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Mohtar Yunianto, Mohtar
Universitas Sebelas Maret
Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences Other

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Performance Analysis of EPC Material as a Kidney Organ Phantom with Exposure Voltage Variations and PA-GF-Based Kidney Stone Size Cari, Cari; Yunianto, Mohtar; Anwar, Fuad; Permadi, Hardo Ardiansyah Gilang
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 15, No 2 (2025): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v15i2.106579

Abstract

Research in the field of radiodiagnostics has been extensively developed, creating the need for substitute objects to represent human organs—namely, radiological phantoms. A phantom is a simulated model of an organ fabricated using 3D printing technology. This study aims to evaluate the suitability of Expanded Polyamide – Glass Fiber (EPA-GF) as a kidney stone phantom material embedded within a kidney phantom, based on parameters such as material density, CT number, electron density, and radiation dose across various CT scan exposure voltages. The phantom samples were printed using a dual-extruder 3D printer, with Expanded Polycarbonate (EPC) used as the kidney phantom material. CT scan exposure voltages were set to 80 kV, 100 kV, and 120 kV. Kidney stone sizes used in this study ranged from 1 mm to 8 mm (1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, and 8 mm). The measured density of EPA-GF was 1.51 ± 0.06 g/cm³. The CT numbers obtained at each voltage were 373.30 HU, 329.05 HU, and 299.46 HU, respectively. The corresponding electron density values were 1.231, 1.210, and 1.196, respectively. The effective doses measured at each voltage were 0.0240 mSv, 0.0448 mSv, and 0.0798 mSv. All parameter values were found to be closely aligned with literature references. The smallest visible kidney stone size detected was 2 mm.
Front Matter Vol 07 No 02 2017 Yunianto, Mohtar
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 7, No 2 (2017): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v7i2.19972

Abstract

Lung Cancer Classification using Gray-Level Co-Occurrence Matrix Feature Extraction and Forward Selection Feature Selection based on the K-Nearest Neighbor Algorithm Soeparmi, Soeparmi; Yunianto, Mohtar; Amalia, Lukmaniyah Rizky
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 15, No 1 (2025): April
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v15i1.90378

Abstract

In diagnosing lung cancer, the medical imaging team manually identifies CT-scan images of the lungs. This identification process makes it difficult for the medical imaging team to differentiate between lung cancer and normal images. This is because there is noise in the image, which reduces the image quality, so image processing must reduce the noise. This study used median and Gaussian filters, Otsu thresholding segmentation, GLCM feature extraction, forward selection, and k-nearest Neighbor classification. The research results show that of the 22 statistical features extracted, only 16 were selected for characterizing image classification. The image datasets used are 900 image data sets for program training and 100 image data sets for program testing. With a dataset of 100 image data sets, the level of diagnostic accuracy without forward selection (22 GLCM features) was 81.67%, while the diagnostic accuracy using forward selection (16 GLCM features) was 93.22% with a sensitivity of 92.25% and specificity is 94.46%.
Back Matter Vol 07 No 02 2017 Yunianto, Mohtar
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 7, No 2 (2017): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v7i2.19974

Abstract

Pneumonia Classification Based on GLCM Features Extraction using K-Nearest Neighbor Suharyana, Suharyana; Anwar, Fuad; Dewi, Armylia Chandra; Yunianto, Mohtar; Salamah, Umi; Chai, Rifai
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 13, No 2 (2023): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v13i2.77120

Abstract

Pneumonia has been detected using Machine learning. The stages in this study began with preprocessing in 4 stages: resizing, cropping, filtering using a high pass filter, and Adaptive Histogram Equalization. The feature extraction process continued with 22 Gray Level Co-occurrence Matrix (GLCM) features and classification using K-Nearest Neighbor (KNN). The image used was 150 data sets for training on the classification of 3 classes with a ratio of 50:50:50 while training on two classes was 50 bacterial pneumonia and 50 viral pneumonia. The most optimal training data accuracy results were obtained using the angle direction on the GLCM, namely 135o with the KNN classification (k = 3). For the classification of two classes Using 40 data sets, an accuracy of 91% was obtained, while testing for three classes with 60 data sets was 83.3%.
Front Matter Vol 06 No 02 2016 Yunianto, Mohtar
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 6, No 02 (2016): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v6i02.19964

