Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar
Vol 7 No 2 (2021): Edisi September

The Klasifikasi Jenis Ikan Berbasis Jaringan Saraf Tiruan Menggunakan Algoritma Principal Component Analysis (PCA)

Arif Lumute Unihehu (Unknown)
Imam Suharjo (Universitas Mercu Buana Yogyakarta)



Article Info

Publish Date
03 Sep 2021

Abstract

Fish are cold-blooded animals that are widely used by humans. Fish are a diverse group of poikilothermic vertebrates with more than 27,000 species worldwide. A large number of fish species becomes a problem in distinguishing the types of fish. The purpose of this study was to create a fish type classification system based on the texture of artificial neural network-based fish imagery using K-Nearest Neighbors and Principal Component Analysis (PCA) algorithms. The data was taken through direct exploration and retrieved directly by researchers. The data only uses 3 types of fish as the object of further research conducted training and testing test data in the first, second, and third classes only one can not be recognized by the system, while the other data can be recognized by the percentage of success of 93% (Ninety-three percent).

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Journal Info

Abbrev

jikom

Publisher

Subject

Computer Science & IT

Description

Computer Science Scientific Journal is published 2 (two) times in a year with the frequency of publication every 6 months in March and September. This journal contains research articles, scientific studies and social services related to Computer ...