Sistem Pendukung Keputusan Seleksi Penerimaan Beasiswa Bidikmisi Menggunakan Metode Topsis dan Metode SAW

Education is an important thing for every child to get knowledge and formal education in school. Background of children who are from underprivileged families, not the least cause the children drop out of school. The government provides solutions through Kemenristek Dikti institution to hold a scholarship program BIDIKMISI for underprivileged and achieving children for education, especially from SMA / SMK or equivalent to university. In this research, a decision support system was developed using TOPSIS method (Technique for Order Performance by Equal with Ideal Solution) and SAW (Simple Additive Weighting) method for BIDIKMISI scholarship recipient. The policies used in determining scholarship recipients are generation, value, number of siblings, father education, and mother education. The results obtained by using 79 data of prospective recipients obtained by using the name of Nensy, 0.7394 of TOPSIS calculation and 81.7 from the calculation of SAW. Highest value parsing system according to priority

Kendali Kecepatan Motor DC dengan Metode Pulse Width Modulation Menggunakan N-channel Mosfet

The DC motor is one component of robot, the main function of a DC motor is as a driver, whether it's a legged robot or not, as used in a mobile robot. DC motor control is necessary to be one thing that must be considered, because if the motor does not run properly, it will renew the purpose of the motor when it is created. The ability to control a DC motor is needed when building a robot. Many things can affect a person's ability to design DC motor controller, one of which is the development of science, especially computer science, the use of algorithms to achieve the effectiveness of DC motor movements is very necessary today, so that the robot can move well and according to what is desired. The algorithm requires some information from the system that is built either as input or output so that the algorithm can perform the control process properly. in this study the motor speed controller circuit has been designed using transistor IR630 (n-channel mosfet), in this study the motor speed controller circuit has been designed using transistor IR630 (n-channel mosfet), the potentiometer is used as an analog input on the microcontroller and then converted to a PWM signal which will be used as input to the controller circuit to drive a DC motor. In the tests that have been carried out, the results obtained that the motor can be controlled properly, the use of resistors with a certain amount (220 ohms) can increase the resulting motor rotation and at what voltage the motor starts to spin at a voltage of 0.436 volts, and continues to increase and the maximum voltage recorded at 6.40 Volts

Simulasi Kendali Pergerakan Mobile Robot Menggunakan Algoritma A-star dalam Menentukan Jarak Terpendek

Planning the path is one of the most important things in the world of robotics, especially autonomous robots, to be able to move the autonomous robot requires a path that will guide the movement, or steps to be taken next, can also be spelled out as the determination of the point of coordinates to be addressed so that the robot can move to destination by taking the nearest lane and guiding the robot not to take unnecessary steps. This research uses adaptive A-star algorithm as the shortest path finding algorithm, the algorithm used is the development of A-star algorithm so that it can perform path search gradually and done repeatedly to determine every step that must be taken robot in the future and this algorithm belongs to a simple algorithm in a family heuristic algorithm. The test environment is built using Netlogo 5.3.1 Application, an agent-based application developed by Uri Wilensky at the center for Connected Learning and Compute-based Modeling at Northwestern University. The results of the tests have shown that the adaptive A-star algorithm can perform the optimal shortest path search and not trapped in the optimal local conditions with a standard deviation of 0.422%