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All Journal JURNAL FISIKA JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Journal of Soft Computing Exploration Abdi Masya Abdi Teknoyasa Journal of Multiscale Materials Informatics
Diah Rahayu Ningtias, Diah Rahayu
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Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Other

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Utilization of Spiking Neural Network (SNN) in X-Ray Image for Lung Disease Detection Ningtias, Diah Rahayu; Rofi’i, Mohammad; Pramudita, Brahmantya Aji
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.10671

Abstract

The large number of cases of lung disease means that doctors have difficulty in making initial diagnoses, making them prone to misdiagnoses. One type of lung disease that is included in the vulnerable category is pneumonia. Early detection of the condition of the lungs affected by bacterial pneumonia can be carried out by screening using the X-Ray examination modality, namely Digital Radiography (DR). However, in practice, the diagnosis process on Citra DR takes a long time because it requires competent medical personnel (specialists). A system is needed that can help medical personnel to speed up the process of diagnosing lung disease and get accurate results so that misdiagnosis does not occur. The aim of this research is to utilize the Spiking Neural Network (SNN) method for classifying lung disease from DR images. The system was created using MATLAB with the initial step of creating a read data program, namely reading DR image secondary data in .jpg format taken from Kaggle.com. This research uses DR image data totaling 200 images. Next, standardize the size to 50 x 50 pixels. Then segmenting the image divides the gray level histogram into two different parts of the image automatically without requiring user assistance to enter threshold values ​​for normal and pneumonia images. Then convert the image to 1 dimension and create a manual program for the training data using 50 normal images and 50 pneumonia images. Lastly, create a program to test the data using 100 normal images and 100 pneumonia images. Based on the results of data testing, a confusion matrix was obtained from 200 images with sensitivity of 87%, specificity of 69%, precision of 73.7288%, recall of 69%, and accuracy of 78%
Pengaruh Duty Cycle terhadap Nilai Heart Rate pada Pengujian Alat Fetal Simulator Berbasis Arduino Ningtias, Diah Rahayu; Harsoyo, Imam Tri; Aulia, Andika
Jurnal Fisika Vol 11, No 1 (2021)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v11i1.29378

Abstract

Fetal simulator merupakan phantom sekaligus kalibrator yang digunakan untuk kegiatan kalibrasi fetal doppler, yang bekerja sebagai pengganti detak jantung janin. Fetal simulator pada umumnya menggunakan relay sebagai generator sinyal. Kecepatan posisi on dan off relay yang dimodifikasi untuk menghasilkan rentang frekuensi yang dapat dialirkan ke jantung janin di jaringan lunak yang terdeksi oleh fetal doppler. Fetal simulator dibuat menggunakan oli trafo untuk meredam noise. Sebagai alat uji untuk mengetahui keakuratan dan kestabilan nilai heart rate fetal simulator digunakan alat fetal doppler tipe ultrasonic pocket doppler Sonotrax merk EDAN yang sudah dikalibrasi. Fetal simulator disetting pada nilai heart rate secara berturut turut yaitu 30 bpm, 60 bpm, 80 bpm, 90 bpm, 120 bpm, 150 bpm, 180 bpm, 210 bpm dan 240 bpm. Rata rata error pada alat fetal simulator adalah 0,082 bpm, dengan demikian dapat dinyatakan alat memiliki akurasi dan kestabilan tinggi. Nilai duty cycle didapatkan dengan menghubungkan generator penghasil pulsa heart rate pada osiloskop. Berdasarkan pengamatan yang telah dilakukan, dalam satu gelombang periode mati relay yang didapatkan semakin berkurang seiring bertambahnya nilai heart rate. Hal ini dikarenakan terjadi pergeseran periode mati relay namun periode hidup relay cenderung tetap, sehingga didapatkan nilai duty cycle yang berbeda-beda.
Pemeliharaan Alat Centrifuge Dan Ultrasonic Scaler Dental di Rsud Dr. Soewondo Kendal Harsoyo, Imam Tri; Kusumaningtyas, Pramesti; Wahyudi, Bayu; Ningtias, Diah Rahayu
Abdi Teknoyasa Volume 5, No. 1, Juli 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/abditeknoyasa.v5i1.5603

Abstract

Sesuai dengan Permenkes no.15  tahun 2023 bahwa kegiatan pemeliharaan alat kesehatan pada fasilitas pelayanan kesehatan bertujuan untuk menjamin tersedianya alat kesehatan sesuai dengan standar pelayanan, persyaratan mutu, keamanan, manfaat, keselamatan dan laik guna mendukung penyelenggaraan pelayanan kesehatan yang aman dan bermutu. Tujuan dari kegiatan pengabdian masyarakat yang dilakukan adalah untuk membantu pihak IPSRS RSUD Dr. Soewondo Kendal dalam melaksanakan kegiatan manajemen pemeliharaan peralatan elektromedik. Dalam penyelenggaraan kegiatan pemeliharaan, diketahui bahwa terdapat unit centrifuge dan ultrasonic scaler dental yang mengalami kerusakan. Trobleshooting alat dilakukan dengan mencari sumber kerusakan kemudian memperbaiki kerusakan tersebut. Informasi kerusakan digali dengan wawancara dengan user, kemudian dilakukan cek fisik, cek kelistrikan dan uji fungsi. Dari proses tersebut diketahui bahwa kerusakan centrifuge terjadi pada rangkaian dimmer dan motor universal, sedangkan pada dental scaler kerusakan terdapat di trafo osilator dan selenoid valve. Setelah dilakukan langkah perbaikan dan uji fungsi, alat harus tetap dikalibrasi oleh pihak yang berwenang agar kelaikan alat dapat dipastikan. Hasil akhir dari PKM ini menunjukan adanya peningkatan usia pakai peralatan elektromedik untuk menunjang pelayanan kesehatan di RSUD Dr. Soewondo Kendal.  
Developing a classification system for brain tumors using the ResNet152V2 CNN model architecture Rhomadhon, Syahruu Siyammu; Ningtias, Diah Rahayu
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.372

