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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Published by Universitas Ahmad Dahlan
ISSN : 23383070     EISSN : 23383062     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical (power), 3) Signal Processing, 4) Computing and Informatics, generally or on specific issues, etc.
Arjuna Subject : -
Articles 601 Documents
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Recognition of Balinese Traditional Ornament Carving Images with Convolutional Neural Network and Discrete Wavelet Transform Ni Luh Putu Kurniawati; Made Windu Antara Kesiman; I Made Gede Sunarya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24360

Abstract

Balinese carvings are less known to the public due to the lack of information about Balinese carvings. Minimum information about Balinese carvings can be overcome by utilizing advances in information technology in the field of image processing, namely the introduction of Balinese carving patterns. In the pattern recognition model of an image, there are several things that can be analyzed, such as the recognition method used, feature extraction, including the model in preprocessing to reduce noise in a Balinese carving image. In this study, the Convolutional Neural Network (CNN) was used to classify Balinese carving images combined with Discrete Wavelet Transform (DWT) in extracting image features. The introduction was made to 25 categories of Balinese carving ornaments. Tests are generated based on the level of accuracy generated in the testing process. Analysis of the results was carried out on the resulting model, namely the analysis of the combination of CNN with DWT and without DWT. Testing the data set with 212 training data and 129 testing data using all DWT channels. Based on the results of the tests that have been carried out, it is found that using the DWT extraction feature produces a higher testing accuracy value, namely 35.66% for 25 classes and 74, 42% for 3 carving classes. Meanwhile, without using DWT, it produces an accuracy value of 32.56% for 25 classes and 66.67% for 3 carving classes. In future research, it is hoped that there will be an improvement in the data set and good shooting with a balanced and adequate number for the 25 carving classes that have been obtained.
Optimize Image Processing Algorithm on ARM Cortex-A72 and A53 Rachmat Muwardi; Mirna Yunita; Harun Usman Ghifarsyam; Hendy Juliyanto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24457

Abstract

This work presents a technique to optimize processing image algorithms. The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has the mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM supported by shared memory, is presented with implementation details. The target platform chosen is the NanoPi M4V2. It has a dual-core and quad-core architecture with an ARM Cortex-A72 and Cortex-A53. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template-matching tasks such as face recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core, which runs a popular operating system such as Linux. The algorithms are tested on a variety of images, and performance results are presented, measuring the speedup obtained due to dual-core and quad-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks.
Detecting the Same Pattern in Choreography Balinese Dance Using Convolutional Neural Network and Analysis Suffix Tree I Komang Hendra Trinium Jaya; Made Windu Antara Kesiman; I Made Gede Sunarya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24461

Abstract

The Balinese dances that are popular today were created by maestros who have existed since time immemorial. To develop the dances made by the existing maestro, one must know the characteristics of each dance based on the motion used. The help of digital image processing and string algorithm analysis methods will help to determine the characteristics of a dance. The algorithm used for dance analysis is the Suffix Tree, where the suffix tree is one of the algorithms that can be used to find patterns from input strings. The string to be analyzed is a series of codes performed by the classifier. The classifier used is Convolutional Neural Network. This method uses an image as its input, which will later perform convolution operations and perform a full-connected layer. The results were obtained using the Convolutional Neural Network method with Alexnet architecture as the classification and confusion matrix to calculate the level of accuracy of the test set, the best accuracy for the head is by using parameter learning rate 0.001, epoch 150, and RGB color space obtained 95% accuracy, 88% precision, 78% recall, and 82% f1-score. For the full body, using a learning rate of 0.01, epoch 150, and RGB color space, the accuracy is 85%, precision is 79%, recall is 64%, and f1-score is 69%. For the legs, using a learning rate of 0.001, epoch 150, and RGB color space, the accuracy is 92%, precision is 84%, recall is 59%, and f1-score is 65%. The results of the suffix tree analysis between codes that use ground truth and classification results have similar values, although the results of the movement patterns obtained by the suffix tree algorithm have not varied, which is dominated by class A because class A is the dominant class in each dance.
Fast and Accurate Voice Biometrics with Deep Learning Algorithm of CNN Depthwise Separable Convolution Model and Fusion of DWT-MFCC Methods Haris Isyanto; Ajib Setyo Arifin; Muhammad Suryanegara
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24515

Abstract

Theft of private data became a threat of crime in cyberspace. This issue was in line with rapid development of data technology, especially online transactions. To attenuate this problem, voice biometrics was developed as an answer to keep up security identity. This paper develops the voice biometric framework based on Convolutional Neural Network Depthwise Separable Convolution (DSC) model and the fusion of Discrete Wavelet Transform (DWT) and Mel Frequency Cepstral Coefficients (MFCC). Such a scheme has targeted to increase the high accuracy, to reduce the burden of high computational costs and to speed up the performance of classification process time. We conduct three testing performance, i.e. voice Biometric Training Performance, speaker Recognition Performance (”Who is speaking?”), and Speech Recognition performance (”What keyword is uttered?”).  For each of the testing, the results are compared with CNN Standard performance. The training results has shown that CNN DSC model has reduced the amount of training parameters to 364,506, leading to accelerate the performance of training process time to 5.12 minutes. The results of speaker recognition performance has attained the best performance with an accuracy 99.25%, precision 97.14%, recall 98.17% and F1-score 97.28%. The results of speech recognition performance has been able to improve the best performance with accuracy 100%. It can be concluded that CNN DSC with the fusion of DWT- MFCC has outperformed the CNN Standard. The framework can be applied for the identification and verification of user voices accurately, quickly and efficiently for any applications requiring better security performance.
Fiber Optic Attenuation Analysis Based on Mamdani Fuzzy Logic in Gambir Area, Central Jakarta Yuliza Yuliza; Ninda Sari; Rachmat Muwardi; Lenni Lenni; Yosy Rahmawati
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24549

Abstract

In this study, the authors conducted an analysis of the quality of fiber optic network maintenance based on attenuation value and maintenance time using fuzzy Mamdani logic and simulated using Matlab software, to improve accuracy in drawing conclusions on maintaining quality. This study uses a quantitative method, in which the author obtains a summary of customer data from PT. Telkom Indonesia in a period of 4 months of observation from August to November 2021. In August there were 776 customers, in September there were 362 customers, in October there were 359 customers, and in November 445 customers who underwent Indihome fiber optic cable maintenance. The test results with the centroid method with an input Handling Time of 1.5 hours and an Attenuation of 15 dB, then the output Repair Quality is 5.5 or categorized as Good. The greater the attenuation value generated, the more time it takes to maintain the IndiHome internet network disturbance. This is due to the many technical maintenance of fiber optic cables carried out by technicians to adjust for damage/trouble in the field. It is expected that maintenance can be carried out routinely in order to avoid fatal internet disturbances on the customer's side, and maximize maintenance time according to the dosage determined by the company, which is less than 3 hours, taking into account the work performance of technicians and also the quality of maintenance.
Trajectory Tracking and Collision Avoidance on Smart Wheel Chair Munawar Agus Riyadi; Syuja Rizqullah; Sumardi Sumardi; Teguh Prakoso
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24550

Abstract

There have been many developments of wheelchairs as mobility aids, including electric wheelchairs. Wheelchairs sometimes still require manual steering. Therefore, in this research, a smart wheelchair is developed that can move automatically to the destination position from a predetermined position with a trajectory tracking system. The system deploys the odometry method, orientation angle using the output of the IMU-9DOF sensor with Kalman filter, and collision avoidance to avoid collisions with obstacles in front of it. The use of the Kalman filter improves the angle output that is close to the reference. In the trajectory tracking test, the wheelchair can approach the given reference position with a maximum error of 20 cm for the x-axis and 2 cm for the y-axis. The wheelchair collision avoidance test has been able to avoid collisions, as it successfully detects an obstacle less than 40 cm and avoids the collision correspondingly.
Raspberry Based Hand Gesture Recognition Using Haar Cascade and Local Binary Pattern Histogram Helfy Susilawati; Fitri Nuraeni
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24643

Abstract

Many companies and even public institutions for civil servants currently use photo-taking for the attendance. However, this strategy is still considered ineffective since the employees still can hack the attendance by making their own photos and put them in their desks. Therefore, an alternative that can complement the current face detection method is highly needed so that the employee’s attendance can be directly monitored. One of the methods that can be used to detect the attendance is hand gesture detection. This research aims to detect hand gestures made by the employees to ensure whether they really come to work or not. This research make  the chance for manipulation using photo or fake GPS is quite small. For the purpose of hand gesture recognition, this study utilized Local Binary Pattern Histogram algorithm. The hand gesture image was first taken using a raspberry pi camera and then processed by the device to examine whether it matches the registered ID or not. The results showed that ID recognition by using hand gestures is detectable. The number recognition in hand gestures includes numbers 1 to 10. The test results showed that for 5 trials, the average time required for reading hand gestures using a laptop was 9.2 seconds, while that of using raspberry was 14.2 seconds. The results of this research show that the system has not been able to distinguish which hand is read first, so numbers that have the same number are considered the same, such as 81 and 18. So, the motion reading using a raspberry takes longer than that of using a laptop because the laptop's performance is higher than that of a raspberry and system cannot distinguish between numbers consisting of the same number.
Control Improvement of Low-Cost Cast Aluminium Robotic Arm Using Arduino Based Computed Torque Control Petrus Sutyasadi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24646

