Manuscript Number : IJSRST173869

Comparative Analysis of Sequitur Algorithm with Adaptive Huffman Coding Algorithm on Text File Compression with Exponential Method

Authors(5) :-Muhammad Fadlan, Surya Darma Nasution, Fadlina, Saidi Ramadan Siregar, Pristiwanto

This research was conducted to analyze and compare sequitur algorithm with the adaptive Huffman coding algorithm in compressing text file, to find which algorithm more effective and efficient in compressing compressed text file will be compared with an exponential method to be seen the performance of each algorithm based on CR, SS, RC. Text file compression will read the current string in the text file. In the Huffman adapting algorithm the text file coding will be changed into bit form, and the sequitur algorithm will change the file based on the grammar. The test result states that Huffman adapting coding algorithm is no better than sequitur algorithm.

Authors and Affiliations

Muhammad Fadlan
Research Scholar. STMIK Budi Darma, Medan, Indonesia
Surya Darma Nasution
Department of Computer Engineering, STMIK Budi Darma, Medan, Indones
Fadlina
Department of Computer Engineering, STMIK Budi Darma, Medan, Indones
Saidi Ramadan Siregar
Department of Computer Engineering, STMIK Budi Darma, Medan, Indones
Pristiwanto
Department of Computer Engineering, STMIK Budi Darma, Medan, Indones

Compression, Text file, Adaptive Huffman Coding, Sequitur, Exponential.

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Publication Details

Published in : Volume 3 | Issue 8 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 349-353
Manuscript Number : IJSRST173869
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Muhammad Fadlan, Surya Darma Nasution, Fadlina, Saidi Ramadan Siregar, Pristiwanto, " Comparative Analysis of Sequitur Algorithm with Adaptive Huffman Coding Algorithm on Text File Compression with Exponential Method", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 8, pp.349-353, November-December-2017.
Journal URL : https://ijsrst.com/IJSRST173869
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