Journal IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)

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M Saiful Haris, Andi Dharmawan, Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.24220

Abstract:The function of camera gimbal control system that use in this research is to serves with the angle changes that occur due quadrotor maneuver. The PID control with tuning classical method has weakness, which is the PID variable not independently adjust to the environment, thus proposed using PID fuzzy control.Gimbal camera used in this study has a mechanical design with two joint (pitch and roll) and the BLDC motor as actuator. The angle changes that occur in the pitch and roll axis will be a feedback system. Then, fuzzy logic will tune the PID variable based on that feedback.Results of testing the system on 2-axis gimbal camera shows the PID fuzzy control generates better response in parameter risetime, overshoot, and settlingtime compared with PID control. Error input value range of [-30° 30°] and delta error of [-10° 10°] on the pitch and roll axes. The range of the output value for the pitch axis is, Kp at [40.2 46.2], Ki at [10.7 20.7], and Kd of [0.05 to 0.15]. The range of the output value for the roll axis is, Kp at [6.4 16.4], Ki at [17.3 to 27.3], and Kd at [0.08 0.16]. Speed response speed of pitch axis is 0.12 second and the roll axis is 1.07 seconds.
Muhammad Irfan, Bakhtiar Alldino Ardi Sumbodo, Ika Candradewi
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.18260

Abstract:The evolution of video sensors and hardware can be used for developing traffic monitoring system vision based. It can provide information about vehicle passing by utilizing the camera, so that monitoring can be done automatically. It is needed for the processing systems to provide some information regarding traffic conditions. One such approach is to utilize digital image processing.This research consisted of two phases image processing, namely the process of detection and classification. The process of detection using Haar Cascade Classifier with the training data image form the vehicle and data test form the image state of toll road drawn at random. While, Multilayer Perceptron classification process uses by utilizing the result of the detection process. Vehicle classification is divided into three types, namely car, bus and truck. Then the classification parameters were evaluated by accuracy. The test results vehicle detection indicate the value of accuracy is 92.67. Meanwhile, the classification process is done with phase trial and error to evaluate the parameters that have been determined. Results of the study show the classification system has an average value of the accuracy is 87.60%.
Gong Matua, Triyogatama Wahyu Widodo, Mitrayana Mitrayana
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.18294

Abstract:Photoacoustic tomography is a system of utilization of the photoacoustic effect is used to obtain image-processing with high resolution and contrast. The purpose of studies is to design a mechanics xy-stage and implement control systems in laser modulation. The system design consists of designing hardware and software. Hardware design includes the design of optical devices and the design of electronic devices using the Arduino microcontroller. Software design using Arduino IDE, Audacity and Matlab. Recording test results showed that the photoacoustic signal peaks on the recording with the samples was higher than the recording unsampled. Based on the test mileage xy-stage mechanical movement using a type of bipolar stepper motor Nema 17, earned mileage (4.046 ± 0.005) mm for the motor movement for one revolution and it takes 25 steps to obtain the distance as far (0.50 ± 0.05) mm used on scanning process. Image-processing has been able to show the results of the image corresponding to the scanning area, the process is carried out on the object-imaging soft tissues such as the pancreas with cell tumor tissue.
Khalaqas Hakiim, Andi Dharmawan, Faizah Faizah
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.23937

Abstract:Quadrotor is square-form unmanned aerial vehicle (UAV) type with four motor in each arms. Quadrotor has ability to take-off and landing vertically. This research designs and creates a system that capable to stabilize the quadrotor flight also able to maintain roll, pitch and yaw angle using PID controller optimized by genetic algorithm, one of evolutionary algorithms.PID is a common applied controller including to control the quadrotor. Tunning or setting PID parameter process is needed to obtain fit PID parameters. Tunning is very important to reach quadrotor flight stability. This research applies Ziegler-Nichols tunning to obtain PID parameters. Then the PID parameters will be a reference for genetic algorithm optimization process to obtain the suitest PID parameter to control roll, pitch ,and yaw angle.Optimization process result show quadrotor controller capable to reach stability with steady state error for pitch angle in range 2,34 degree conterclockwise to 3,37 degree clockwise, for roll angle in range 2,99 degreee counterclockwise to 2,27 degree clockwise, and for yaw angle in range 8,39 degree counterclockwise to 3,89 degree clockwise.
Setyo Swasoko, Abdul Rouf
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.24276

