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DAMPAK DIMENSI TANGGUNG JAWAB SOSIAL PERUSAHAAN TERHADAP PENGHINDARAN PAJAK Manich, Tesalonika Avemaria Ineari; Weli, Weli
Dinamika Akuntansi Keuangan dan Perbankan Vol 12 No 2 (2023): Vol. 12 No. 2 2023
Publisher : Faculty of Economic and Business Universitas STIKUBANK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dakp.v12i2.9760

Abstract

The purpose of this research is to analyze the impact of corporate social responsibility, as viewed from economic, environmental, and social dimensions, on tax avoidance practices. The research population comprises non-cyclical consumer sector manufacturing companies listed on the Indonesia Stock Exchange from 2018 to 2021. Data for this study were obtained from these companies' annual and sustainability reports. The research sample was selected using purposive sampling, resulting in 38 companies. Data analysis will involve Descriptive Statistical Analysis and Multiple Linear Regression Analysis using IBM Statistical Package for the Social Sciences (SPSS) version 25.0. The results of the data analysis indicate that only the variables related to the economic and environmental dimensions of corporate social responsibility impact tax avoidance practices. In contrast, social size does not influence tax avoidance practices.
Large Language Models in Accounting Tasks: Driving Factors and Ethical Dilemmas Among Accounting Students Josephine, Katherine Olivia; Tarigan, Thia Margaretha; Weli, Weli
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 01 (2026): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i01.2531

Abstract

This research aims to identify the key factors that affect accounting students’ intention to adopt and the actual usage of Large Langauge Models (LLMs), including ChatGPT, in academic contexts. It also addresses ethical concerns that may arise from their use. Using a quantitative design, data were collected through an online survey involving 302 students from various universities in the Greater Jakarta area who had prior experience using LLMs. This research aims to address the gap in literature on AI-based technology acceptance within the accounting field by extending the Technology Acceptance Model (TAM) with trust and academic ethics. The study offers a theoretical contribution by deepening insights into technology acceptance within accounting education and a practical contribution by emphasizing the integration of ethical considerations in the use of LLMs in higher education. The study focuses on key constructs including perceived ease of use, perceived usefulness, trust, academic ethics, behavioral intention, and actual usage behavior. Data was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique via SmartPLS 4 software. The results show that all examined factors positively influence students’ intention to use LLMs, with perceived usefulness stands out as the most significant driver. Furthermore, behavioral intention significantly predicts actual use, suggesting that students who see practical value in these tools are more likely to adopt them in their learning routines. What sets this research apart is its integration of motivational and ethical dimensions in examining technology acceptance within accounting education.