Open AccessImplementation of Text Compression using Adaptive Shannon-Fano Algorithm
Author(s) -
Satria Gunawan Zain,
Nirwana,
Andi Baso Kaswar,
Suhartono Suhartono,
Abd. Rahman Patta
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c6383.029320
Subject(s) - compression ratio , data compression , compression (physics) , character (mathematics) , computer science , algorithm , file size , data compression ratio , lossless compression , fano plane , image compression , mathematics , artificial intelligence , image processing , materials science , geometry , image (mathematics) , automotive engineering , pure mathematics , engineering , composite material , internal combustion engine , operating system
This study aims to implement the Shannon-fano Adaptive data compression algorithm on characters as input data. This study also investigates the data compression ratio, which is the ratio between the number of data bits before and after compression. The resulting program is tested by using black-box testing, measuring the number of character variants and the number of types of characters to the compression ratio, and testing the objective truth with the Mean Square Error (MSE) method. The description of the characteristics of the application made is done by processing data in the form of a collection of characters that have different types of characters, variants, and the number of characters. This research presents algorithm that support the steps of making adaptive Shannon-fano compression applications. The length of the character determines the variant value, compression ratio, and the number of input character types. Based on the results of test results, no error occurs according to the comparison of the original text input and the decompression results. A higher appearance frequency of a character causes a greater compression ratio of the resulting file; the analysis shows that a higher number of types of input characters causes a lower compression ratio, which proves that the proposed method in real-time data compression improves the effectiveness and efficiency of the compression process.