In this paper, present a vehicle actuator response using a hybrid control and make the vehicle has electronic stability program. Electronic Stability Program (ESP) is an automatic stability control systems on vehicles. Where the system works to avoid understeer and oversteer conditions when the vehicle is turning. Understeer is a condition where the vehicle more difficult to turn, this is because the front wheels tend to slip so that the vehicle will be more difficult to turn. Oversteer is a condition in which the vehicle is easier to turn, this is because the rear wheel tends to slip so that the vehicle will be easier to turn. Understeer and oversteer conditions often occur when turn or when a vehicle suddenly turn to avoid another vehicle. The control system designed for controlling vehicle is Fuzzy and PID-AFC. Fuzzy is for the high level control and PID-AFC is for low level control. Fuzzy processed a wheel speed, steering angle and IMU data. And PID-AFC receive set points value for wheel deceleration and acceleration from Fuzzy output. PID-AFC control the speed of left and right rear wheels when slip occurs. With this control the vehicle is expected to have a fast response and resistant to slip that happened. The test has successfully compared between PID and PID - AFC when running the motor. Without control, steady state error reaches 27.1%. When using PID steady state error only 1.7% with oscillation 12 times, when there is disturbance PID takes 1.4 seconds to return to setpoint. When using PID-AFC steady state error is only 1.7% with oscillation only 5 times and when any disturbance PID-AFC takes only 1.1 seconds to return to setpoint.

Fire is one of the few disasters that frequently occurred in Indonesia. Jakarta has archived 1139 fire incident with more than 20 casualties in 2016. By the rapid development of information technology and communication in Indonesia, it turns out that the number of incident and casualty still cannot be suppressed. This research is focused on early fire detection and home monitoring based on Wireless Sensor Network using 4 sensors such as temperature, air humidity, Carbon Monoxide, and smoke sensors. If the fire probability calculation categorized as high, system will perform an action of unlocking home door lock, turning on alarm, and notifying the user. Based on the trials and testing result, system is able to send notification to user precisely. However, error still can be encountered with up to 0.3% ratio on fire probability calculation.

In this paper, we present an approach for detecting, recognizing and tracking varying number of objects through both have similarity shape and colors. The objects tracking is the varying notes of Indonesian traditional instrument called “gambang”. Our method build an idea how to recognize well the notes and classify each objects in real time tracking. The houghlines standard method is used to search the right lines of the shape of instrument. At the level of detecting object, the square and contours method is used. The real time tracking is based on the color of contour object using hsv color filter. We demonstrate the viability of this approach by experimenting on several videos of the instrument from different angle of view 2D camera. The instrument labeling testing with the camera view from the left side has 100% success, from the center side has 95% success, and from the right side has 90% success.

Memory management evaluation test is one of the ways to understand the characteristic and performance of dynamic memory allocation algorithm. DMA is one of the RTOS parts that provide storage management when the applications are running. Nowadays there is a lot of memory management algorithm, and each algorithm has its own characteristics like the deterministic or nondeterministic algorithm. We develop a testing framework using Markov chain in order to test the allocation algorithm performance to fit the allocation behavior in RTOS. The framework generates various type of scenario test which can determine deterministic and nondeterministic of the algorithm based on the performance result. The result shows the impact of allocation size and allocation variation affect the allocation performance respond that generated by this framework.

Particle Swarm Optimization (PSO) is fast and popular algorithm to find the optimum value of non-linear and multi-dimensional function. However, it often easily trapped into local optima because the particles move closer to the best particle quickly. This paper purposes a new algorithm called Multi-Group Particle Swarm Optimization with Random Redistribution (MGRR-PSO) that tried to solve the weakness of standard PSO. MGRR-PSO combines two groups of PSO with opposite acceleration coefficients. In addition, some particles are redistributed when they are trapped in local optima. Experimental studies on 5 benchmark functions with 50-dimensions and 100-dimensions show that the MGRR-PSO can solve the problems that can't be solved by original PSO with better performance.