Abstract

According to The American Cancer Society, in 2021 there were 24,530 cases of brain and nervous system tumors. The National Cancer Institute reports that there are approximately 4.4 new cases of brain tumors per 100,000 men and women per year. Brain tumors can be detected using magnetic resonance imaging (MRI), a scanning tool that uses a magnetic field and a computer to record brain images and is able to provide clear visualization of differences in soft tissue such as white matter and gray matter. However, this cannot be done optimally because it still relies on manual analysis, so it cannot classify brain tumor types on larger datasets with the potential for error and a low level of accuracy. To accurately determine the type of brain tumor, a better classification method is needed. The aim of this study is to determine the accuracy of brain tumor calcification using the deep learning model. In this study, the classification of brain tumor types was carried out using the ResNet152V2 convolutional neural network (CNN) model which has a depth of 152 layers. The dataset used in this study was 7,023 MRI images of brain tumors consisting of 1,645 meningiomas, 1,621 gliomas, 1,757 pituitary and 2,000 normal. Research results show an accuracy value of 94.44%, so it can be concluded that the ResNet152V2 model performs well in classifying brain tumor images and can be used as a medium for physicians to more accurately diagnose brain tumor patients more accurately.
Utilization of eye tracking technology to control lights at operating room Permana, Asyraf; Ningtias, Diah Rahayu
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.502

Abstract

The development of technology for control systems is increasing, especially to help people with disabilities and facilitate the performance of health workers. Where it is required to maintain the level of sterilization of equipment in hospitals. Eye tracking technology in the last few decades has developed very rapidly. This control system using eye tracking technology can be done with eye movements for those who experience mobility problems. This research aims to develop a light control system through eye activity using the Mediapipe framework from Google. In this study, 2 lamps (A and B) were used, each with a light intensity of 10W. In lamp A, the light intensity can be controlled by turning the light on or off using the blink of the right eye and the blink of the left eye, while lamp B can adjust the intensity of the light by opening both eyes (right and left). Research on a lighting control system using the eye tracking method with an image processing system has been successfully carried out. All data generated is based on activity, distance, eye position on the camera and differences in participant backgrounds. Apart from that, a system that can work well means consistent results are obtained. However, based on distance, the system can read with precision at distances of 50 cm and 60 cm.
XGBoost performance in predicting corrosion inhibition efficiency of Benzimidazole Compounds Ningtias, Diah Rahayu; Akrom, Muhamad
Journal of Multiscale Materials Informatics Vol. 1 No. 2 (2024): October
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v1i2.11021

Abstract

In this study, we compare the performance of the XGBoost model with a Support Vector Machine (SVM) model from the literature in predicting a given task. Performance metrics such as the coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE) were utilized to evaluate and compare the models. The XGBoost model achieved an R² of 0.99, an RMSE of 2.54, and an MAE of 1.96, significantly outperforming the SVM model, which recorded an R² of 0.96 and an RMSE of 6.79. The scatter plot for the XGBoost model further illustrated its superior performance, showing a tight clustering of points around the ideal line (y = x), indicating high accuracy and low prediction errors. These findings suggest that the XGBoost model is highly effective for the given prediction task, likely due to its ability to capture complex patterns and interactions within the data.
MONITORING KUALITAS AIR BERBASIS IoT (INTERNET OF THINGS) UNTUK MENINGKATKAN PRODUKTIVITAS NELAYAN DI KABUPATEN DEMAK Ningtias, Diah Rahayu; Rofi’i, Mohammad; Zulfa, Nely
Abdi Masya Vol 5 No 2
Publisher : Pusat Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52561/abdimasya.v5i2.406

Abstract

Pond farmers in Demak Regency, especially in Tambakbulusan Village, face challenges in maintaining the optimal quality of brackish water ponds. Uncontrolled fluctuations in temperature, pH, and salinity hurt the growth of brackish water biota, including shrimp and milkfish. Therefore, it is necessary to develop technology and innovation, such as an IoT (Internet of Things)-based water quality monitoring tool that allows farmers to monitor pond conditions in real time from a distance. This monitoring uses a website that is integrated with localhost so that special treatment can be carried out more quickly. In making this IoT-based monitoring tool, pH, temperature, and salinity levels were tested. The results obtained were that the pH, salinity, and temperature levels in pond water were still within normal limits. Community service activities in Tambakbulusan Village, Karangtengah District, Demak Regency have succeeded in increasing the productivity of brackish water pond farmers for milkfish and shrimp. In the future, it is hoped that there will be follow-up activities, namely the addition of fresh water when there is an increase in salinity levels in brackish water ponds automatically, so that the community feels more helped.
Co-Authors Akrom, Muhamad Aulia, Andika Bayu Wahyudi Brahmantya Aji Pramudita Harsoyo, Imam Tri Kusumaningtyas, Pramesti Permana, Asyraf Rhomadhon, Syahruu Siyammu Rofi’i, Mohammad S. Susilo, S. Sutikno Madnasri zulfa, nely