Implementasi Algoritma Arithmetic Coding dan Sannon-Fano Pada Kompresi Citra PNG - Syuhada, Ibnu (Forum Kerjasama Pendidikan Tinggi (FKPT), 2022)
The rapid development of technology plays an important role in the rapid exchange of information. In sending information in the form of images, there are still problems, including because of the large size of the image so that the solution to this problem is to perform compression. In this thesis, we will implement and compare the performance of the Arithmetic Coding and Shannon-Fano algorithms by calculating the compression ratio, compressed file size, compression and decompression process speed. Based on all test results, that the Arithmetic Coding algorithm produces an average compression ratio of 62.88% and a Shannon-Fano compression ratio of 61.73%, then Arithmetic Coding the average speed in image compression is 0.072449 seconds and Shannon-Fano 0.077838 second. Then the Shannon-Fano algorithm has an average speed for decompression of 0.028946 seconds and the Arithmetic Coding algorithm 0.034169 seconds. The decompressed image on the Arithmetic Coding and Shannon-Fano algorithm is in accordance with the original image. It can be concluded from the test results that the Arithmetic Coding algorithm is more efficient in compressing *.png images than the Shannon-Fano algorithm, although in terms of decompression Shannon-Fanose is a little faster compared to Arithmetic Coding.