Abstract

Sistem Pengukuran Detak Jantung Janin Melalui Elektrokardiogram Abdominal dan Android Aji, Yusuf Anggara; Nuryani, Nuryani; Wiyono, Nanang; Yunianto, Mohtar; Purnama, Budi; Utari, Utari; Riyatun, Riyatun; Suharno, Suharno; Raharjo, Dwi Teguh
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 12, No 2 (2022): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v12i2.65287

Abstract

An android-based fetal heart rate measurement is presented in this article. The fetal heart rate was obtained from the mother's abdominal electrocardiogram which was then measured and processed by Raspberry pi using k-means. Raspberry pi processed results produce ECG signals and fetal heart rate which was displayed on Android devices in real-time. The android application can also save heart rate and ECG data or retrieve previously taken heart rate recordings. The system obtained that the average value of accuracy, sensitivity and predictive positive were 90.49%, 97.10% and 93.03%, respectively. The variation of the training time of the algorithm showed that the training time of 10 and 15 seconds mostly has better performance than the training time of 5 seconds.
Back Matter Vol 06 No 02 2016 Yunianto, Mohtar
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 6, No 02 (2016): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v6i02.19966

Abstract

Front Matter Vol 06 No 01 2017 Yunianto, Mohtar
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 7, No 1 (2017): April
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v7i1.19968

Abstract

Study of Macrobending Losses Effect in Plastic Optical Fibber. Ghozali, Egyn Furqon; Yunianto, Mohtar; N, Nuryani
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 4, No 01 (2014): April
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v4i01.1166

Abstract

Experimental study to analyze the effect of macrobending losses in plastic optical fiber triple bending model based on PC (personal computer) has been conducted. The data is gathered by measuring the change of the light intensity due to the presence of bending on optical fibers. The bending causes losses of optical fiber that is read by WIM (weight in motion) Acquisition program based on Borlan Delphi 7. The optical fibers are plastic with diameter of 3 mm. The diameter of pin is 8 mm and the space between the pin is 5 mm. The light source is a LED (λ=676 nm). As a result, the losses of optical fiber increase with the enhancement of bending. The increase trend linear to sensitivity of the sensor with gradient of 0,1063 and R2 of 0,9626. Therefore, the proposed design might be applied as a WIM sensor.
Co-Authors Ahmad Marzuki Aji, Yusuf Anggara Aldicia, Ivara Salsabila Putri Amalia, Lukmaniyah Rizky Anwar, Fuad Budi Legowo Budi Purnama Cari, Cari Chai, Rifai Cindyana, Adnan Darmanto Darmanto Devi, Nanda Astika Dewi, Armylia Chandra Fahru Nurosyid Fuad Anwar, Fuad Ghozali, Egyn Furqon Hendri Widiyandari Khairuddin - Koesuma, Sorja Kusumandari, Kusumandari M, Arrini Nurul Maftukhaturrizqoh, Olivia N, Nuryani Nanang Wiyono Nuryani Nuryani Permadi, Hardo Ardiansyah Gilang Praptomo, Mokhamad Sahid Raharjo, Dwi Teguh Risa Suryana Riyatun, Riyatun Sari, Arum Putri Kurnia Soeparmi Soeparmi, Soeparmi Sofia, Iftita Ida Suharno Suharno Suharyana Suharyana Suparmi Suparmi Umi Salamah Utari Utari Wijaya, Agung Dwi Wiji Lestari Wuriatmo, Hastho Yofentina Iriani