IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)
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Pengukuran Jarak Lubang Pada Benda Padat Menggunakan Sensor Ultrasonik
Get PDF The process of making solid object in general, not print with good so that holes can’t be seen directly visually. NDT (Non Destructive Testing) is a method for detecting holes and the quality of solid objects without damaging solid object one uses ultrasonic to detect holes a solid object which there are on internal solid object. This research aims to design an instrument for measuring distances holes of solid body using ultrasonic sensor and oscilloscope.The method used for the testing is the echo pulse which produce output of the wave amplitude shown oscilloscope. Function generator as input pulses 40 KHz to circuit amplifier then the transformator strengthened and continued to ultrasonic transmitter. Transmitter generated pulse to object and the pulse has reflection because it has holes an internal object. The reflection pulse is received by the receiver ultrasonic sensor and amplified by signal amplifier circuit, then the wave displayed on oscilloscope. The research showed that the smaller distance holes testing the wave amplitude obtained becomes larger and when the distance holes a solid object is longer the attenuation coefficient value the greater worth. The value of measurement error in using a tool value made author of 5 %
Pengembangan Hidung Elektronik untuk Klasifikasi Mutu Minyak Goreng dengan Metode Principal Component Analysis
Get PDFThe existence of cooking oil which is mixed with dangerous material is very difficult to be detected by human olfactory system yet can be detected by sophisticated equipment. However, the equipment is very expensive and require an expert to operate it.Static system of electronic nose based on unselected gas sensor array has been built for classifying pure cooking oil’s odour and mixed cooking oil’s odour. Sensor array consist of sensor MQ-9, TGS-2600, MQ-2, TGS-2620, and TGS-822 along with a heat exchanger system that can reduce the temperature of sample’s odour. The sample chamber and sensor chamber are made from stainless steel with cylinder shape. The system tested by boiling the sample consist of each pure cooking oil form both palm and coconut oil with its mixture such as used lubricant, candle, and diesel fuel up to 300 0C to realese its odour. After the odour has been detected by electronic nose the next step is to classifying the data with PCA method.The result show that the response of sensor’s output is stable and the output of score plot from each pure cooking oil’s data from both palm and coconut oil can be well-classified from the mixed cooking oil
Klasifikasi Sel Darah Putih Berdasarkan Ciri Warna dan Bentuk dengan Metode K-Nearest Neighbor (K-NN)
Get PDFThe traditional procedure of classification of blood cells using a microscope in the laboratory of hematology to obtain information types of blood cells. It has become a cornerstone in the laboratory of hematology to diagnose and monitor hematologic disorders. However, the manual procedure through a series of labory test can take a while. Thresfore, this research can be helpful in the early stages of the classification of white blood cells automatically in the medical field.Efforts to overcome the length of time and for the purposes of early diagnose can use the image processing technique based on morphology of blood cells. This research aims to classify the white blood cells based on cell morphology with the k-nearest neighbor (knn). Image processing algorithms used hough circle, thresholding, feature extraction, then to the process of classification was used the method of k-nearest neighbor (knn).In the process of testing used 100 images to be aware of its kind. The test results showed segmentation accuracy of 78% and testing the classification of 64%
Purwarupa Sistem Integrasi Metadata Foto Udara Dengan Data Sistem ADAHRS
Get PDFThis research was done by implementing aerial photographs metadata integrated system with ADAHRS data system. Photos and ADAHRS data were taken along using the camera and ADAHRS devices were installed on UAV. Data were taken from ADAHRS consisted of date, time, air speed, GPS latitude-longitude, altitude, temperature, air pressure, roll, pitch, and yaw.The method in the system included custom tag configuration, extracted metadata, the synchronisation and integrated data between ADAHRS and photo metadata. Configuration, extraction and integration process were done using ExifTool. Datestamp and timestamp in photo metadata and ADAHRS data were used as a parameter of integrating data on synchronisation.The systematical experiment was done by test on the effect of image resolution and number of photos to the duration of the whole process. This system was able to integrate ADAHRS data from image resolution, were 230 pixels x 1536 pixels, 1920 pixels x 1080 pixels, 1280 pixels x 720 pixels, and 848 pixels and 480 pixels. Amount of time average of process were 3,936 seconds/100 photos, 7,454 seconds/200 photos, 11,156 second/300 photos, 14,740 seconds/400 photos, and 18,460 seconds/500 photos. This system can be able to make a backup from extended version and retain the originality of photo metadata
Deteksi Copy Move Forgery Pada Citra Menggunakan Exact Match, DWT Haar dan Daubechies
Get PDFCopy-Move Forgery is a special type of image forgery, in which a part of a digital image is copied and pasted to another part in the same image in order to cover an important image feature. This research developed a system to detect copy move forgery in digital image. The system is intended to help the user determine whether an image is authentic or already contained a copy move object, and if the image already contains copy move object, the system can determine in which section the copy move object is located. Copy move forgery detection system discussed in this research, was developed by using Exact Match, DWT Haar, DWT db2 and DWT db4 using blocks of 4 x 4, 8 x 8 and 16 x 16. Users can use the system by using the digital image as input. The output of the system is the information about the area detected as a copy move forgery along with areas suspected of being false match.The final result is shown in the form of accuracy, the area of the false match and execution time. Based on the test results, the accuracy of Exact Match method for blocks of 4 x 4, 8 x 8 and 16 x 16 is better than the DWT, although exact match have an bigger false match area. Accuracy of DWT Haar, DWT db2 and DWT DB4 depending on the copy move area on the image. Block 4 x 4 has a false match area larger than the block 8 x 8 and 16 x 16. The execution time depends on the size of the block, the larger the block, the longer the time of execution.