The massive internet usage is followed by the rise of cyber-related crime such as information stealing, denial-of-service (DoS) attack, trojan and malware. To cope with the threats, one of most popular choice is using Intrusion Detection System (IDS). The logs produced by IDS in a day is huge and the limitation of computing power is the main problem to process that logs files. In this paper, we propose a big data analysis architecture of multi IDS sensors using in-memory data processing. Deployed IDS sensors are taking an extra role as computation slave to build scalable data analysis platform for network security analysis. So, adding more sensors means expanding computational resources. Adding to three sensors are helping data computation of clustering algorithm faster up to 27% comparing to the computation by using only one sensor. This research also introduces the use of memory-based processor, this system provides 7,9 times faster data processing than conservative MapReduce operation. And moreover, we also have performed botnets classification over Spark RDD that give high accuracy result to 99%.

As continuation of our last research about dancing humanoid robot in 33 degree of freedom, in this paper we describe how to build dance pattern planning of Indonesia traditional dance movement in complete degree of freedom. We discuss the primitive pose in that commonly happened in traditional dance and build the transition pattern among the pose. The motion pattern method between the poses is based on the ability of robot to reach zero moment point position, and also the system to synchronize timing for dance motion is built. In this research zero moment point is our most concern problem because the worst thing in humanoid research is when the robot cannot maintain the balance itself. The computation considers that the zero moment point stays in a support polygon area.

Human can recognize an object just by looking at the environment, this capability is very useful for designing the reference of humanoid robot with the ability of adapting it on its environment. By knowing the field conditions that exist in such environments, robot can understand the obstacles or anything that can be passed. To do that, robot vision needs to have a knowledge to understanding an obstacles that exist around it. We investigate possible improvements that can be achieved in depth estimation by merging coded apertures and stereo cameras. The demonstrated results of this analysis are encouraging in the sense that coded apertures can provide valuable complementary information to stereo vision based depth estimation in some cases. We show that with this system, it is possible to extract depth information robustly, by utilizing the inherent relation between the disparity and defocus cues, even for scene regions which are problematic for stereo matching.

Humanoid robot is a robot that has intelligence like human. In this research, the team has build a robot called by FLoW. The robot is designed to have the ability as human beings, one of the ability is able to communicate. In the process of communication requires media, one of them is sound. This system is built to help the development research of ER2C (EEPIS Robotic Research Center) in building a Humanoid Robot ‘FLoW’. Robot ‘FLoW’ to be able to communicate, then the robot should be able to say word or doing speech. Its called as speech generation. To generate sound, it will be make text to speech synthesis system. In the process of preprocessing is using FSA (Finite State Automata) algorithms. In Indonesian language uses 11 patterns. The testing process is done on the processing of ‘words’, ‘sentences’, and ‘articles’. The percentage of success in ‘words’ and ‘sentences’ is more accurate and match with the separation of syllables in Indonesian language than the process of articles. From processing the article in newspaper, it has success rate of parsing 92.63%. The data were processed taken from five types of theme articles, namely the economy, education, sports, politics, and law. The performance is the result of parsing the articles is lower due to the addition of the name, title, and foreign words that have not undergone uptake in Indonesian language.

The ability of a robot to be able to change the shape is not something impossible to do. This research introduce such changeable shape robot named PodRacle, which has two basic forms; a form of a six-legged robot and a form of spherical robot. Combining the two basic forms, the PodRacle robot can result in increasing efficiency of a six-legged robot motion on a flat surface by means of rolling movement. The spherical robot shape can roll on a flat surface, then has a rolling speed that is faster than the walking legged robot. In order to implement the rolling movement, a prototype of robot mechanism is designed and its kinematics and dynamics equations are derived. The effectiveness of the robot and the equations are tested through experiments.

The RoboCup Middle Size League competition is a standard real-world test bed for autonomous multi-robot control, robot vision and other relative research subjects. In the past decade, omnidirectional vision system has become one of the most important sensors for the RoboCup soccer robots, for it can provide a 360° view of the robot's surrounding environment in a single image. The robot can use it for tracking and self-localization which very important for robot's control, strategy, and coordination. This paper will discuss the vision system to detect ball, goals, and calculate the angle and real distance from those objects. Based on the research that has been done, the system can detect the ball and the goal, and calculate the angle and the actual distance with a maximum error distance is 5%.

