Background: Digital media has changed the practice of investigative journalism significantly, particularly in exposing corruption by public officers. Digital platforms have been built to enhance access to information and to involve the public. Purpose: The objective of this study is to examine the role of digital investigative journalism in exposing corruption from the perspective of digital media, public pressure and institutional accountability. Methods: This research employs qualitative method through literature study and instrumental case study in corruption case of Rafael Alun Trisambodo. The data were collected by analysis of documents of scientific literature, research reports and digital media sources. Results: The results of this study show that digital investigative journalism can accelerate the accumulation of evidence and improve the capability to set the agenda in the construction of public discourse. The intersection of open source intelligence, AI and big data facilitates journalists to better find obscure patterns and networks, while crowd-based investigations offer citizens a better chance to find corruption. We can observe that, in the analyzed cases, digital media also play an important role in the transformation of social events into opportunities for uncovering corruption. Misinformation, cyber attacks, issues of ethics, and gaps in online literacy can have dire consequences for the credibility of the research process. Conclusion: The case of Rafael Alun Trisambodo shows the power of investigative journalism, social media activism and public demand in the digital era to reveal corruption. The results demonstrate how digital media can transform non-corruption events into an opportunity to expose corruption and institutional accountability. Implications: Investigative journalism has improved transparency, accountability, and democratic oversight. It additionally emphasizes the need for ethical standards, mechanisms for verification and improved online literacy which are critical to the sustainability and reliability of digital research practices.