Real-Time Water Surface Obstacle Detection Using YOLOv11 and Stereo Vision on NVIDIA Jetson Orin NX
Keywords:
AI Water Surface Obstacle Detector, Computer Vision, Jetson Orin NX, Marine Navigation, YOLOv11Abstract
Introduction/Main Objectives:This research aims to investigate how digital transformation, company size, and profitability influence tax avoidance behavior in healthcare companies listed on the Indonesia Stock Exchange (IDX) between 2022 and 2024.
Background Problems: Despite post-pandemic performance growth—marked by increased revenue, asset expansion, and accelerated digitalization—the healthcare sector's average Effective Tax Rate (ETR) remains lower than the statutory corporate tax rate, indicating persistent potential for tax avoidance.
Research Methods: The study employs an associative quantitative approach using secondary data from annual financial reports. Data analysis is conducted through multiple linear regression, with the Effective Tax Rate (ETR) serving as the measure for tax avoidance.
Finding/Results: Digital transformation, company size, and profitability collectively have a significant impact on tax avoidance.Individually, digital transformation and company size show a significant effect on tax avoidance.Profitability has only a slightly significant individual effect.Digital transformation acts as a key factor in reducing tax avoidance practices.Larger companies exhibit greater scope for tax avoidance.
Conclusion: Digital transformation is an effective and significant driver in reducing tax avoidance, whereas larger company size correlates with increased potential for such practices. The findings highlight the importance of digital adoption and regulatory attention to firm scale in mitigating tax avoidance.
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