subtracting current period profits from previous period profits divided by profits in the previous period. Financial ratios function to find out whether the company is healthy or not in company performance, especially financial performance as a consideration for investors to invest, which of course will have an impact on changes in company profits. This study aims to investigate the effect of profitability as proxied by Return on Assets (ROA) and financial leverage which is proxied by the Debt to Equity Ratio (DER) to changes in earnings. The object of this research is the Basic and Chemical Industry Sector listed on the Indonesia Stock Exchange in the period 2015-2017. The steps used to take samples based on predetermined criteria are called purposive sampling so there are a sample of 51 companies. This observation uses multiple linear regression analysis. This study shows that both simultaneously and partially ROA and DER affect earnings changes.
Towards Entrepreneurial Campus Sustainability: Integrating Artificial Intelligence for Resource Allocation in Business Management Juanda, Juanda; Riansyah, Reza Juang; Arsadi, Arsadi; Bethany, Laurens
Aptisi Transactions On Technopreneurship (ATT) Vol 6 No 3 (2024): November
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v6i3.410

Abstract

This research delves into the utilization of artificial intelligence (AI) within the framework of campus resource allocation, with a primary focus on enhancing business management practices and fostering entrepreneurial sustainability within educational institutions. Through an innovative amalgamation of AI technology and SmartPLS methodology, the study constructs a comprehensive analytical framework aimed at tackling the multifaceted challenges inherent in resource allocation within campus environments. The findings underscore the transformative potential of AI integration in optimizing resource utilization, identifying efficiency gains, and nurturing entrepreneurial endeavors. This paper distinguishes itself from existing studies by presenting a novel approach that emphasizes the unique contributions of AI-driven solutions in both methodological innovation and practical application. By harnessing SmartPLS alongside AI, the research facilitates more accurate resource demand forecasting and enables adaptive decision-making processes, thereby contributing to the Sustainable Development Goals (SDGs), particularly in promoting quality education and sustainable management practices. The study also provides a detailed technical implementation of AI algorithms, offering valuable insights into their development and application within campus settings. The broader implications for the educational sector are explored, considering the scalability and adaptability of the proposed solutions in various educational contexts. Furthermore, the research contributes to theoretical advancements by pioneering the integration of AI and SmartPLS in campus management research, offering a fresh perspective on economic, environmental, and social impact assessments of AI-driven solutions.