TY - GEN
T1 - Radionuclide identification analysis using machine learning and GEANT4 simulation
AU - Kusuma, Gina
AU - Saryadi, Rezky Mahardika
AU - Wijaya, Sastra Kusuma
AU - Soekirno, Santoso
AU - Prajitno, Prawito
AU - Susila, I. Putu
N1 - Funding Information:
This work was supported by PPTI - 5LVWHNGLNWL SURJUDP ZLWK WKH WLWOH SURJUDP ³'HYHORSPHQW RI 5DGLDWLRQ (QYLURQPHQWDO 0RQLWRULQJ EDVHG RQ *DPPD 6SHFWURVFRS\´ ZKLFK VXEPLWWHd by PRFN-BATAN with contract number 12/G2/PPK/E/E4/2019.
Publisher Copyright:
© 2021 Author(s).
PY - 2021/11/11
Y1 - 2021/11/11
N2 - Security of nation border is an important thing which has to be kept from many kinds of criminal activities. One of the important things is preventing the nation from nuclear criminal activity like illegal nuclear source trafficking, nuclear source abuse and or nuclear pollution which want to enter to our country. Indonesia, through national nuclear agency (BATAN) will build environment and nuclear monitoring device station which will be placed at each state border. This device prepared to detect nuclear pollution around the station which potentially can harming the nation environment. Detecting nuclear pollution in the open environment is required to have an ability to radionuclide identifications rapidly. Support Vector Machine and Linear Discriminant Analysis was used in this research which prepared to be used on environment and nuclear monitoring device. Pre-processing was done to make the gamma spectrum data from CsI(Na) detector as feature can be analyzed with SVM and LDA. The setup of data collection was done with variation of source-detector distance, there are 50, 75, 100, 125 and 150 cm, variation of measurement time, from 1, 5, 10, 15, 30, 60 and 120 minutes. The result shows that LDA method can detect the radionuclide source with an accuracy value 84 percent, whereas using SVM-LDA method can get accuracy score more than 91 percent.
AB - Security of nation border is an important thing which has to be kept from many kinds of criminal activities. One of the important things is preventing the nation from nuclear criminal activity like illegal nuclear source trafficking, nuclear source abuse and or nuclear pollution which want to enter to our country. Indonesia, through national nuclear agency (BATAN) will build environment and nuclear monitoring device station which will be placed at each state border. This device prepared to detect nuclear pollution around the station which potentially can harming the nation environment. Detecting nuclear pollution in the open environment is required to have an ability to radionuclide identifications rapidly. Support Vector Machine and Linear Discriminant Analysis was used in this research which prepared to be used on environment and nuclear monitoring device. Pre-processing was done to make the gamma spectrum data from CsI(Na) detector as feature can be analyzed with SVM and LDA. The setup of data collection was done with variation of source-detector distance, there are 50, 75, 100, 125 and 150 cm, variation of measurement time, from 1, 5, 10, 15, 30, 60 and 120 minutes. The result shows that LDA method can detect the radionuclide source with an accuracy value 84 percent, whereas using SVM-LDA method can get accuracy score more than 91 percent.
UR - http://www.scopus.com/inward/record.url?scp=85119360980&partnerID=8YFLogxK
U2 - 10.1063/5.0067593
DO - 10.1063/5.0067593
M3 - Conference contribution
AN - SCOPUS:85119360980
T3 - AIP Conference Proceedings
BT - Proceedings of the International Conference on Nuclear Science, Technology, and Application 2020, ICONSTA 2020
A2 - Rifal, Muhammad
A2 - Mulyani, Emy
A2 - Mujamilah, null
A2 - Sugono, Irawan
A2 - Santoso, Muhayatun
A2 - Taufik, null
PB - American Institute of Physics Inc.
T2 - International Conference on Nuclear Science, Technology, and Application 2020, ICONSTA 2020
Y2 - 23 November 2020 through 24 November 2020
ER -
