Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Vol 4 No 1 (2020): Februari 2020

Implementasi Metode Perceptron Untuk Pengenalan Pola Jenis-Jenis Cacing Nematoda Usus

Erni Rouza (Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Pasir Pengaraian)
Jufri (Universitas Pasir Pengaraian)
Luth Fimawahib (Universitas Pasir Pengaraian)



Article Info

Publish Date
20 Feb 2020

Abstract

The purpose of pattern recognition is do the process of classifying an object into one particular class based on the pattern it has, so it can be used to recognize patterns of intestinal nematode worm types. One of the methods used in pattern recognition is by utilizing the artificial neural network method, the artificial neural network is able to represent a complex Input-Output relationship. For that the algorithm used is the perceptron algorithm. Perceptron is one method of Artificial Neural Networks. In the introduction of types of intestinal nematode worms, a computer must be trained in advance using training data and test data, this study discusses how a computer can recognize a pattern of types of intestinal nematode worms using the perceptron method. Based on the results of testing trials with input in the form of worm image scan results, based on the results of the perceptron method testing is able to recognize the pattern recognition of the types of intestinal nematode worms and be able to analyze with the right results of 100% for pinworms patterns, hookworm patterns, and 40- 50% for roundworms, by comparing the output value and the target value entered first.

Copyrights © 2020






Journal Info

Abbrev

RESTI

Publisher

Subject

Computer Science & IT Engineering

Description

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat ...