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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 16 Documents
 1   2 
Search results for , issue "Vol 8, No 4 (2022): Desember" : 16 Documents clear
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.
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.
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.
Classification of Leukocytes Using Meta-Learning and Color Constancy Methods Eduardo Rivas-Posada; Mario I. Chacon-Murguia; Juan Alberto Ramirez-Quintana; Carlos Arzate-Quintana
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.v8i4.25192

Abstract

In the human healthcare area, leukocytes are very important blood cells for the diagnosis of different pathologies, like leukemia. Recent technology and image-processing methods have contributed to the image classification of leukocytes. Especially, machine learning paradigms have been used for the classification of leukocyte images. However, reported models do not leverage the knowledge produced by the classification of leukocytes to solve similar tasks. For example, the knowledge can be reused to classify images collected with different types of microscopes and image-processing techniques. Therefore, we propose a meta-learning methodology for the classification of leukocyte images using different color constancy methods involving previous knowledge. Our methodology is trained with a specific task at the meta-level, and the knowledge produced is used to solve a different task at the base-level. For the meta-level, we implemented meta-models based on Xception, and for the base-level, we used support vector machine classifiers. Besides, we analyzed the Shades of Gray color constancy method commonly used in skin lesion diagnosis and now implemented for leukocyte images. Our methodology, at the meta-level, achieved 89.28% for precision, 95.65% for sensitivity, 91.78% for F1-score, and 94.40% for accuracy. These scores are competitive regarding the reported state-of-the-art models, especially the sensitivity which is very important for imbalanced datasets, and our meta-model outperforms previous works by +2.25%. Additionally, for the basophil images that were acquired from a chronic myeloid leukemia-positive sample, our meta-model obtained 100% for sensitivity. Moreover, we present an algorithm that generates a new conditioned output at the base-level obtaining highly competitive scores of 91.56% for sensitivity and F1 scores, 95.61% for precision, and 96.47% for accuracy. The findings indicate that our proposed meta-learning methodology can be applied to other medical image classification tasks and achieve high performances by reusing knowledge and reducing the training time for new similar tasks.
Terahertz Imaging Simulation Using Silicon-based Microstrip Antenna and Horn Antenna for Breast Cancer Detection Herry Tony Andhyka; Catur Apriono; Fitri Yuli Zulkifli
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.v8i4.24809

Abstract

Breast cancer is one of the most common cancers in the world that cause a lot of mortality. Early cancer detection is crucial to decrease morbidity and mortality rates worldwide. Effective treatment or early intervention is crucial before the disease becomes more incurable. This research contributes to proposing a THz imaging system for early cancer detection, especially breast cancer, by using the benefit of THz radiation. Some approaches are made differently from the previous research, such as the imaging method, the antenna type, and the material for the antenna with the expectation of producing an efficient system and better imaging results. The system consists of one microstrip antenna as a transmitter, 25 horn antenna as a receiver and a breast tissue model. All antenna is designed to meet the requirement specification. The receiver antenna will receive power from the transmitter which will vary due to the absorption of the breast model. The received power will be visualized into a 2D color image. The simulation was able to visualize an image of the breast tissue model. Received power varies from -16.280 dB to -55.241 dB which leads to different color levels to represent the model. Antenna radiation patterns also take a role to cause the phenomenon occurred that leads to differentiation of the breast tissue type. Based on the results, this research has able to simulate a THz imaging system for breast cancer. Further modification to the system can be done to improve the imaging results.
Deep Learning-Based SOLO Architecture for Re-Identification of Single Persons by Locations Rotimi-Williams Bello; Chinedu Uchechukwu Oluigbo
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.v8i4.25059

Abstract

Analyzing and judging of captured and retrieved images of the targets from the surveillance video cameras for person re-identification have been a herculean task for computer vision that is worth further research. Hence, re-identification of single persons by locations based on single objects by locations (SOLO) model is proposed in this paper. To achieve the re-identification goal, we based the training of the re-identification model on synchronized stochastic gradient descent (SGD). SOLO is capable of exploiting the contextual cues and segmenting individual persons by their motions. The proposed approach consists of the following steps: (1) reformulating the person instance segmentation as: (a) prediction of category and (b) mask generation tasks for each person instance, (2) dividing the input person image into a uniform grids, i.e., G×G grid cells in such a way that a grid cell can predict the category of the semantic and masks of the person instances provided the center of the person falls into the grid cell and (3) conducting person segmentation. Discriminating features of individual persons are obtained by extraction using convolution neural networks. On person re-identification Market-1501 dataset, SOLO model achieved mAP of 84.1% and 93.8% rank-1 identification rate, higher than what is achieved by other comparative algorithms such as PL-Net, SegHAN, Siamese, GoogLeNet, and M3L (IBN-Net50). On person re-identification CUHK03 dataset, SOLO model achieved mAP of 82.1 % and 90.1% rank-1 identification rate, higher than what is achieved by other comparative algorithms such as PL-Net, SegHAN, Siamese, GoogLeNet, and M3L (IBN-Net50). These results show that SOLO model achieves best results for person re-identification, indicating high effectiveness of the model. The research contributions are: (1) Application of synchronized stochastic gradient descent (SGD) to SOLO training for person re-identification and (2) Single objects by locations using semantic category branch and instance mask branch instead of detect-then-segment method, thereby converting person instance segmentation into a solvable problem of single-shot classification.
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.
MongoDB Based Real-Time Monitoring Heart Rate Using Websocket For Remote Healthcare Emin Guney; Gamze Agirtas; Cuneyt Bayilmis
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.v8i4.25052

