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Optimization of LZW Compression Algorithm With Modification of Dictionary Formation

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 12 No. 1 (2018) · pp. 73–82

DOI
10.22146/ijccs.28707
ISSN
2460-7258, 1978-1520
Published
2018-01-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

At present, the need to access the data have been transformed into digital data, and its use has been growing very rapidly. This transformation is due to the use of the Internet is growing very rapidly, and also the development of mobile devices are growing massively. People tend to store a lot of files in their storage and transfer files from one media to another media. When approaching the limit of storage media, the fewer files that can be stored. A compression technique is required to reduce the size of a file. The dictionary coding technique is one of the lossless compression techniques, LZW is an algorithm for applying coding dictionary compression techniques. In the LZW algorithm, the process of forming a dictionary uses a future based dictionary and encoding process using the Fixed Length Code. It allows the encoding process to produce a sequence that is still quite long. This study will modify the process of forming a dictionary and use Variable Length Code, to optimize the compression ratio. Based on the test using the data used in this study, the average compression ratio for LZW algorithm is 42,85%, and our proposed algorithm is 38,35%. It proves that the modification of the formation of the dictionary we proposed has not been able to improve the compression ratio of the LZW algorithm.

Keywords

Collaboration network of the authors

6 authors · 8 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Budi Luhur
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Bagas PramuditaUniversitas Budi Luhur1
Painem PainemUniversitas Budi Luhur1
Anindya Putri PradipthaUniversitas Budi Luhur1
Ludi NugrohoUniversitas Budi Luhur1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Optimization of LZW Compression Algorithm With Modification of Dictionary Formation</dc:title>
	<dc:creator>Maulunida, Restu</dc:creator>
	<dc:creator>Solichin, Achmad</dc:creator>
	<dc:subject xml:lang="en-US">Data Compression</dc:subject>
	<dc:subject xml:lang="en-US">Data Compression; Variable Length Code; Lossless; LZW</dc:subject>
	<dc:description xml:lang="en-US">At present, the need to access the data have been transformed into digital data, and its use has been growing very rapidly. This transformation is due to the use of the Internet is growing very rapidly, and also the development of mobile devices are growing massively. People tend to store a lot of files in their storage and transfer files from one media to another media. When approaching the limit of storage media, the fewer files that can be stored. A compression technique is required to reduce the size of a file. The dictionary coding technique is one of the lossless compression techniques, LZW is an algorithm for applying coding dictionary compression techniques. In the LZW algorithm, the process of forming a dictionary uses a future based dictionary and encoding process using the Fixed Length Code. It allows the encoding process to produce a sequence that is still quite long. This study will modify the process of forming a dictionary and use Variable Length Code, to optimize the compression ratio. Based on the test using the data used in this study, the average compression ratio for LZW algorithm is 42,85%, and our proposed algorithm is 38,35%. It proves that the modification of the formation of the dictionary we proposed has not been able to improve the compression ratio of the LZW algorithm.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2018-01-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/28707</dc:identifier>
	<dc:identifier>10.22146/ijccs.28707</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 73-82</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/28707/19949</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
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