Abstract:NDT Research conducted to detect any defects on a solid materials. This method is done because not damage the object being tested. Various methods of NDT research also studied, one of which is a multi-transmitter. Multi-transmitter more efficient in scanning objects defective because a more extensive range of sensors. Prioritizing advantages compared with other pulse sources such as AFG, including portable, small radiation, the price relatively cheaper, variety of frequencies that can be generated, and smaller power supplies will be used microcontroller as signal generator.With this concept, generating ultrasonic waves 40kHz emitted by three transmitter input from serial PC to microcontroller and converted into analog signal AD9850 module. Amplitude of the frequency of AD9850 strengthened using LM386, and strengthened again using transfomator ferrite core. And choose sensor, used switches. From research conducted by a few conclusions. Maximum of output voltage AD9850 module is 1.04 V. Maximum output voltage of LM386 is ± 14 V and maximum voltage output of ferrite transformator is ± 170 V. The effective transmitter is SRF04 and maximum input voltage is ± 60 V. Amplitude of wave will be smaller if reflection distance farther, otherwise amplitude increases if the reflection distance is closer.
Ariesa Budi Zakaria, Andi Dharmawan
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.25503

Abstract:Quadrotor is one of UAV (Unmanned Aerial Vehicle) rotary wing aircraft type. Quadrotor has been widely used for various needs to military or civilian. Quadrotor can be operated manually by remote or autonomously. One of the difficulties of quadrotor operations is to avoid the obstacles before autonomous flying towards destination point. Therefore, an obstacle avoidance control system is required on quadrotor systems. Linear Quadratic Regulator is a control system that produces an input value system from state value and feedback. State value is produced from translation and rotation. That input value then converted into pulse width modulation to control the speed of the brusless motor, and it's used to do obstacles avoidance manouver.This method might reduce overshoot on the system and make response time (rise time) arrived faster than other methods. The obstacle avoidance system requires small overshoot value and an appropriate response time to avoid frictions or collisions. The result of this research is the rise time to avoid obstacles that reached 4,7 second with flight speed of 0,6 m/s and turns for roll angle equal to 14,27 °, pitch equal to 13,26 °, and yaw equal to 9,87 ° while avoidance maneuvering obstacles.
Eviyan Fajar Anggara, Triyogatama Wahyu Widodo, Danang Lelono
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.25489

Abstract:E-nose is an instrument used to detect odor. E-nose developed with Bidirectional Associative memory (BAM) algorithm has advantages in processing incomplete input data and noise. The purpose of the study was to implement the BAM algorithm to detect pure beef among samples of beef, pork, and mixed meat from aroma with e-nose.Data processing of the sample reading results begins by performing the baseline manipulation process, then do difference and integral feature extraction for the data. The characteristic extraction data will be converted into bipolar matrix patterns (1 and -1) so that the threshold data is needed to be able to determine the feature extraction data to be bipolar. Data that have become bipolar matrices will be used as test and reference data in the program with cross validation testing to obtain the percentage of truth of meat detection using BAM based e-nose.Detection of meat with BAM using integral feature extraction with bipolar the first way yields a 14,8% success percentage and the second way bipolar yields a 15,7% success rate. The extraction of characteristic difference with bipolar the first way yields a success percentage of 17,3% and the second way bipolar yields a success rate of 16,4%.
Tri Kuntoro Priyambodo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.18238

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Zaki Hamizan, Raden Sumiharto
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.18240

Abstract:One of the algorithm for aerial image stitching system is SURF (Speeded Up Robust Features). It is a robust algorithm which is invariant to image scale, rotation, blurring, illumination, and affine transformation. Although SURF has good performance, some of the detected keypoints are not always considered as necessary keypoints . As a result, these unnecessary keypoints are needed to be eliminated to decrease computation time.The proposed system uses SURF detector in the detection process. The data reduction method will eliminate couple of keypoints which have near distance each other. Next, the keypoints will be described by SURF descriptor.The description Results further matched using FLANN. The next step is the search pattern with RANSAC homography matrix and stitch the picture to accumulate keypoints using warpPerpective.Stitching system are tested with some variations, such as scale variations, rotation variations, and overlap variations on the image. Based on the result, the proposed Data Reduction method has optimum value of minimal radius from 40 pixels to 100 pixels. The stitching process is still working with up to 90% keypoint number reduction. Average computation time using data reduction method are 39,41% faster than without data reduction method.
Catur Atmaji, Zandy Yudha Perwira
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), Volume 7; doi:10.22146/ijeis.22893

Abstract:In this study, observation on the differences in features quality of EEG records as a result of training on subjects has been made. The features of EEG records were extracted using two different methods, the root mean square which is acquired from the range between 0.5 and 5 seconds and the average of power spectrum estimation from the frequency range between 20 and 40Hz. All of the data consists of a 4-channel recording and produce good quality classification on artificial neural network, with each of which generates training data accuracy over 90%. However, different results are occured when the trained system is tested on other test data. The test results show that the two systems which are trained using training data with object with color background produce higher accuracy than the other two systems which are trained using training data with object without background color, 63.98% and 60.22% compared to 59.68% and 56.45% accuracy respectively. From the use of the features on the artificial neural network classification system, it can be concluded that the training system using EEG data records derived from the visualization of object with color background produces better features than the visualization of object without color background.
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