Digital humanities offers a novel approach to comprehensively understand, analyze, and interpret literary texts. This study aims to elucidate the various digital humanities methods and their implications for advancing literary studies. A systematic literature review with a descriptive-analytical approach was employed to examine digital humanities methods and analytical tools within Indonesian literature. Four primary approaches were identified: (a) digital text analysis, (b) data visualization, (c) sentiment analysis and text classification, and (d) geographic mapping. Software such as Voyant Tools and AntCont facilitate textual analysis, while Tableau and Gephi open new dimensions in visualizing narrative structures and interrelations between literary elements. Machine learning methods and natural language processing libraries enable more sophisticated sentiment analysis and text classification. In contrast, ArcGIS and Neatline expand the exploration of spatial dimensions in literary works. Digital humanities methods allow for the integration of quantitative and qualitative analyses, yielding novel insights into literary text analysis. The implementation of digital humanities methods should be studied rigidly and critically, always considering the cultural and historical contexts of Indonesian literature. Digital humanities methods should also be viewed as a complement, rather than a replacement, for established conventional approaches. The integration of digital humanities methods enriches the body of knowledge in Indonesian literary studies.
                        
                        
                        
                        
                            
                                Copyrights © 2025