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All Journal Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Applied Physics Letters JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Ilmiah Wahana Pendidikan International Journal of Health Science (IJHS) Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Endah Purwanti
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Journal : Indonesian Applied Physics Letters

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Identification of Stroke with MRI Images Using the Learning Vector Quantization (LVQ) Method Based on Texture Features Endah Purwanti; Lellen Novia Hariono; Suryani Dyah Astuti
Indonesian Applied Physics Letters Vol. 3 No. 2 (2022): December
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v3i2.40958

Abstract

Research on the Identification of Stroke with MRI Imagery Using the Learning Vector Quantization (LVQ) Method Based on Texture Features has been carried out. This study aims to determine the program's best parameters and the highest accuracy level of the stroke identification program. This research was conducted at Haji Sukolilo Hospital - Surabaya by obtaining 57 images of stroke patients and 15 images of regular patients. The study used the intelligence of stroke, tumor, and standard images to determine each category's image characteristics. After knowing the differences in each class, the next process is digital image processing, followed by feature extraction used is the Gray-Level Co-occurrence matrix (GLCM) with four parameters: contrast, correlation, diversity, and homogeneity. These four parameters are the best input parameters with an intelligence rate of 0.100 with a decrease in intelligence rate of 0.100, so the best accuracy value for training is 74.97%, and test data is 78.60%. Regarding the program's ability to correctly identify 11 data from 14 data tested, the program is feasible to be used as a second opinion.
Android Application for Initial Screening of Atrial Fibrillation Using The Dempster Shafer Method Rizky Widya Rachmawati; Endah Purwanti; Marcella Aurelia Yatijan; Yudi Her Oktaviono; M. Arief Bustomi
Indonesian Applied Physics Letters Vol. 4 No. 1 (2023): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v4i1.48159

Abstract

Atrial Fibrillation (FA) is one of the most common types of heart rhythm abnormalities found in clinical practice in Indonesia. Atrial fibrillation can cause a stroke risk 5 times. Meanwhile, stroke cases themselves tend to rise and become one of the main causes of death every year. The cause of the high number of FA cases is the lack of public knowledge and awareness/sensitivity to the early symptoms of the disease. The purpose of this study was to design an android device for early screening of suspected FA through examination of pulse, complaints/symptoms and disease risk factors. The dempster shafer method is used as a decision making tool for suspected FA or not FA. The results of the detection system performance test, obtained a sensitivity of 93.5%, a specificity of 89.7%, and an accuracy of 91.7%. The test results of the android application design, namely Visual Design and User Interaction, Functionality, Stability and Performance and Overall Satisfaction, show a "good" response in all aspects.
Co-Authors Ade Ragil Wibowo Adhityo Dwi Nugraha Ananda Elang Satriatama Ari Prasetyo Wibowo Ashomaji Destiana Refdy Astrida Rakhma Bekti Sukoco Brigita Suni Candra Galang Gemilang Putra Devvyta Ferika Sari Eunike Adonia Laga Frans Manangsang I Gusti Ngurah Arnold Laili Nur Hidayati, Laili Lellen Novia Hariono M. Arief Bustomi Marcella Aurelia Yatijan Mohammad Saljan Reni Rahmadewi Renona Delianna L Tobing Reyhan Bayu Pratama Rizky Widya Rachmawati Santa Sihombing Siti Asma Kuniyati Laitupa Suryani Dyah Astuti Syamsiar, Syamsiar Tegar Alwinata Masyhuda Vita Efelina Yohannes Alexander Agusti Yudi Her Oktaviono, Yudi Her