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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Jurnal Neutrino : jurnal fisika dan aplikasinya JURNAL FISIKA JFA (Jurnal Fisika dan Aplikasinya) Jurnal Imejing Diagnostik Journal of Natural Sciences and Mathematics Research Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Jurnal Inovasi dan Pembelajaran Fisika Knowledge Engineering and Data Science Prosiding SNFA (Seminar Nasional Fisika dan Aplikasinya) MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal Teras Fisika : Teori, Modeling, dan Aplikasi Fisika Physics Education Research Journal Jurnal Fisika dan Terapannya Parta: Jurnal Pengabdian Kepada Masyarakat Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Sumarti, Heni
Jurusan Fisika, Fakultas Sains Dan Teknologi, Universitas Islam Negeri Walisongo Semarang, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Medicine & Pharmacology Physics Other

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ANALISIS PERKEMBANGAN PASIEN COVID-19 MENGGUNAKAN SEGMENTASI CITRA RONTGEN TORAKS Sumarti, Heni
JFT : Jurnal Fisika dan Terapannya Vol 7 No 1 (2020): Juni
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jft.v7i1.13858

Abstract

Chest X-ray segmentation using the contour active method has been widely carried out and produces additional information for data analysis. This information can be used to determine the development of COVID-19 patients while in the hospital. The method in this study was divided into three, first taking X-ray images of patients COVID-19, second image segmentation using the active contour method then calculating area segmentation, and third calculating the deviation area in image segmentation then analyzed. The results showed that while patient in the hospital for 1-8 days 89% of patients had  50% decrease area clean lung, whereas only 11% of patients increased clean lung repair by about 20 - 31%. Patients who have improved this condition were hospitalized in a fairly severe condition and treated for 8 days. In general, days 1-8 patients determine at the hospital is when patients get worse showed by an decrease clean lung arean more than 50%, while days 8-14 is when the patient gets better or dies.
Deteksi Tepi pada Citra Rontgen Penyakit COVID-19 Menggunakan Metode Sobel Muhammad Ghozali; Heni Sumarti
Jurnal Imejing Diagnostik (JImeD) Vol 6, No 2: JULY 2020
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jimed.v6i2.5840

Abstract

Background: Coronavirus Disease 2019 (COVID-19) discovered at the end of 2019 occasioned by coronavirus 2 (SARS-CoV-2) causing severe acute respiratory syndrome and expanded globally so that World Health Organization (WHO) declare a global pandemic. There was a delay of socialization and delivering information to society about this disease. The doctors did a method to detect COVID-19 by reading the correct X-ray images of patients who affected by a coronavirus.Methods: With advances in the field of computers in the application of image processing techniques method of this research use application to get better digital image results for COVID-19 X-ray images, so make it easier to analyze the X-ray images. There are 13 samples of X-ray images that are processed through the clean the stage with high-pass filtering, then segmented with thresholding technique in the lung area, then the edge detection method is used to mark the area that makes the image detail.Results: The result of this detection form the pattern of objects and regions of the spread of coronavirus, then there is a limit on the image looks clear enough, with the Sobel method producing white pixels that are so visible as well.Conclusions: This study to make a simulation of x-ray thorax COVID-19 and know the region of virus infection using Sobel method with thresholding technique that can see the spread of coronavirus and shown that edge detection use Sobel method as one of diagnosing for COVID-19 disease.
Analysis of chest X-Ray (CXR) images in COVID-19 patients based on age using the Otsu thresholding segmentation method Uhty Maesyaroh; Laelatul Munawaroh; Heni Sumarti; Rico Adrial
Journal of Natural Sciences and Mathematics Research Vol 7, No 2 (2021): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.2021.7.2.10891

Abstract

The infection with the COVID-19 virus or better known as the Corona virus spread throughout China and other countries around the world until it was designated a pandemic by the World Health Organization (WHO). Detection of patients infected with COVID-19 in the form of RT-PCR, CT-Scan images and Chest X-Ray (CXR). This study aims to analyze CXR images of COVID-19 patients based on age using Otsu Thresholding Segmentation. The image segmentation process uses the Otsu auto-tresholding method to separate objects from the background on the CXR image. The results show that the images of COVID-19 patients have pneumonia spots that are not visible on the original CXR image. The average value of the accuracy of the Otsu Thresholding results is 95.18%. Penunomia spots are mostly found in COVID-19 patients aged 50 to 70 years and over which cause severe lung damage.©2021 JNSMR UIN Walisongo. All rights reserved.
Classification of Pneumonia in Thoracic X-Ray images based on texture characteristics using the MLP (Multi-Layer Perceptron) method Latifatul Istianah; Heni Sumarti
Journal of Natural Sciences and Mathematics Research Vol 6, No 2 (2020): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.2020.6.2.11228

