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Pengaruh Free cash flow, Kepemilikan Institusional, Profitabilitas dan Leverage Tehadap Kebijakan Dividen Tunai Pada Perusahaan Property dan Real estate yang Terdaftar di Bursa Efek Indonesia Syelly Wulandari; Nita Priska Ambarita; Mia Dwi Puji Wahyuni Darsono
Akuisisi: Jurnal Akuntansi Vol 15, No 2 (2019)
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/akuisisi.v15i2.429

Abstract

This research aims to examine and analyze the effect of free cash flow, institutional ownership, profitability and Leverage on dividend policy by using an approach multiple regression model. The proxies used to measure the financial elements are free cash flow, institutional ownership, Return on Assets and debt to equity ratio. The population in this research is property and real estate  companies listed in Indonesia Stock Exchange for six years (2014-2019). Election sample procedure uses purposive sampling and the result are existed 5 companies that fulfill criteria so that amount of data studied by 30 data. The results of this research show that free cash flow, institutional ownership and profitability have a significant effect on dividend policy proxied by Dividend payout ratio. Leverage which is measured by debt to equity ratio hasn’t a significant effect on dividend policy. Free cash flow has a positive effect on dividend policy. Institutional ownership has a positive effect on dividend policy. Profitability which is measured by Return on Assets has a negative effect on dividend policy. The predictive ability of these variabel on dividend policy is 49,6% as shown by the amount of R square, while 50,4% is affected by the other factor which is not included in the research model.
THE EFFECT OF FINANCIAL RATIOS ON STOCK PRICE IN LQ45 Nita Priska Ambarita
JOURNAL OF HUMANITIES AND SOCIAL STUDIES Vol. 1 No. 1 (2023): MAY 2023
Publisher : Media Inovasi Pendidikan dan Publikasi

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Abstract

The stock price is the most important thing. This study aims to determine the effect of financial performance as reflected in financial ratios on the company's stock price. The results of this study indicate that the line of business of a company can influence investor behavior which has an impact on its stock price. profitability has a significant negative effect on stock prices of the main sectors, and no significant negative effect on the manufacturing sector and the service sector (non-banking). Leverage has a significant positive effect on company stock prices in the main sectors, the manufacturing sector and the service sector (non-banking). Market Ratio has no significant positive effect on stock prices of main sector companies, significant positive on stock prices of manufacturing sector companies and a significant negative effect on stock prices of service sector companies (non-banking) and activities have no significant positive effect on stock prices of main sector companies, and negatively significant in the manufacturing and services (non-banking) sectors.
An Interdisciplinary Bibliometric Review of the Symbiotic Relationship between Business Intelligence and Artificial Intelligence Loso Judijanto; I Wayan Karang Utama; Nita Priska Ambarita; Indra Permana
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 02 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i02.183

Abstract

This research conducts an interdisciplinary bibliometric review to explore the symbiotic relationship between Business Intelligence (BI) and Artificial Intelligence (AI). Utilizing advanced bibliometric tools, we analyze a comprehensive dataset extracted from reputable databases, encompassing articles that meet predefined inclusion criteria. The study reveals thematic clusters, influential documents, and core keywords shaping the discourse within the BI-AI landscape. Thematic clusters highlight the multidisciplinary nature of research, ranging from the impact of AI on finance to business model innovation and sustainability. The top-ten cited documents provide a snapshot of seminal works guiding academic and practical understanding, while keyword analysis illuminates the central themes and areas of emphasis. The cross-analysis of these elements offers a nuanced view of the evolving landscape of BI-AI integration. The findings not only contribute to academic scholarship but also provide practical insights for organizations navigating the dynamic intersection of BI and AI.