Abstract

Gravity causes non-linearity in position control of an articulated industrial robotic arm. Especially for a joint position control of a robot’s shoulder and elbow that works parallel with the gravity direction. To overcome the problem, Computed Torque Control algorithm was implemented. This algorithm linearized the feedback, so a regular linear Proportional Derivative controller can be implemented. The contribution of this research is to find an effective controller to control a heavy weight low-cost robotic arm link/body using low-cost controller such as Arduino. A Computed Torque Control was implemented to control the shoulder joint of an articulated robotic arm. This joint is the most affected joint by the gravity. It works along the vertical plane, and loaded by the rest of the arm and the robot’s load. The proposed controller was compared to a Proportional Integral Derivative (PID) Controller and a Cascade PID Controller. The experiment showed that the Computed Torque Controller can control the position of the arm properly both in the direction along or against the gravity. A linear PID controller could not bring the arm to the set point when it moves against the gravity, but it works well when the arm moves in the opposite direction. A Cascade PID controller has an overshot when the arm moves along the gravity. But it works properly when it moves up against the gravity. A Computed Torque Control works well in both directions even in the presence of gravity force because it includes the gravity on its algorithm.
Compensation to Fulfill Voltage Drop Security in Medium Voltage Feeders Hermagsantos Zein; Sri Utami; Siti Saodah; Conny Kurniawan Wachjoe
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24743

Abstract

Increasing the load or expanding the feeder can increase the voltage drop. In addition, the greater the flow of reactive power on the line, the worse the voltage drop. On the other hand, the voltage must meet certain safety limits, and one way to correct the voltage drop is to apply for compensation. However, calculating the voltage drop through the power flow and the measurement methods is difficult to apply because it is necessary to determine the value of the amount of load on each node. This paper will propose a simple method that is convenient to apply to determine the compensation needed to maintain voltage quality in medium voltage feeders. The methodology used is a current source approach that functions as a variable. Then the current flow along the channel is assumed as a linear function so that the load center point is obtained according to the feeder configuration and load capacity. The simulation results on the 21-node feeder assuming a power factor of 0.8, show that the voltage drop improvement is quite effective with compensation. For example, at a 150 A current source, with 30 A compensation, the voltage drop can be increased from 4.45% to 3.98%. Furthermore, by applying for compensation, it is possible to expand the load to a source current of 165 A with a compensating current of 80 A.
Saving Product Using Blockchain for E-BMT Platform Taufiq Gilang Adhitama; Anggunmeka Luhur Prasasti; Ali Fahmi Perwira Negara
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24753

Abstract

Baitul Maal Wa At Tamwil (BMT) is a sharia financial institution that provides savings and loan services in accordance with the social, cultural, and economic needs of rural communities, especially in agricultural and plantation communities. The current data management is still using manual recording and a centralized server which can cause fraudulent financial reports and creates a lack of credibility between BMT and its customers. The research method is to decentralize the application data system by using blockchain technology, then replacing the conventional database to blockchain system. The simulation shows that the e-BMT application are connected to blockchain network as intended, users can use metamask to interact with the Ethereum network, the blockchain implementation on e-BMT application has run according to expectations with a 100% success rate with the average transfer time on two devices of 9.47 seconds and 12.13 seconds. While the results of data entry time on two devices obtained an average of 9.96 seconds and 37.09 seconds. While the blockchain implementation on e-BMT could provide access to every user so that each entity could confirm the validity of the transactions, the size of the transactions, and other data recorded on the blockchain without having to develop an integrated database system. The research contributes in two aspects, first, we develop the distributed blockchain system using public Ethereum  blockchain network integrated with with popular e-wallet such as metamask, provides easy access for both customers and BMT parties who are connected to the network so that the recorded data can be accessed by anyone, and second, the application of blockchain technology to BMT is capable to interact with users as it is built on a website platform with RESTful API.

Page 56 of 61 | Total Record : 601

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