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PERHITUNGAN ENERGI KEADAAN DASAR ATOM LITHIUM MENGGUNAKAN METODE VARIASIONAL DUA PARAMETER Josua Timotius Manik; Victor Reynaldi; Zaki Su'ud
Jurnal Sains dan Pendidikan Fisika Vol 18, No 3 (2022): JURNAL SAINS DAN PENDIDIKAN FISIKA
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jspf.v18i3.32939

Abstract

Setiap atom memiliki energi pada keadaan dasar yang berbeda-beda. Semakin banyak jumlah elektron yang dimiliki oleh atom, maka semakin kompleks pula cara pengerjaan yang perlu dilakukan untuk menghitung energi keadaan dasarnya. Perhitungan energi tersebut dapat dilakukan dengan berbagai metode. Penelitian ini bertujuan untuk menghitung energi atom Lithium pada keadaan dasar secara analitik dan numerik. Salah satu metode yang dapat digunakan untuk perhitungan energi adalah metode variasional dengan menggunakan dua parameter variasi. Pengerjaan secara numerik dilakukan menggunakan aplikasi GNU Octave sebagai alat bantu. Hasil perhitungan menunjukkan bahwa energi keadaan dasar atom Lithium adalah -201.28 eV. Hasil ini cukup mendekati nilai eksak hasil eksperimen yang terdapat pada referensi dengan deviasi sekitar 1.08%. Hal ini membuktikan bahwa metoda variasional dapat digunakan untuk menghitung energi keadaan dasar atom berelektron banyak. 
Introduction of Physics Application for Medical Imaging on CT Scan Modalities at SMA Efata Tangerang Josua Timotius Manik; Eunike Winda Ayusari; Gabriella Novinda; Tumpal Pandiangan
Jurnal Pengabdian Masyarakat Bestari Vol. 2 No. 3 (2023): March 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/jpmb.v2i3.3495

Abstract

The physics contribution in medicine began with the discovery of x-rays by Wilhelm Roentgen in 1895. The uses of ionizing radiation for medical imaging applied to the CT scan modality to obtain inside images of the human body based on differences in organ density. Preliminary observations show that students at SMA Efata Tangerang do not have enough knowledge about physics and its application in medicine. Therefore, the Physics Study Program at Matana University carried out community service activities (PKM) in order to introduce medical physics to the students at SMA Efata. The PKM activities are carried out in the form of seminars which are divided into three sessions using lecture and discussion methods. The results of this service show that PKM activities can spur the motivation and interest of students at SMA Efata in studying physics.
Validation of Varian Clinac iX Model on 6 MV Photon Beam Using Fast Monte Carlo Simulation Josua Timotius Manik; Anisza Okselia; Daniel Gibbor Gaspersz; Freddy Haryanto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27075

Abstract

Monte Carlo (MC) is widely recognized as the most accurate method for dosimetry analysis in radiotherapy due to its precision. However, successful MC dose calculation hinges upon the validation of the linac model employed in simulations. This study aims to verify the PRIMO model of the Varian Clinac iX and to determine the optimal initial electron energy. The comparison of one-dimensional dose distribution between simulations and measurements serves as the foundation for assessment. The Varian Clinac iX on 6 MV photon beam was meticulously modeled with the initial electron energies spanned from 5.2 to 5.8 MeV in increments of 0.2 MeV. The dose calculation were performed for a field size of 10 cm × 10 cm and a source-to-surface distance (SSD) of 100 cm. The Dose Planning Method (DPM) was adopted as the simulation engine for expedited MC simulation. A number of particle histories–approximately 4.0 × 108–were simulated, resulting in the generation of around 109 particles from the linac head. The investigation revealed that an initial electron energy of 5.8 MeV achieves good agreement with measurement by attaining the smallest difference in percentage depth dose (PDD) of about 0.98%. The lateral dose deviation of approximately 4.63% serves to validate the precision of the secondary collimator design. Additionally, a comparative analysis of DPM and PENELOPE for dose calculation was conducted. In contrast to the PENELOPE, the DPM speeds up simulation time by approximately 3.5 times, reduced statistical uncertainties to 0.59% and afford better accuracy in dose calculation. The result underscore the suitability of the PRIMO model for MC simulation for dose calculation, given its robust agreement with the measurements.
Algoritma Convolutional Neural Network sebagai Alat Bantu Analisa Tingkat Keparahan Tumor Otak IRMANIAR, IRMANIAR; MANIK, JOSUA TIMOTIUS; HARYANTO, FREDDY
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 9, No 1 (2024): MIND Journal
Publisher : Institut Teknologi Nasional Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v9i1.1-12

