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Comparison between Fuzzy Logic Controller (FLC) and Fractional Order Proportional Integral Derivative (FOPID) Controller on Water Level and Steam Temperature of Steam Drum Boiler Zainullah Zuhri; Mardlijah Mardlijah; Didik Khusnul Arif
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 4 No. 2 (2018)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

Steam drum boiler is an important component of boiler on electric steam power plant which is useful to obtain steam. The obtained steam makes turbine spin. In order to obtain maximal result for the steam power plant (PLTU) 1-2 PT PJB UP Gresik, the water level of steam drum boiler must be 0.7625 m and the temperature of steam drum boiler must be 786 K. Thus, it needs some controller to keep the position of water level and the temperature stable. In this problem, we compare two controllers FLC and FOPID. It can be concluded that FLC works better than FOPID controller. Nevertheless, FOPID controller has faster response time than FLC, i.e. no overshoot and more robust when disturbance is present on the system.
Safety Verification of SEITR Epidemic Model on Recombination HIV and Hepatitis B Virus using Taylor Model Asmudik Asmudik; Dieky Adzkiya; Mardlijah Mardlijah; Hariyanto Hariyanto
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 7 No. 1 (2021)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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Abstract

Human Immunodeficiency Virus (HIV) is an AIDS (Acquired Immuno Deficiency Syndrome) virus that attacks the immune system for which there is no cure. When the immune system has decreased, it is prone to diseases such as Hepatitis B disease. To reduce the error value of the number of subpopulations, we use an interval approximation. One of the simulation calculations that the number of variables initially intervals is Taylor model. Taylor's model can be used to verify that the number of people infected with HIV and Hepatitis B will not exceed the specified number of unsafe sets. To calculate the set of states that are reached by the system over a certain period of time, given the initial conditions and parameters. The initial condition is divided into three scenarios, an affordable set of states, safety verification can be done. As a result of the safety verification of the three scenarios provided there is no set of states that are not safe, so the results of all three scenarios are safe.
Analysis Mathematical Model of Radicalization S(Susceptible) E(Extremists) R(Recruiters) I(Immunity) with Optimal Control Dauliyatu Achsina; Mardlijah Mardlijah
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 7 No. 2 (2021)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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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.