Endah Purwanti
Biomedical Engineering, Faculty Of Science And Technology, Airlangga University, Indonesia

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Journal : JFA (Jurnal Fisika dan Aplikasinya)

Desain Sistem Klasifikasi Kelainan Jantung menggunakan Learning Vector Quantization Endah Purwanti; Franky Chandra Satria Arisgraha; Pujiyanto Pujiyanto; Muhammad Arief Bustomi
Jurnal Fisika dan Aplikasinya Vol 9, No 2 (2013)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.44 KB) | DOI: 10.12962/j24604682.v9i2.841

Abstract

Electrocardiograph (ECG atau EKG) merupakan alat diagnosis yang mengukur dan merekam aktifitas listrik jantung. Analisis sinyal EKG sering digunakan untuk mendiagnosis beberapa jenis kelainan jantung. Pada penelitian ini, kami merancang sistem jaringan syaraf tiruan untuk klasifikasi citra elektrikardiogram. Metode pemrosesan citra digunakan untuk ekstraksi fitur citra EKG dan proses klasifikasi menggunakan learning vector quantization. Beberapa data elektrokardiogram digunakan sebagai data pelatihan dan pengujian jaringan klasifikasi. Tiga jenis kelainan jantung dapat dideteksi oleh sistem. Hasil simulasi menunjukkan bahwa akurasi algoritma klasifikasi adalah sebesar 89% yang terdiri dari 9 normal, 4 bradikardi, 8 takikardi dan 7 aritmia.
Light Spectrum Speckle Analysis in Roughness Material Identification by Using Naïve Bayes Classifier Based Equalization Histogram Adaptive Bustomi, Muhammad Arief; Utama, Edwin Widya; Purwanti, Endah
Jurnal Fisika dan Aplikasinya Vol 19, No 3 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24604682.v19i3.18482

Abstract

Speckle imaging is a method that has been used in various fields. This method can be used to analyze the surface roughness of an object. Speckle imaging uses laser light and observes speckle patterns formed from light interference on the surface. The speckle imaging method is very safe and does not require any contact so it is easy to detect the roughness of an object. In this research, two types of sandpaper were used as rough surface objects. Speckle images of the sandpaper surface were created using three laser diodes with different wavelengths, namely 405 nm, 550 nm, and 650 nm. Image processing in this research begins with pre-processing methods, image segmentation, feature extraction, and then the classification process. The feature extraction process uses an Adaptive Histogram. The classification process uses the Naïve Bayes classifier method. Based on the research results, it was found that variations in the wavelength of the light spectrum affect the results of the Adaptive Histogram image features. The accuracy of Naïve Bayes classification increases if the wavelength used in creating the speckle image is shorter. Identification accuracy increased from 92% to 96% due to the use of speckle images resulting from diode laser irradiation from 650 nm to 405 nm.