Abstract

AbstrakKecerdasan buatan telah menjadi dasar dalam pengembangan computer-aided-diagnosed (CAD), yaitu alat tambahan yang digunakan untuk melakukan diagnosa penyakit, misalnya tumor otak. Pada penelitian ini dilakukan klasifikasi otomatis citra MRI otak ke dalam 4 kategori, yaitu tumor otak grade II, III, IV dan non-tumor menggunakan Convolutional Neural Network (CNN). Tiga jenis arsitektur yang digunakan, yaitu arsitektur 12 lapisan, Resnet-152 dan VGG-16. Peningkatan jumlah gambar dilakukan dengan melakukan 6 jenis teknik augmentasi. Hasilnya menunjukkan bahwa ketiga model dapat melakukan klasifikasi tumor dengan akurasi masing-masing sebesar 84%, 95% dan 84% pada data tanpa augmentasi dan 49%, 81% dan 72% untuk data yang mengalami augmentasi. Hasil tersebut menunjukkan bahwa arsitektur Resnet-152 memberikan performa terbaik dibandingkan dengan arsitektur lainnya.Kata kunci: Tumor otak, Convolutional Neural Network (CNN), Resnet-152, VGG-16AbstractArtificial intelligence has become the basis for the development of computer-aided-diagnosed (CAD), an additional tool used to diagnose diseases, such as brain tumors. In this study, automatic classification of brain tumor was carried out into 4 categories, namely grade II, III, IV and non-tumor using the Convolutional Neural Network (CNN) algorithm. Three types of architecture are used, namely 12 layer architecture, Resnet-152 and VGG-16. The dataset comes from the REMBRANDT and IXI dataset. Increasing the number of images using 6 types of augmentation techniques is also done. The results show that the three models can classify tumors with an accuracy of 84%, 95% and 84% respectively for data without augmentation and 49%, 81% and 72% for data with augmentation. It can be concluded that the Resnet-152 architecture provides the best performance than the other architectures.Keywords: Brain tumor, Convolutional Neural Network (CNN), Resnet-152, VGG-16
Investigation of Radiation Protection Measures in Extracorporeal Shock Wave Lithotripsy Facilities: A Study Based on NCRP Report 147 Margaretha, Angelica; Adhianto, Dwi; Manik, Josua Timotius
Journal of Physics and Its Applications Vol 6, No 2 (2024): May 2024
Publisher : Diponegoro University Semarang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/elipsoida.%Y.22518

Abstract

Fluoroscopy, also referred to as the C-Arm, is a direct imaging modality used in interventional radiology. It is commonly used, particularly in Extracorporeal Shockwave Lithotripsy (ESWL) for kidney stone removal. The process of kidney stone destruction typically spans from 45 to 60 minutes. Continuous exposure to the radiation can lead to an accumulation of radiation dosage, potentially causing harmful effects. Radiation shielding is one of the most important factors for radiation protection in obtaining a license to construct a radiation room. Radiation shielding requires a minimum thickness to prevent exposure to radiation from escaping the room and posing a risk to the public. Measurements were conducted within the ESWL facility situated at XYZ private hospital, encompassing both internal and external locations, spanning across a total of 11 designated measurement points. The calculations were performed in accordance with the guidelines stated in NCRP Report No.147. The result obtained were 1.665; 1.681; 1.686; 1.109; and 1.716 mm for lead material thickness and 223.8; 225.9; 226.4; 153.2; and 230.2 mm for concrete material thickness. The hospital walls were constructed using concrete with a thickness of 200 mm and were additionally covered with a 2 mm Pb coating. In conclusion, the lead installed meets NCRP standards, but the thickness of the concrete walls around the room still falls short of the requirements.