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.

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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

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