Abstract

One of the diseases that attack the lungs is pneumonia. This disease can attack someone with a weak immune system. Pneumonia is inflammation of the lungs that can be caused by pathogens, such as bacteria, viruses, and fungi. The purpose of this study was to classify fungal pneumonia, bacterial pneumonia, and lipoid pneumonia based on texture characteristics and the MLP method using machine learning WEKA. The method in this study has three stages including pre-processing, extraction of texture features consisting of Histogram and GLCM, and classification using the MLP (Multi Layer Perceptron) method. The results of the texture feature extraction showed that the three types of pneumonia were: lipoid pneumonia with brightness, sharp contrast random distribution on correlation characteristics, bacterial pneumonia with high brightness, high contrast random distribution on energy characteristics, and fungal pneumonia with brightness, sharp contrast, random distribution of homogeneity attributes. The third similarity of pneumonia is in the gray level that collects each other in the middle. The method used in this study resulted in the same accuracy, sensitivity, and specificity, namely 100%. The image classification in this study shows the success of the texture features and the MLP method in classifying pneumonia images accurately so that they can be used as additional tools that make it easier for medical experts.   ©2020 JNSMR UIN Walisongo. All rights reserved. 
Analysis of Axial CT-Scan image of COVID-19 patients based in gender using the Otsu Thresholding method Melany Puspa Damayanti; Heni Sumarti
Journal of Natural Sciences and Mathematics Research Vol 6, No 1 (2020): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.2020.6.1.11152

Abstract

At the beginning of 2020, the world was shocked by the emergence of the COVID-19 virus. This virus has spread to all corners of the world, not only in Indonesia. Therefore, the government needs to make efforts to break the chain of transmission of this virus. One of these efforts is to detect COVID-19 as early as possible. Using CT images can be one of the early detection efforts of early-phase lung infections in COVID-19 patients. The stage in detecting COVID-19 is by segmenting the image. In this study, segmentation was carried out using the Otsu Thresholding method on 8 axial CT images of the lungs of COVID-19 patients, consisting of 4 images of male patients and 4 images of female patients. Then the image segmentation results of male and female patients were compared and evaluated using ROC measurements, Threshold (T) values and analyzed for GGO (grand-glass opacity). The result can be seen that judging from the value of the ROC measurement results, the measurement of image segmentation evaluation of male patients is more accurate than female patients. The number of false negatives for male patients and female patients is the same, while the number of false positives for male patients is less than female patients. Threshold value of the image segmentation results of male and female patients is the same so that the density of image segmentation is the same. GGO (grand-glass opacity) for male COVID-19 patients aged between 45-55 years is fuller than female COVID-19 patients aged 45-55 years. This shows that men are more at risk of dying from COVID-19 than female.©2020 JNSMR UIN Walisongo. All rights reserved.
PENGEMBANGAN ALAT UKUR KADAR GULA DARAH SECARA NON-INVASIVE MENGGUNAKAN SENSOR TCRT5000 UNTUK MENGURANGI LIMBAH MEDIS Tria Nurmar’atin; Ayu Wulandari; Heni Sumarti
JURNAL INOVASI DAN PEMBELAJARAN FISIKA Vol 9, No 1 (2022): JURNAL INOVASI DAN PEMBELAJARAN FISIKA
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jipf.v9i1.15444

