KOMPRESI CITRA BERWARNA MENGGUNAKAN PENGGABUNGAN PARTICLE SWARM OPTIMIZATION DAN MODIFIED HARMONY SEARCH ALGORITHM
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><relation>http://repository.unsri.ac.id/1036/</relation><title>KOMPRESI CITRA BERWARNA MENGGUNAKAN PENGGABUNGAN PARTICLE SWARM OPTIMIZATION DAN MODIFIED HARMONY SEARCH ALGORITHM</title><creator>BUBUH ALHAMMADY, BUBUH</creator><creator>Saparudin, Saparudin</creator><creator>Miraswan, Kanda Januar</creator><subject>T175-178 Industrial research. Research and development</subject><subject>T57.6-57.97 Operations research. Systems analysis</subject><subject>T58.5-58.64 Information technology</subject><description>Digital image compression is a process of reducing data redundancy, so that the size of the image becomes smaller than the original. The more recent a digital image, the greater the size of the image. This certainly causes losses in the storage and transmission process because the original image requires a large amount of storage space and longer delivery times. Image compression is a way of solving problems because it can reduce the amount of data in representing a digital image. However, the reduced the size of the compressed image, the less the quality of the image. Because it requires the application of a software that can compress images and maintain image quality. In this study a software that can compress images and maintain its quality will be developed using a combination of Particle Swarm Optimization (PSO) and Modified Harmony Search Algorithm (MHSA). MHSA-PSO is a development of the Modified Harmony Search Algorithm (MHSA). MHSA-PSO uses two parameters in PSO which function to optimize the values of the MHSA parameters, namely PAR and bw. This study shows the results of good image compression and is suitable for lossy image compression.</description><date>2019-07-15</date><type>Thesis:Thesis</type><type>PeerReview:NonPeerReviewed</type><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/2/RAMA_55201_09121402012_0012046904_0009019002_01_front_ref.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/3/RAMA_55201_09121402012_0012046904_0009019002_02.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/4/RAMA_55201_09121402012_0012046904_0009019002_03.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/5/RAMA_55201_09121402012_0012046904_0009019002_04.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/6/RAMA_55201_09121402012_0012046904_0009019002_05.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/7/RAMA_55201_09121402012_0012046904_0009019002_06.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/8/RAMA_55201_09121402012_0012046904_0009019002_06_ref.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/1036/9/RAMA_55201_09121402012_0012046904_0009019002_07_lamp.pdf</identifier><identifier> BUBUH ALHAMMADY, BUBUH and Saparudin, Saparudin and Miraswan, Kanda Januar (2019) KOMPRESI CITRA BERWARNA MENGGUNAKAN PENGGABUNGAN PARTICLE SWARM OPTIMIZATION DAN MODIFIED HARMONY SEARCH ALGORITHM. Undergraduate thesis, Sriwijaya University. </identifier><recordID>1036</recordID></dc>
|
| language |
ind |
| format |
Thesis:Thesis Thesis PeerReview:NonPeerReviewed PeerReview Book:Book Book |
| author |
BUBUH ALHAMMADY, BUBUH Saparudin, Saparudin Miraswan, Kanda Januar |
| title |
KOMPRESI CITRA BERWARNA MENGGUNAKAN PENGGABUNGAN PARTICLE SWARM OPTIMIZATION DAN MODIFIED HARMONY SEARCH ALGORITHM |
| publishDate |
2019 |
| isbn |
09121402012 |
| topic |
T175-178 Industrial research. Research and development T57.6-57.97 Operations research. Systems analysis T58.5-58.64 Information technology |
| url |
http://repository.unsri.ac.id/1036/2/RAMA_55201_09121402012_0012046904_0009019002_01_front_ref.pdf http://repository.unsri.ac.id/1036/3/RAMA_55201_09121402012_0012046904_0009019002_02.pdf http://repository.unsri.ac.id/1036/4/RAMA_55201_09121402012_0012046904_0009019002_03.pdf http://repository.unsri.ac.id/1036/5/RAMA_55201_09121402012_0012046904_0009019002_04.pdf http://repository.unsri.ac.id/1036/6/RAMA_55201_09121402012_0012046904_0009019002_05.pdf http://repository.unsri.ac.id/1036/7/RAMA_55201_09121402012_0012046904_0009019002_06.pdf http://repository.unsri.ac.id/1036/8/RAMA_55201_09121402012_0012046904_0009019002_06_ref.pdf http://repository.unsri.ac.id/1036/9/RAMA_55201_09121402012_0012046904_0009019002_07_lamp.pdf http://repository.unsri.ac.id/1036/ |
| contents |
Digital image compression is a process of reducing data redundancy, so that the size of the image becomes smaller than the original. The more recent a digital image, the greater the size of the image. This certainly causes losses in the storage and transmission process because the original image requires a large amount of storage space and longer delivery times. Image compression is a way of solving problems because it can reduce the amount of data in representing a digital image. However, the reduced the size of the compressed image, the less the quality of the image. Because it requires the application of a software that can compress images and maintain image quality. In this study a software that can compress images and maintain its quality will be developed using a combination of Particle Swarm Optimization (PSO) and Modified Harmony Search Algorithm (MHSA). MHSA-PSO is a development of the Modified Harmony Search Algorithm (MHSA). MHSA-PSO uses two parameters in PSO which function to optimize the values of the MHSA parameters, namely PAR and bw. This study shows the results of good image compression and is suitable for lossy image compression. |
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Universitas Sriwijaya |
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