Abstract

With the gradual development of Industry 4.0, the internet of things (IoT) concept has become an even more current and fundamental study topic. Consisting of devices and objects with communication capability, IoT is a network that uses internet infrastructure, especially for data collection, display, decision-making, control, and optimization of processes. Recently, patient tracking systems have become even more critical with Covid19 and have diversified in health for IoT topics such as biomedical device tracking and disease diagnosis. Within the scope of this study, a prototype of a patient tracking system was developed over the sensor in order to contribute to the biomedical field. We aimed to observe real-time heart rates using WebSockets to demonstrate its use in the medical field via the web application. Monitoring the heart rate using a WebSocket can help doctors make faster and better diagnoses. The current technology study instantly collected the patient's heart rhythm with the pulse sensor. The pulse data collected in real time was then transferred to a web platform with the NodeMCU ESP 8266 board. With this platform, the patient was monitoring in real-time. With the opportunities provided by the study, the doctor implemented an application monitors the instantaneous pulse of the patients.
Shibboleth IdP for Single Sign-On with Kubernetes and Persistent Volume Longhorn Ikhwan Alfath Nurul Fathony; Mukhammad Andri Setiawan
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.v8i4.24272

Abstract

Many organizations do not use centralized user authorization with Single Sign-On (SSO) Management to seamlessly move from one system to another. The same thing also occurred at Universitas Islam Indonesia (UII). Students were having trouble login in from one web service to another. The Board of Information Systems of UII, or Badan Sistem Informasi (BSI), implements SSO to avoid this problem. However, after BSI implemented SSO on the virtual machine, it turned out that the server load became too high. A spiking number of user logins happened in a short period. The centralized system could not handle this. The research's solution is to use a clustered service using Shibboleth IdP. The Shibboleth IdP customization can be carried out to be deployed into the Kubernetes cluster infrastructure ecosystem to meet the needs of authentication login on the business processes at UII. The Shibboleth IdP itself will be equipped with a persistent storage longhorn to support and maintain the service and avoid a single point of failure. The Kubernetes and Persistent Volume Longhorn provide a redundancy function in an application and a more flexible replication process. Inside Kubernetes, there is containerization technology. It was used to optimize the server's resources instead of replicating the application using virtual machines. With the use of centralized login by Shibboleth IdP and persistent storage longhorn, the error because of server load could be minimized. The downtime of the downed services can also be reduced. The research also proves that using Kubernetes and Persistent Volume Longhorn could help the system by preventing a Single Point of Failure using its redundancy function.
Optimized PID-Like Neural Network Controller for Single-Objective Systems Gunawan Dewantoro; Johanes Nico Sukamto; Fransiscus Dalu Setiaji
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.v8i4.25237

Abstract

The utilization of intelligent controllers becomes more prevalent as the hype of Industry 4.0 arises. Artificial neural network (ANN) exhibits the mapping ability and can estimate the output by means of either interpolation or extrapolation. These properties are sought to supersede the classical controllers. In this study, the ANN establishment was initiated by collecting dataset from the input and output of a well-known PID controller. The dataset was trained using a set of control factor combinations, including the number of neurons, the number of hidden layers, activation functions, and learning rates. Two kinds of ANN controllers were investigated, including one-input and three-input ANN. The testing was conducted under normal and uncertain conditions. These uncertainties include external disturbances, plant variations, and setpoint variations. The integral absolute error (IAE) was selected as the single objective to assess. The simulation results show that the response of three-input ANN controllers could yield smaller IAE at their best combinations under most kinds of conditions. Besides, the three-input ANN outperforms the one-input ANN both qualitatively and quantitatively. These facts might lead to a broader utilization of ANN as controllers.

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