Basically Biped robots had to walk like human, to generate this system we use basic approach for analysis human walking behavior. Human walking behavior can be analyzed using Zero Moment Point (ZMP). Zero Moment Point (ZMP) is a zero point which total of gravity forces and horizontal inertia equal 0 (Zero). This paper describes about early step to made basic walking trajectory for FLoW robot. To determine the best Zero Moment Point (ZMP) reference, it can use the comparison of distance and time. From this comparison, the walking characteristic of FLoW robot was found and the best Zero Moment Point (ZMP) trajectory also founded. The basic walking trajectory will generate based on the best Zero Moment Point (ZMP) trajectory as a reference. In the FLoW robot, the best Zero Moment Point Trajectory was founded at distance of 14cm with difference of Zero Moment Point Reference and Real Zero Moment Point equal 0.012cm.

Unicycle mobile robot is wheeled mobile robot that can stand and move around using one wheel. It has attached a lot of researchers to conduct studies about the system, particularly in the design of the system mechanisms and the control strategies. Unlike two wheel balancing mobile robot which mechanically stable on one side, unicycle mobile robot requires additional mechanisms to keep balancing robot on all sides. By assuming that both roll dynamics and pitch dynamics are decoupled, so the balancing mechanisms can be designed separately. The reaction wheel is used for obtaining balancing on the roll angle by rotating the disc to generate momentum. While the wheeled robot is used for obtaining balancing on the pitch angle by rotating wheel to move forward or backward. A PID controller is used as balancing control which will control the rotation motor on the reaction disc and wheel based on the pitch and roll feedback from the sensor. By adding the speed controller to the pitch control, the system will compensate automatically for perfectly center of gravity on the robot. Finally, the unicycle robot will be able to balance on pitch angle and roll angle. Based on simulation result validates that robot can balance using PID controller, while based on balancing pitch experiment result, robot can achieve balancing with maximum inclination about ±23 degree on pitch angle and ±3.5 degree on roll angle with steady state error 0.1 degree.

Pens-Wheel is an electric vehicle which uses one wheel that able to balance itself so the rider does not fall forward or backward while riding it. This vehicle uses one brushless DC motor as actuator which capable to rotate in both directions symmetrically. The vehicle uses a combination of accelerometer and gyroscope contained in IMU (Inertial Measurement Unit) for balancing sensor. The controlled motion on the vehicle occurs only on the x-axis (pitch angle), in forward and backward directions. The PID (Proportional Integral Derivative) control algorithm is used to maintain the balance and movement of the vehicle. From the simulation and application in the real vehicle, the use of PID control is capable driving the vehicle in maintaining the balance condition within ±10° tilt angle boundary on flat surface, bumpy road, and inclining road up to 15° slope.

Many electrical vehicles have been developed recently, and one of them is the vehicle type with the self-balancing capability. Portability also one of issue related to the development of electric vehicles. This paper presents one wheeled self-balancing electric vehicle namely PENS-Wheel. Since it only consists of one motor as its actuator, it becomes more portable than any other self-balancing vehicle types. This paper discusses on the implementation of Kalman filter for filtering the tilt sensor used by the self-balancing controller, mechanical design, and fabrication of the vehicle. The vehicle is designed based on the principle of the inverted pendulum by utilizing motor's torque on the wheel to maintain its upright position. The sensor system uses IMU which combine accelerometer and gyroscope data to get the accurate pitch angle of the vehicle. The paper presents the effects of Kalman filter parameters including noise variance of the accelerometer, noise variance of the gyroscope, and the measurement noise to the response of the sensor output. Finally, we present the result of the proposed filter and compare it with proprietary filter algorithm from InvenSense, Inc. running on Digital Motion Processor (DMP) inside the MPU6050 chip. The result of the filter algorithm implemented in the vehicle shows that it is capable in delivering comparable performance with the proprietary one.