https://ejournal.uniji.ac.id/ideb <p style="text-align: justify;">Digital entrepreneurship enables entrepreneurs to leverage digital technologies to improve their organizations. In the current business landscape, many digital entrepreneurial endeavors provide interesting case studies showing innovative paths to entrepreneurship. Digital Entrepreneurial research explores new economic corridors that could provide employment opportunities, disruptive innovation, and overall economic efficiency and growth.</p> <p style="text-align: justify;">The International Journal of Digital Entrepreneurship and Business (IDEB) is an academic journal that publishes high-quality manuscripts dealing with digital entrepreneurship and digital business. IDEB provides a multi-disciplinary forum for entrepreneurs, researchers, managers, consultants, and practitioners in digital entrepreneurship. The journal includes case studies and conceptual and empirical papers that study the relationship between digital technologies and businesses to provide a better understanding of entrepreneurial approaches to doing business.</p> <p style="text-align: justify;">This journal is a premier platform for entrepreneurship and digital business researchers. Since its inception in August 2020, with subsequent editions released in February (from August 2020 to February 2023), IDEB has embraced a refined publication schedule. <strong>Since June 2023</strong>, the journal has committed to delivering insightful articles annually <strong>in April and October</strong>. In accordance with this trajectory, IDEB will <strong>exclusively publish manuscripts in the English</strong> language, extending the opportunity for authors to submit their works in the Indonesian language, with translation costs borne by the journal. Additionally, IDEB reserves the prerogative to periodically present special issues, delving into specific topics germane to its core focus. At the heart of IDEB's mission lies an unyielding dedication to publishing excellence, underscored by a steadfast adherence to elevated paper quality standards.</p> <p style="text-align: justify;">The International Journal of Digital Entrepreneurship and Business (IDEB) is available online with the following credentials:</p> <p style="text-align: justify;">Online ISSN (E-ISSN) : <a href="https://issn.brin.go.id/terbit/detail/1594785102">2723-5432</a></p> <p style="text-align: justify;">DOI (Digital Object Identifier) : <a title="DOI" href="https://doi.org/10.52238">https://doi.org/10.52238</a></p> <p style="text-align: justify;">Local Acceditation : <a title="Accreditation" href="https://sinta.kemdikbud.go.id/journals/profile/9994" target="_blank" rel="noopener">SINTA 5</a></p> <p style="text-align: justify;">Publication Language : <strong> ENGLISH</strong></p> <p style="text-align: justify;">Call for Paper (URL) : <a href="https://ejournal.jic.ac.id/ideb/announcement/">https://ejournal.jic.ac.id/ideb/announcement/</a></p> <p style="text-align: justify;">IDEB is published by <strong>Faculty of Economy and Business University of Jakarta International</strong> as publisher. </p> en-US ideb@uniji.ac.id (Liana Rahardja) sarwono.sarwono@jic.ac.id (Sarwono) Thu, 07 May 2026 10:08:10 +0700 OJS 3.2.1.1 http://blogs.law.harvard.edu/tech/rss 60 https://ejournal.uniji.ac.id/ideb/article/view/198 <p><em>This study aims to analyze the effect of financial performance, firm size, and transfer pricing on tax avoidance. This study used 19 samples of mining companies in the energy sector listed on the Indonesia Stock Exchange (IDX) during 2019 - 2023 with a total of 95 observation data. In determining the research sample, the purposive sampling method was used, with path analysis processed using SmartPLS. The results of this study state that financial performance has no effect on tax avoidance. While firm size has an effect on tax avoidance. While transfer pricing has no effect on tax avoidance. </em></p> <p><strong><em>Keywords:</em></strong><em> Financial Performance, Firm Size, Transfer Pricing, and tax avoidance</em></p> Rosa Tri Wirnarni, Nurhayati Nurhayati Copyright (c) 2025 Rosa Tri Wirnarni, Nurhayati Nurhayati https://creativecommons.org/licenses/by/4.0 https://ejournal.uniji.ac.id/ideb/article/view/198 Thu, 07 May 2026 00:00:00 +0700 https://ejournal.uniji.ac.id/ideb/article/view/292 <p>This study evaluates the performance of six machine learning models in predicting financial distress, focusing on Indonesia and comparing with other nations. Using metrics like accuracy, AUC Macro, F1 Macro, F1 Weighted, and Log Loss, we find the Random Forest model with a Standard Scaler Wrapper performs best across most metrics, while LightGBM with MaxAbs Scaler is preferred for deployment due to its robustness and scalability. We analyze feature importance of identifying key factors influencing financial distress, such as investment growth, GDP growth, and economic uncertainty. Our findings highlight the critical role of machine learning in economic forecasting and policymaking, emphasizing the importance of digital optimization and AI-driven decision-making in addressing global financial stability.</p> Syahril, Pedro J Trujillo T Copyright (c) 2026 Syahril, Pedro J Trujillo T https://creativecommons.org/licenses/by/4.0 https://ejournal.uniji.ac.id/ideb/article/view/292 Thu, 07 May 2026 00:00:00 +0700