Jurnal Telematika
Vol 13, No 2 (2018)

Penerapan Metode Learning Vector Quantization untuk Mendiagnosa Penyakit Gangguan pada Lambung

Edwin Edwin (Institut Teknologi Harapan Bangsa)
Ken Ratri Retno Wardani (Institut Teknologi Harapan Bangsa)



Article Info

Publish Date
05 Feb 2019

Abstract

Iridology can prove that iris keeps information one’s health. Along with the development of technology, image processing can diagnose diseases based on iridology to detect with classification of iris image data. Disease to be studied in this research is a gastric disorder located in zone 1 according to iridology. Image processing through several preprocessing stages such as Grayscale, Gaussian Filtering, Canny edge detection, and also eye iris detection by algorithm Hough Transformation Circle. Image processing can also extract features with the help of masking. Masking is the process by which the system only focuses on the area to be detected ie the iris of the eye of the zone 1. The result of the process masking becomes input on the method of Learning Vector Quantization (LVQ) to update the value of weights at the time of learning and will be reused at the time of testing. Based on that test done, the accuracy of gastric disease detection is 0.714286 %.Ilmu iridologi dapat membuktikan bahwa iris mata menyimpan informasi kesehatan seseorang. Seiring dengan perkembangan teknologi, pengolahan citra dapat mendiagnosis penyakit berdasarkan iridologi untuk mendeteksi dengan klasifikasi data citra iris mata. Penyakit yang akan diteliti pada penelitian kali ini adalah gangguan lambung yang terletak pada zona 1 menurut ilmu iridologi. Pengolahan citra melalui beberapa tahap preprocessing seperti Grayscale, Gaussian Filtering, deteksi tepi Canny, dan deteksi iris mata dengan algoritme Hough Transformation Circle. Pengolahan citra juga dapat mengekstrasi fitur dengan bantuan masking. Masking adalah proses dimana sistem hanya berfokus pada daerah yang akan dideteksi yaitu iris mata bangian zona 1. Hasil proses masking menjadi masukan pada metode Learning Vector Quantization (LVQ) untuk melakukan pembaharuan terhadap nilai bobot pada saat pembelajaran dan akan digunakan kembali pada saat pengujian. Berdasarkan pengujian yang dilakukan, akurasi deteksi penyakit gangguan lambung mencapai 0.714286 %.

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Journal Info

Abbrev

telematika

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Description

Jurnal Telematika is a scientific periodical written in Indonesian language published by Institut Teknologi Harapan Bangsa twice per year. Jurnal Telematika publishes scientific papers from researchers, academics, activist, and practicioners, which are results from scientific study and research in ...