Abstract

Diabetes Mellitus merupakan penyakit berat yang banyak diderita oleh orang sedunia. Sangat penting bagi penderita diabetes untuk selalu memantau kadar gula darah agar tetap berada pada kisaran normal. Pemeriksaan kadar gula darah secara invasive dapat menimbulkan ketidaknyamaan dan menambah tumpukan limbah medis, sehingga perlu dikembangkan alat pemantaua kadar gula darah secara non-invasive (tanpa melukai tubuh) dengan biaya rendah dan mengurangi limbah medis. Sistem deteksi kadar gula darah non-invasive yang dikembangkan dalam penelitian ini memanfaatkan serapan sinar Near Infra-Red (NIR) menggunakan sensor TCRT5000. Kalibrasi alat dengan membandingkan hasil pengukuran alat ini dengan alat ukur standar pada 10 sampel acak menghasilkan koefisien determinasi 0.99 yang menunjukan hubungan linear yang sangat kuat. Pengujian alat pada 30 sampel menghasilkan nilai akurasi alat sebesar 97.71%. Alat ini dapat digunakan sebagai instrumen alternatif untuk mengukur kadar gula darah karena memiliki nilai akurasi diatas ambang alat medis yang bisa digunakan manusia yaitu ? 95%.
Implementasi prototype deteksi gejala dini Covid-19 berbasis NodeMCU ESP8266 pada usia lanjut Putri Diah Pitaloka; Heni Sumarti; Firman Hardianto
Jurnal Teras Fisika: Teori, Modeling, dan Aplikasi Fisika Vol 5 No 1 (2022): Jurnal Teras Fisika: Teori, Modeling, dan Aplikasi Fisika
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jtf.2022.5.1.5173

Abstract

Pada awal tahun 2020, dunia dihadapkan dengan wabah pneumonia baru yang muncul dari Kota Wuhan dan menjadi pandemi karena menyebar dengan cepat ke 190 negara salah satunya adalah Indonesia. Wabah ini dikenal sebagai Coronavirus Disease 2019 (Covid-19). Banyak upaya yang telah dilakukan untuk mencegah penularan Covid-19 seperti pembatasan sosial berskala besar (PSBB) sampai pengecekan suhu yang banyak dijumpai di beberapa tempat. Namun, sampai saat ini belum ada alat yang menerapkan tiga parameter yang dapat ditinjau sebagai pemeriksaan awal Covid-19 (suhu, denyut jantung dan saturasi oksigen). Penelitian ini bertujuan untuk mengembangkan alat deteksi dini Covid-19 yang dapat digunakan untuk mengukur tiga parameter dalam satu alat terpadu dan menjelaskan hasil implementasinya pada usia lanjut. Penelitian ini menggunakan metode Research and Development (RnD) dengan tahapan yang dilakukan meliputi tahap perancangan, pembuatan, dan pengujian. Analisis data dilakukan dengan pengujian akurasi, yakni membandingkan dengan alat standar. Hasil akurasi pada pegukuran suhu adalah sebesar 98.38%, denyut jantung sebesar 95.1% dan saturasi oksigen sebesar 98.8%. Alat yang telah dikembangkan berfungsi dengan baik dan dapat digunakan sebagai alat ukur standar karena tingkat akurasinya di atas 95%. Berdasarkan implementasi deteksi gejala dini Covid-19, maka disimpulkan bahwa responden dalam keadaan sehat dan tidak terjangkit Covid-19.
The analysis of differences at Binary Image in COVID-19 and ARDS Patients from chest X-Ray examination Syntia Anggraeni; Siska Nuryani; Heni Sumarti; Samuel Gideon
Journal of Natural Sciences and Mathematics Research Vol 8, No 1 (2022): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.2022.8.1.10890

Abstract

Corona virus disease 2019 (COVID-19), a viral infection that was discovered at the end of December 2019 in Wuhan, China. The spread and transmission of this virus is very fast even to all countries in the world. Meanwhile, Acute Respiratory Distress Syndrome (ARDS) is an emergency condition in the field of pulmonology that occurs due to fluid accumulation in the alveoli causes gas exchange disorders so that oxygen distribution to tissues were reduced. In this study, Chest X-Ray (CXR) image processing done in COVID-19 and ARDS patients with the aim of analyzing the differences in binary image using the Otsu Thresholding method. This study prioritizes improving the quality of the original CXR image by segmentation using calculating the Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MSE) values. The results showed that the difference between CXR images in COVID-19 patients and ARDS lies in the extent of spread, in COVID-19 patients the extent of spread varies depending on the length of time the virus has invaded and not all of it starts from the alveolus, while ARDS tends to be constant and starts from the lungs. The lower part of the lung, specifically the alveoli. ©2022 JNSMR UIN Walisongo. All rights reserved.
ANALISIS DAMPAK PUASA SENIN KAMIS TERHADAP KADAR KOLESTEROL DALAM DARAH MENGGUNAKAN ALAT UKUR NON-INVASIF BERBASIS ARDUINO UNO Muhammad Labib; Farah Alfiana Na’ila; Lailiyatu Latifah; Heni Sumarti
JFT : Jurnal Fisika dan Terapannya Vol 9 No 1 (2022): JUNI
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jft.v9i1.25745

