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All Journal Journal of Physics and Its Applications SEMAR Jurnal Ilmiah Ilmu Terapan Universitas Jambi Aceh International Journal of Science and Technology
Fuad Anwar, Fuad
Program Studi Teknik Industri, Universitas Islam Bandung
Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences

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Tuberculosis Detection using Gray Level Co-Occurrence Matrix (GLCM) and K-Nearest Neighbor (K-NN) Algorithms Anwar, Fuad; Yunianto*, Mohtar; Putri, Rahmanisya Fani Aisha
Aceh International Journal of Science and Technology Vol 12, No 3 (2023): December 2023
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.3.33241

Abstract

Research has been conducted on detecting tuberculosis (TB) using machine learning. In this study, chest Xray (CXR) image data was used with a pixel value of 512 x 512 and PNG format consisting of normal lung images and TBinfected lung images in a 50:50 ratio; the number of images was 200 training data images and 80 testing data images. In the preprocessing stage, grayscaling is carried out so the image has a grayscale. Then, do the image improvement using contrast stretching. Furthermore, image extraction was carried out using 22 GLCM features with variations in the direction of the angles of 0, 45, 90, and 135. The result of feature extraction data is then identified using KNN Classification. The training results have the highest accuracy value with variations in the direction of the GLCM angle of 45 and the value of K = 3; at the testing stage, it produces an accuracy of 90%.
Analysis of Total Proton Therapy Dose Distribution with Pencil Beam Collimator Model and Varied Beam Directions in Craniopharyngioma Tumor using MCNP6 Software Hayati, Widia; Utari, Utari; Anwar, Fuad; Suharyana, Suharyana; Arianto, Fajar; Khakim, Azizul
Journal of Physics and Its Applications Vol 7, No 1 (2024): November 2024
Publisher : Diponegoro University Semarang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jpa.v7i1.23977

Abstract

Proton therapy modeling for treating craniopharyngioma tumors was conducted using a pencil beam collimator, and variations in beam directions were performed using MCNP6 software. The simulation was carried out on a head and neck phantom with the tumor cells modeled within a cubic irradiation area geometry with a 1.2 cm side length, divided into 27 small cubic voxels with a small voxel side length of 0.4 cm. The radiation source from the irradiation area's right, left, and top directions, with a diameter of 0.4 cm, was directed at each cubic voxel. Variation in radiation source directions indicated that irradiation from the right direction of the irradiation area is the most recommended approach, with a dose uniformity level of 83.47%. Healthy organs surrounding the irradiation area received lower doses than those obtained by tumor cells, and the majority remained below the Organ At Risk (OAR) threshold. Healthy organs received the highest dose, particularly in the brain region, at a relative 0.46% compared to the total dose received by tumor cells.
STUDY OF 3D PRINTING HIPS BREAST PHANTOM MATERIAL: EFFECT OF EXPOSURE VOLTAGE VARIATION AND NODULE SIZE Yunianto, Mohtar; Devi, Nanda Astika; Anwar, Fuad; Cindyana, Adnan
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.42846

