<![CDATA[A video file is a type of file recorded or stored in a digital format that contains visual and audio data, including moving images, sound, and text. The large size of video files often causes issues in storage and data transmission, especially for long-duration videos. Storage media such as Google Drive and cloud storage are used to address storage space needs, but these solutions are often not efficient enough. Therefore, data compression techniques are required to reduce file size without losing important information. To address this issue, this research implements two data compression algorithms: Prefix Code and Burrows-Wheeler Transform. The Prefix Code algorithm uses a unique binary encoding method for each symbol in the data, while the Burrows-Wheeler Transform performs a text data transformation to produce repetitive patterns that are easier to compress. The aim of this research is to compare the effectiveness of these two algorithms in compressing video files, focusing on the parameters of Compression Ratio (CR), Ratio of Compression (RC), and Space Saving (SS). The results indicate that both algorithms are effective in compressing video files. However, a comparison between the algorithms shows significant differences in compression performance. The Prefix Code algorithm proves to be more efficient in reducing file size without compromising data quality, while the Burrows-Wheeler Transform algorithm shows advantages in maintaining data integrity during the transformation process. This analysis provides deeper insights into the effectiveness of both algorithms and can assist in choosing the most appropriate compression technique for video files.]]>
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