Analysis Mathematical Model of Radicalization S(Susceptible) E(Extremists) R(Recruiters) I(Immunity) with Optimal Control
Keywords:
Susceptible (S), Extremists (E), Recruiters (R), Immunity (I)Abstract
Radicalization is a process when people come to adopt increasingly extreme political or religious ideologies, radicalization almost occurs in almost all countries in the world. Seeing a number of cases in recent times, radicalization has become a major concern for the world, especially in the field of national security. Radicalization has become one of the focuses in the national security sector because it leads to acts of extremism, violence and terrorism. The level of radicalization is high in each year and continues to increase so special supervision is needed to control it because it causes huge financial losses. Therefore a preventive effort is needed to overcome this. Efforts to prevent radical movements have been widely used, ranging from direct or indirect, in addition some things have also been done directly by the government. So far it has not been seen how effective these efforts are. Radicalization is formed because of the influence of extremists and the recruiters group. Many individuals are affected and enter the group because they are influenced by the people in the group who are within their scope. To overcome these problems, a control is needed as an effort to prevent radicalism. Prevention efforts are in the form of strict sanctions given to recruiters. Next to find out how the influence of controls on individual groups of recruiters is needed a tool to represent the tool is a model. The mathematical model that is suitable for representing the appropriate problems of radicalization is the Susceptible (S) , Extremists (E) Recruiters (R), Immunity (I) model.
References
C. McCluskey and M. Santoprete, “A bare-bones mathematical model of radicalization,” arXiv preprint arXiv:1711.03227, 2017.
R. Rahimullah, S. Larmar, and M. Abdalla, “Understanding violent radicalization amongst muslims: A review of the literature,” Journal of Psychology and Behavioral Science, vol. 1, no. 1, pp. 19–35, 2013.
E. Mulcahy, S. Merrington, and P. Bell, “The radicalisation of prison inmates: A review of the literature on recruitment, religion and prisoner vulnerability,” Journal of Human Security, vol. 9, no. 1, pp. 4–14, 2013.
H. Hethcote, “The mathematics of infectious diseases,” SIAM review, vol. 42, no. 4, pp. 599–653, 2000.
O. Tessa, “Mathematical model for control of measles by vaccination,” in Proceedings of Mali Symposium on Applied Sciences, vol. 2006, 2006, pp. 31–36.
M. Choisy, J.-F. Guegan, and P. Rohani, “Dynamics of infectious diseases and pulse vaccination: teasing apart the embedded resonance effects,” Physica D: Nonlinear Phenomena, vol. 223, no. 1, pp. 26–35, 2006.
M. Santoprete and F. Xu, “Global stability in a mathematical model of de-radicalization,” Physica A: Statistical Mechanics and its Applications, vol. 509, pp. 151–161, 2018.
A. Panfilov, “Qualitative analysis of differential equations,” arXiv preprint arXiv:1803.05291, 2018.
N. Nastitie and D. Arif, “Analysis and optimal control in the cancer treatment model with combining radio and anti-angiogenic therapy,” IJCSAM (International Journal of Computing Science and Applied Mathematics), vol. 3, no. 2, pp. 55–60, 2017.
