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All Journal JURNAL FISIKA JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Elektrika Journal of Soft Computing Exploration Abdi Masya Jurnal EduHealth 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 Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Veterinary 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

Petani tambak di kabupaten Demak khususnya di Kelurahan Tambakbulusan menghadapi tantangan dalam menjaga kualitas air tambak air payau secara optimal. Fluktuasi suhu, pH, dan salinitas yang tidak terkontrol dengan baik memberikan dampak negatif pada pertumbuhan biota air payau, yaitu meliputi udang serta bandeng. Oleh sebab itu diperlukan pengembangan teknologi dan inovasi misalnya alat monitoring kualitas air berbasis IoT (Internet of Things) memungkinkan petani untuk memantau kondisi tambak secara real-time dari jarak jauh. Pemantauan ini menggunakan website yang terintegrasi dengan localhost sehingga memungkinkan perlakukan khusus secara lebih cepat. Pada pembuatan alat monitoring berbasis IoT ini dilakukan uji tingkat pH, suhu, dan salinitas. Hasil yang didapatkan adalah tingkat pH, salinitas, dan suhu pada air tambak sejauh ini masih dalam batas normal. Kegiatan pengabdian kepada masyarakat di Kelurahan Tambakbulusan, Kecamatan Karangtengah, Kabupaten Demak ini telah berhasil meningkatkan produktivitas petani tambak air payau untuk bandeng dan udang. Kedepan diharapakn terdapat kegiatan lanjutan yaitu penambahan air tawar ketika terjadi kenaikan kadar salinitas di tambak air payau secara otomatis, sehingga masyarakat lebih merasa terbantu.
Identification of lung cancer using gray level co-occurrence matrix (GLCM) and artificial neural network with backpropagation algorithm Fauziah, Haniifah Hana; Ningtias, Diah Rahayu; Wahyudi, Bayu; Simanjuntak, Josepa ND
Journal of Soft Computing Exploration Vol. 6 No. 1 (2025): March 2025
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v6i1.543

Abstract

Air pollution is a problem that occurs in various countries, including Indonesia. One of the consequences of poor air quality due to air pollution is health problems in the lungs, one of which is lung cancer. According to WHO data, lung cancer caused 1.80 million deaths in 2020. This is due to limited services to identify lung cancer early, resulting in delays in treatment. This study aims to identify lung cancer using CT-Scan image processing. The identification method uses a Backpropagation Artificial Neural Network (ANN BP) with Gray Level Co-occurrence Matrix (GLCM) feature extraction. Preprocessing is carried out to improve image quality by removing noise using a median filter. Segmentation of preprocessing results using Otsu threshold. Texture features from segmentation can be calculated from the resulting GLCM, such as Angular Second Moment (ASM)/energy, contrast, correlation, Inverse Different Moment (IDM)/homogeneity, and entropy. These values ​​are obtained from angles of 0°, 45°, 90°, and 135°, and a distance between pixels of 2 pixels. Identification using ANN with Backpropagation algorithm. This study used images of normal lungs and lung cancer with 160 training data images and 40 test data images. The best test results were obtained with the best accuracy level of 92.5%.
Analysis of the Effects of Variation of Phantom Diameter on Radiation Dose on Image Dicom CT Scan Using IndoseCT Andriani, Intan; Budiwati, Trisna; Ningtias, Diah Rahayu
Jurnal EduHealth Vol. 13 No. 01 (2022): Jurnal EduHealth, April - September 2022
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (316.434 KB)

Abstract

CT-Scan is one of the imaging modalities in the field of radiodiagnostics that can produce axial, coronal, and sagittal slices of the object or patient performing the examination. CT-Scan can be applied to diagnose trauma in cancer cases. The use of CT-Scan aircraft certainly provides a fairly large radiation dose compared to other diagnostic imaging modalities (Bushberg, 2012). This study aimed to determine the effect of the thickness (diameter) of the object on the radiation dose. This study's benefit is providing accuracy in receiving the body's absorbed dose on CT-Scan examination. This research is experimental. The study used a sample of 5 phantoms with variations in the diameter of 8 cm, 16 cm, 24 cm, 32 cm, and 40 cm. The data is obtained from the phantom scan results, which are inputted into the IndoseCT program. The data generated by IndoseCT will be analyzed regarding the amount of radiation dose received by each phantom size. The final result expected from this research is the evaluation of measurement or monitoring of doses to patients who can support radiation protection programs in ensuring patient safety.
RANCANG BANGUN BANTAL TERAPI BERBASIS ARDUINO Ningtias, Diah Rahayu; Sudarma, Made Putra; Harsoyo, Imam Tri
Elektrika Vol. 11 No. 2 (2019): Oktober 2019
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/elektrika.v11i2.1706

Abstract

One form of physiotherapy is utilizing heat for recovery. Heat therapy can open blood vessels wider, thereby increasing blood flow and supply of oxygen and nutrients to reduce pain in joints, muscles, ligaments and injured tanks. To help health services in the field of physiotherapy the author modifies the therapeutic pillow with Arduino Uno and DS18B20 based as a temperature sensor, LCD as a temperature viewer and a timer and button that functions to choose how long it takes to do therapy. The design of therapeutic pillows is divided into two, namely hardware and software design, hardware design including power supply, a series of drivers and system scenarios. While the software design of this tool uses the Arduino and proteus applications as software. The result of the percentage error at the TP2 measurement is 0.02%. The measurement results on TP3 when the tool is off or off, then the circuit does not get a voltage while when the device is turned on or on the driver circuit gets a voltage of 1.4 Volt. After making the process of making, testing, testing tools and data collection, the author has succeeded in designing a heat therapy pillow using a temperature sensor and ARDUINO UNO based timer controller that can provide convenience when going to heat therapy because it is equipped with an automatically controlled temperature sensor and controller timer. by DS1820 temperature sensor. A therapeutic pillow based on Arduino with 10 minutes of therapy results in a temperature of 41 °C.  
Co-Authors ABA, Muhammad Ulin Nuha Akrom, Muhamad Aulia, Andika Brahmantya Aji Pramudita Fauziah, Haniifah Hana Harsoyo, Imam Tri Intan Andriani Josepa ND Simanjuntak Karim, Muhammad Nauval Kusumaningtyas, Pramesti Nurwijayanti Permana, Asyraf Rhomadhon, Syahruu Siyammu Rofi i, Mohammad Rofi’i, Mohammad S. Susilo, S. Sudarma, Made Putra Sutikno Madnasri Trisna Budiwati Widyastuti, Ardian zulfa, nely