Abstract

A study has examined the characteristics of 3D printer materials of HIPS and PLA. The study began by printing HIPS materials that resembled breast organs and PLA materials that resembled breast cancer nodules. Then it exposed them using a CT scan with voltage variations of 80 kV, 100 kV, and 120 kV. The parameters studied were compared with the reference breast organ. The results obtained at these voltages obtained CT-number values sequentially (-85.14+0.25) ; (-64.79+0.21) HU; (-55.08+0.18) HU values from the reference 35 to -94 HU, relative electron density values sequentially 0.915; 0.935; 0.945 with a reference value of 0.950, the density value of the material obtained is (0.921+0.002) g/, The EDG value is 3.24 x  from ICRU 1989 was 3.33 x, The EDV value is (3.00 + 0.01) x  from ICRU report 44 was 3.18 x 10, the value is 3.50 the value of ICRU data is 3.28, and the effective dose values are respectively 2.53 mSv, 2.83 mSv, 3.20 mSv. Based on these characteristics, the results indicate that the breast phantom matches the characteristics of the breast organ, allowing it to be used to predict the presence of breast cancer, as it shares the same characteristics. The results of exposure to the lung cancer nodule phantom on the CT-Scan image of the 2 mm nodule size are not visible. The results of this study can be used as a consideration for radiologists when choosing a voltage based on the predicted size of the breast cancer nodule.
Inisiasi Implementasi Zenius sebagai Aplikasi Pembelajaran Online di SD Muhammadiyah Wonorejo Anwar, Fuad; Soeparmi, Soeparmi; Cari, Cari; Riyatun, Riyatun; Suharyana, Suharyana; Yunianto, Mohtar; Darmanto, Darmanto
SEMAR (Jurnal Ilmu Pengetahuan, Teknologi, dan Seni bagi Masyarakat) Vol 10, No 2 (2021): November
Publisher : LPPM UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/semar.v10i2.52163

Abstract

Telah dilakukan inisiasi implementasi zenius yang merupakan aplikasi pembelajaran online di SD Muhammadiyah Wonorejo yang  diikuti 17 Guru. Dalam kegiatan tersebut dibagi menjadi 2 tahap, tahap pengenalan Aplikasi berbasis Desktop untuk menu pengunjung, Guru, Murid dan Orang tua. Untuk menu Guru dilatih untuk mengelola kelas, mengunggah materi pembelajaran, membuat soal, melakukan penilaian siswa serta melakukan pelaporan nilai ke orang tua. Tahap berikutnya adalah pengenalan Aplikasi berbasis Android, di latihkan untuk menu Murid, berisi lihat materi pembelajaran, presensi, mengerjakan soal ujian dan mengetahui hasil ujian. Sebelum dilakukan pelatihan sebagian besar tidak memahami aplikasi pembelajaran online, setelah dilakukan pelatihan semua peserta memahami dan akan mengimplementasikan dalam proses pembelajaran di kelas. 
Inisiasi dan Pengembangan Ruang Komunitas Digital Desa di Desa Wonorejo sebagai upaya mewujudkan Desa Mandiri berbasis Digital Yunianto, Mohtar; Anwar, Fuad; Suparmi, Suparmi; Cari, Cari; Suharyana, Suharyana; Darmanto, Darmanto
SEMAR (Jurnal Ilmu Pengetahuan, Teknologi, dan Seni bagi Masyarakat) Vol 12, No 2 (2023): November
Publisher : LPPM UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/semar.v12i2.75826

Abstract

Desa Wonorejo merupakan satu-satunya Desa di Kecamatan Polokarto yang memperoleh Predikat Desa Mandiri, berbagai kegiatan dilakukan untuk implementasi predikat tersebut salah satunya adalah Desa Digital. Upaya yang dilakukan diantaranya dengan pembentukan ruang komunitas Digital Desa dengan 6 fokus diantaranya Ekonomi Cerdas, Tata Kelola Cerdas, Lingkungan Cerdas, Mobilitas Cerdas, Hidup Cerdas dan Masyarakat Cerdas. Langkah yang telah dilakukan untuk mewujudkan 6 fokus tersebut adalah pembuatan ruang komunitas fisik dan juga ruang komunitas virtual. Dengan di buatnya 2 ruang komunitas tersebut diharapkan Desa Wonorejo segera tercapai sebagai Desa Mandiri berbasis Digital.Katakunci : Digital; Desa Mandiri; komunitas; ruang digital
Co-Authors Azizul Khakim, Azizul Cari, Cari Cindyana, Adnan Darmanto Darmanto Devi, Nanda Astika Fajar Arianto Hayati, Widia Mohtar Yunianto, Mohtar Putri, Rahmanisya Fani Aisha Riyatun, Riyatun Soeparmi Soeparmi, Soeparmi Suharyana Suharyana Suparmi Suparmi Utari Utari Yunianto*, Mohtar