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All Journal INDONESIAN JOURNAL OF APPLIED PHYSICS Adi Widya : Jurnal Pengabdian Masyarakat Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Risalah Fisika SEMAR Jurnal Materi dan Pembelajaran Fisika
Anwar, Fuad
Physics Department, Universitas Sebelas Maret
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Education Energy Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences Other

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Journal : indonesian journal of applied physics

 1 
Klasifikasi Kanker Paru Paru menggunakan Naïve Bayes dengan Variasi Filter dan Ekstraksi Ciri GLCM Mohtar Yunianto; Soeparmi Soeparmi; Cari Cari; Fuad Anwar; Delta Nur Septianingsih; Tonang Dwi Ardyanto; Resta Farits Pradana
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 11, No 2 (2021): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v11i2.53213

Abstract

Telah berhasil dilakukan klasifikasi kanker paru-paru dari 120 data citra CT Scan. Pada penelitian, proses preposisi dimulai dengan variasi filtering yaitu low pass filter, median filter, dan high pass filter. Segmentasi yang digunakan yaitu Otsu Thresholding yang kemudian teksturnya akan diekstraksi menggunakan fitur Gray Level Co-occurrence Matrix (GLCM) dengan variasi arah sudut. Hasil dari ekstraksi GLCM dijadikan database yang akan menjadi dataset untuk pengklasifikasian citra menggunakan klasifikasi naïve bayes. Hasil dari penelitian dengan 12 buah variasi diperoleh hasil variasi terbaik adalah median filter dengan arah sudut GLCM 0° menunjukkan tingkat akurasi yang paling tinggi sebesar 88,33 %.
Pneumonia Classification Based on GLCM Features Extraction using K-Nearest Neighbor Suharyana Suharyana; Fuad Anwar; Armylia Chandra Dewi; Mohtar Yunianto; Umi Salamah; Rifai Chai
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%.
Performance Analysis of EPC Material as a Kidney Organ Phantom with Exposure Voltage Variations and PA-GF-Based Kidney Stone Size Cari Cari; Mohtar Yunianto; Fuad Anwar; Hardo Ardiansyah Gilang Permadi
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.
Co-Authors A Suparmi Alqaan Maqbullah Ilmi Arief Hermanto Armylia Chandra Dewi Artono Dwijo Sutomo Cari Cari Cari Cari Cari Cari Cari Cari Darmanto Darmanto Darmanto Darmanto Delta Nur Septianingsih Fendi Aji Purnomo Hardo Ardiansyah Gilang Permadi Imaduddin, Agung Kusumandari, Kusumandari Mohtar Yunianto Mohtar Yunianto Mohtar Yunianto Mohtar Yunianto Mohtar Yunianto Mohtar Yunianto Mohtar Yunianto Mohtar Yunianto, Mohtar Pekik Nurwantoro Resta Farits Pradana Rifai Chai Riyatun Riyatun Riyatun Riyatun Santosa, Usman Soeparmi Soeparmi Suharyana Suharyana Suharyana Suharyana Suparmi Suparmi Suparmi Suparmi Tanzillal Alfargana Tonang Dwi Ardyanto Tuti Dwi Setyaningsih Umi Salamah Yofentina Iriani