Identifikasi Tahu Berformalin dengan Electronic Nose Menggunakan Jaringan Syaraf Tiruan Backpropagation
Get PDFDuring this time to identify pure and formalin tofu based on color and aroma involving human taster. But this tofu tester still has weaknesses such as subjective. Besides that, the standard chemical analytical methods requires a high cost and need expertise to analyzing it. Basically aroma of tofu is determined by volatile compounds such as heksanal, ethanol, and 1-hexanol, while aroma of formalin tofu is determined by volatile compounds such as OH, CO, and hydrocarbon. Electronic nose based on unselected gas sensor array has the ability to analyze samples with complex compositions that can be known characteristics and qualitative analysis of the samples. Stimulus aroma is transformed by electronic nose into fingerprint data then it is used by feature extraction process using the differential method. The results of feature extraction is used to process the back propagation neural network training to obtain optimal parameters. The parameters have been optimized is then tested on a random tofus. Based on test results, ANN-BP can identify samples with 100% accuracy rate so that the identification of a pure tofu and tofu formalin with electronic nose using back propagation neural network analysis has been successfully carried out
Pemodelan Generator Uap Berbasis Jaringan Saraf Tiruan dengan Algoritme Pelatihan BPGD-ALAM
Get PDFSteam generator is unit plant which has nonlinear and complex system with multiple-input-multiple-output (MIMO) configuration which is hard to be modeled. Whereas, steam generator model is very useful to create simulation such as operator training simulator (OTS). The purpose of this research is to obtain model of steam generator which has 8 output parameters and 9 input parameters based neural network (NN) with BPGD-ALAM training algorithm. Data had been taken from steam generator of PT. Chevron Pacific Indonesia, Duri and it is divided into three types, i.e training data, validation data and testing data. Training data was used to obtain model for each ouput through training process. Verification model is also done for each epoch using validation data to monitor training process whether overfitting occurs or not. Eight NN model of each output which is obtained from training and verification, is tested using testing data for getting its performance. From the reseach results, architecture of neural network models are obtained with various configuration for each output with RMSE value under 9.71 %. It shows that model which has been obtained, close with steam generator real system
Pengoreksi Nada Menggunakan Mikrokontroler untuk Meningkatkan Kualitas Suara pada Biola
Get PDF Violin is a frteless musical instrument so that carefulness of the player affects the tone quality. For begineers, it tooks a lot of time for fingering process, so if they are not skillfull enough it will generate many out-of-tune pitches which uncomfortable to be heard. For clearing this issue, it needs an equipment for generating in-tune pitches while the violinist is playing-live.System is made using sound sensor for receiving the wave of the violin, turned it out to electric signal and then detecting its pitch value – reading it as the interval of the main frequency – and then playing desired in-tune audio data of violin tones. The main process is done by microcontroller supported by audio shield. The output is in-tune audio data which played through speaker.System achieved 100% accuracy while using pure sinusoid wave tones for testing. System achieved 17,33% accuracy while using pre-recorded violin tones for testing. System achieved 10,66% accuracy while using live-played violin tones for testing
Sistem Kontrol Torsi pada Motor DC
Get PDFThe use of a DC motor in the industrialized world is very important. Speed of DC motor and torque of DC motor greatly affects quality and quantity of product. Therefore, we need control system of a DC motor that can be set speed and torque. The number of industry players complained about damage to the DC motor because transported load torque of motor exceeds capabilities of torque of DC motor. Based on these problem, we should make torque control system in DC motor.Torque control system made by regulating armature current of DC motor separately excited with current field constant condition. Torque control system consist of speed control and current control, namely control system two level. Output signal speed control system will be the current reference signal.Testing has been carried out with a maximum load of 3690 grams and a nominal current of 0.8 A or nominal torque of 0.323 Nm. The results shows the effective torque of motor is able to be set in the range of 0.182 Nm - 0,243 Nm. Expected to value effective of regulated torque is able to withstand infinite heavy loads without damaging the motor
Purwarupa Sistem Prediksi Luas dan Hasil Panen Padi suatu Wilayah menggunakan Pengolahan Citra Digital dengan Metode Sobel dan Otsu
Get PDFArea and paddy crop yield prediction system of an area using image processing by Sobel Otsu’s method is one of system that utilize aerial photo data for measuring area and prediction of its crop yield. Otsu’s method is used to thresholding process and Sobel’s method is used to detect paddy field’s edges that will calculate its area. Then filtering process so that the scanning process white pixels are counted only exist in the desired region. After the amount of white pixel(s) is obtained, their amount is multiplied with the scale that obtained from calibration process and crop yield prediction (kg/m2). Detection of yellow paddy color that ready-to-harvest is successfully performed by processing the HSV color, which is then detected by thresholding HSV. At the time of testing with variety of paddy color, the detected paddy color is the paddy color ready-to-harvest, which is brownish yellow that represented by white pixels, and will be used then to predict its area and crop yield. Thereafter, accuracy calculation test resulting in different error levels in different paddy fields. Error in testing of this system are 3,1 %, 8,7%, 4,9% dan 248%. The highest error value is caused by excessive exposure of light, with the result that the green color on paddy is detected by the system as yellow and some areas are covered by trees that, thereby reducing paddy fields area calculation