PERBANDINGAN METODE EUCLIDEAN DISTANCE DENGAN COEFFICIENT CORRELATION PADA KLASIFIKASI PENYAKIT MULTIPLE SCLEROSIS LESION BRAIN (MSLB)

APRIZA, DENDI and Samsuryadi, Samsuryadi (2019) PERBANDINGAN METODE EUCLIDEAN DISTANCE DENGAN COEFFICIENT CORRELATION PADA KLASIFIKASI PENYAKIT MULTIPLE SCLEROSIS LESION BRAIN (MSLB). Undergraduate thesis, Sriwijaya University.

[thumbnail of RAMA_55201_09121402019.pdf] Text
RAMA_55201_09121402019.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (2MB) | Request a copy
[thumbnail of RAMA_55201_09121402019_TURNITIN.pdf] Text
RAMA_55201_09121402019_TURNITIN.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (11MB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_01_front_ref.pdf]
Preview
Text
RAMA_55201_09121402019_0004027101_01_front_ref.pdf - Accepted Version
Available under License Creative Commons Public Domain Dedication.

Download (1MB) | Preview
[thumbnail of RAMA_55201_09121402019_0004027101_02.pdf] Text
RAMA_55201_09121402019_0004027101_02.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (385kB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_03.pdf] Text
RAMA_55201_09121402019_0004027101_03.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (299kB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_04.pdf] Text
RAMA_55201_09121402019_0004027101_04.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (677kB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_05.pdf] Text
RAMA_55201_09121402019_0004027101_05.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (237kB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_06.pdf] Text
RAMA_55201_09121402019_0004027101_06.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (11kB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_07_ref.pdf] Text
RAMA_55201_09121402019_0004027101_07_ref.pdf - Bibliography
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (131kB) | Request a copy
[thumbnail of RAMA_55201_09121402019_0004027101_08_lamp.pdf] Text
RAMA_55201_09121402019_0004027101_08_lamp.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (249kB) | Request a copy

Abstract

The detection of Multiple Sclerosis Lesion Brain (MSLB) disease in brain image segmentation has not been much studied. The Flower Pollination Algorithm is used to optimize the results of segmentation so that its value can be used for the disease classification process. The data used in this study are secondary data of 108 brain images. One technique used for classification is Template Matching, where the method is to group of objects by comparing parts of the image with other image. Template Matching method used is Euclidean Distance and Coefficient Correlation. The results showed that the classification with the Euclidean Distance method was able to achieve an accuracy of 72.2% and the Coefficient Correlation method obtained a percentage of 56.3% of 108 brain image segmentation. Euclidean Distance method is higher by 15.9%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Multiple Sclerosis Lesion Brain (MSLB), Flower Pollination Algorithm, Segmentasi, Klasifikasi, Metode Euclidean Distance, Metode Coefficient Correlation
Subjects: Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Users 3952 not found.
Date Deposited: 07 Jan 2020 07:02
Last Modified: 07 Jan 2020 07:02
URI: http://repository.unsri.ac.id/id/eprint/23207

Actions (login required)

View Item View Item