<![CDATA[Technology is developing very quickly and will continue to increase, so it plays an important role in the process of sending information or data from one device to another. The speed of transmission depends on the size of the data to be sent. Data with a larger size requires a longer delivery time. The amount of storage space required increases as more files are stored. This has led to the development of file shrinking techniques, also known as data compression techniques, with the aim of minimizing the loss of data quality after transmission and reducing the amount of storage space required. Compression techniques have several algorithms that can be used to reduce file size. As in this research, the compression process is done with the run length encoding algorithm and the fixed length binary encoding algorithm. Both algorithms have different compression results, so it is necessary to make a comparison. To make the comparison, 6 grayscale image files with *.jpg extension are used with different resolutions and compare their performance according to predetermined parameters. The compression comparison results of one image data resolution of 300 x 300 in the Run Length Encoding algorithm has a Ratio of Compression (RC) 1.038792, Compression Ratio (CR) 96.266%, Redundancy (Rd) 3.734%, Compression time 399ms, and Decompression time 297ms. While the Fixed Length Binary Encoding algorithm has a Ratio of Compression (RC) of 1.37, Compression Ratio (CR) of 73.248%, Redundancy (Rd) of 26.752%, Compression time of 3258ms, and Decompression time of 1047ms. So from these results it can be said that the better performance in compressing images is the Fixed Length Binary Encoding algorithm compared to Run Length Encoding.]]>
