This video is a recording of a thesis research seminar by Arief Purnama Muharram (Student ID: 23521013), a Master's student in Informatics at the School of Electrical Engineering and Informatics, Bandung Institute of Technology. The seminar was held on Monday, May 20, 2024, from 1:00 PM to 2:00 PM WIB. It discusses the application of Natural Language Inference (NLI) and Knowledge Graphs (KG) in validating COVID-19 information in Indonesian language. The widespread misinformation on the Internet has driven the development of automated fact-checking systems to address this issue. Typically, these systems use the NLI approach to verify the truthfulness of claims based on existing evidence. However, the performance of NLI models often plateaus due to a lack of specific contextual knowledge during model training. This research introduces the use of KG in conjunction with NLI to enhance model performance in validating COVID-19 information in Indonesian. Additionally, KG aims to make the model more aware of current knowledge. If you have any questions regarding this research, please feel free to reach out via email at ariefpurnamamuharram@gmail.com. Note that the Q&A session from the seminar was not recorded. Note: This research received feedback and underwent significant revisions after the seminar. The final results of the research can be accessed at https://arxiv.org/abs/2409.00061.