Abstract

Excessive cholesterol in the blood can have an impact on health, causing various deadly diseases. Fasting Monday and Thursday is one solution in lowering cholesterol levels in the blood apart from our main reason for worshiping Allah SWT. The purpose of this study was to determine the effect of fasting on Mondays and Thursdays on cholesterol levels in the blood using a non-invasive cholesterol level measuring instrument based on Arduino Uno. The method used is the Research and Development (R&D) method. The results showed that the non-invasive measuring instrument had an accuracy of 97.02%, so it was feasible to be used as a medical measuring instrument. Analysis of six respondents who did fasting Monday and Thursday shows a linear tendency to decrease cholesterol levels with an average coefficient of determination of 0.3282.
ANALYSIS OF THE EFFECT OF ISTIGHFAR DHIKR TO ADOLESCENT ANXIETY AT BETA WAVE ACTIVITY USING ELECTROENCEPHALOGRAM (EEG) EXAMINATION Alvania Nabila Tasyakuranti; Heni Sumarti; Hamdan Hadi Kusuma; Istikomah Istikomah; Irman Said Prastyo
Jurnal Neutrino:Jurnal Fisika dan Aplikasinya Vol 15, No 1 (2022): October
Publisher : Department of Physics, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/neu.v15i1.17270

Abstract

Information related to deviants in the near future is often the case by a group of adolescents. Behavior that deviates from anxiety because of a problem in daily life. One way that is taught by Islam by listed in the Qur'an and hadith to reduce anxiety in a person is to do istighfar dhikr. Knowing the beta brain wave activity in anxiety and istighfar dhikr condition can be done using an EEG (Electroencephalogram). Beta waves are brain waves that are detected when a person feels anxious. Beta wave measurement method is calculated based on peaks or troughs per second on the beta signal type frequency (13-30Hz). The method in this research is an experiment with quantitative data collection. The sample used in this study were 8 students in Universitas Islam Negeri Walisongo Semarang with an age range of 20-23 years. The data analysis technique used is bivariate with Paired T-test. The results showed that the average beta wave in anxiety condition was 14.213 Hz and istighfar dhikr was 13.085 Hz. The result of the Paired t-test showed that p = 0.002 (p 0.05) indicating that the decrease in beta waves in the brain is very significant. It shows that istighfar dhikr can reduce anxiety in adolescents.
Co-Authors Adrial, Rico Affa Ardhi Saputri Affa Ardhi Saputri Agus Sudarmanto Alvania Nabila Tasyakuranti Alvania Nabila Tasyakuranti Alvnia Nabila Tasyakuranti Anggita, Sheilla Rully Arifah Riana AYU WULANDARI Azzahra, Jannatul Firdausa BELLA JULIA Edi Daenuri Anwar Edison, Rizki Edmi Fachrizal Rian Pratama Fahira Septiani Fahira Septiani Farah Alfiana Na’ila Fariyani, Qisthi Fina Mushoffa Firman Hardianto Gideon, Samuel Hadi Kusuma, Hamdan Hamdan Hadi Kusuma Hamdan Hadi Kusuma HAMDAN HADI KUSUMA Hamdan Hadi Kusuma Hani Nur Endah Hartono Hartono Huwaidah, Indah Rifdah Irman Said Prastyo Irman Said Prastyo Istikomah Istikomah Istikomah Istikomah Istikomah Istikomah Kholidah Kholidah, Kholidah Laelatul Munawaroh Lailiyatu Latifah Latifatul Istianah Maesyaroh, Uhty Maya Shofani Melany Puspa Damayanti Muhammad Ghozali Muhammad Labib Muhammad Syafiul Huda Nurul Embun Isnawati Nuryani, Siska Putri Diah Pitaloka Qolby Sabrina, Qolby Rahmani, Tara Puri Ducha Rahmawati, Aida Samuel Gideon Sari, Ice Uliya Septiani, Fahira Sheilla Rully Anggita Sheilla Rully Anggita Siska Nuryani Susilawati Susilawati Syntia Anggraeni Tasyakuranti, Alvania Nabila Tika Rahmawati Tria Nurmar’atin Triana, Devi Uhty Maesyaroh Wahyu Caesarendra