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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 505 Documents
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Comparison of IDW and Kriging Interpolation Methods Using Geoelectric Data to Determine the Depth of the Aquifer in Semarang, Indonesia Brilliananta Radix Dewana; Sri Yulianto Joko Prasetyo; Kristoko Dwi Hartomo
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23260

Abstract

Several areas in Semarang City have been unable to get a clean water supply through the Local Water Company (PDAM) channel. One of the solutions that can be done to overcome this problem is by utilizing groundwater, which can be obtained by building a deep well made to obtain rock layers that can accommodate and drain groundwater (aquifer layer). To find out the approximate depth of the aquifer layer, it is necessary to conduct a preliminary investigation before drilling. There are so many methods that can be done, and one of them is by using the geoelectric method. After using the geoelectric method, we can determine the distribution of the depth of the aquifer in Semarang City by using interpolation analysis. In this study, the IDW and Kriging interpolation methods were used. The two methods were then compared to show the difference in the distribution of aquifer depths in areas that lack clean water using the two interpolation methods above. Besides that, we are using RMSE and MAPE analysis to find the error rate of the two methods. The results obtained were the RMSE of the IDW and Kriging methods amounting to 5,829 and 5,433, and the MAPE results were 10.90% and 10.34%. Based on this, the Kriging method tends to have better results when interpolating using geoelectric data. With this research, it is hoped to provide knowledge to determine the most suitable interpolation method used in determining the depth of the aquifer and also can be used as an illustration of the depth of the aquifer in the area that lacked clean water in Semarang City, so that it can be used as a reference in estimating the design of deep good development more accurately.
K-Means Segmentation Based-on Lab Color Space for Embryo Detection in Incubated Egg Shoffan Saifullah; Rafal Drezewski; Alin Khaliduzzaman; Lean Karlo Tolentino; Rabbimov Ilyos
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23724

Abstract

The quality of the hatching process influences the success of the hatch rate besides the inherent egg factors. Eliminating infertile or dead eggs and monitoring embryonic growth are very important factors in efficient hatchery practices. This process aims to sort eggs that only have embryos to remain in the incubator until the end of the hatching process. This process aims to sort eggs with embryos to remain hatched until the end. Maximum checking is done the first week in the hatching period. This study aims to detect the presence of embryos in eggs. Detection of the existence of embryos is processed using segmentation. Egg images are segmented using the K-means algorithm based on Lab color images. The results of the image acquisition are converted into Lab color space images. The results of Lab color space images are processed using K-means for each color. The K-means process uses cluster k=3, where this cluster divides the image into three parts: background, eggs, and yolk. Egg yolks are part of eggs that have embryonic characteristics. This study applies the concept of color in the initial segmentation and grayscale in the final stages. The initial phase results show that the image segmentation results using k-means clustering based on Lab color space provide a grouping of three parts. At the grayscale image processing stage, the results of color image segmentation are processed with grayscaling, image enhancement, and morphology. Thus, it seems clear that the yolk segmented shows the presence of egg embryos. Based on this process and results, the initial stages of the embryo detection process used K-means segmentation based on Lab color space. The evaluation uses MSE and MSSIM, with values of 0.0486 and 0.9979; this can be used as a reference that the results obtained can detect embryos in egg yolk. This protocol could be used in a non-destructive quantitative study on embryos and their morphology in a precision poultry production system in the future.
Modeling and Analysis of Percentage Depth Dose (PDD) and Dose Profile of X-Ray Beam Produced by Linac Device with Voltage Variation Bilalodin Bilalodin; Farzand Abdullatif
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23622

Abstract

The Percentage Depth Dose (PDD) and dose profile of X-Ray output from a LINAC therapy device have been modeled and analyzed. The research was conducted by simulation method through the use of Particle and Heavy Ion Transport code System (PHITS) program. The LINAC therapy device modeled in this work refers to the Siemens Primus LINAC therapy device, which is operated at 6 MV, 10 MV and 18 MV voltages. Determination of PDD was carried at a depth of 0-30 cm and dose profile at a depth of 0-20 cm in a water phantom, placed at 100 cm from the source, which is exposed to a radiation field area of 10×10 cm2. Results from the modeling of the LINAC therapy device agrees with the actual X-ray apparatus and has produced Bremsstrahlung X-ray. It was found from the analysis of the PDD curve that the maximum doses are at the depth of 1.5 cm, 2.5 cm and 3.4 cm. The value of build up factor for each LINAC voltage agrees with the reference. Additionally,  the results of the analysis of the doses profile suggest that the X-ray output has good degree of uniformity. The flatness of dose profile occurs at the depth of 20 cm with percentage value of flatness at 1.6 %, 1.9 % and 1.2 %. The flatness values are all less than 2%. The flatness values shows ≤ 2 % deviation from reference value, which is below the tolerance range required in a measurement.
Tuberculosis Detection in X-Ray Image Using Deep Learning Approach with VGG-16 Architecture Suci Aulia; Sugondo Hadiyoso
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23994

Abstract

Tuberculosis (TB) is a chronic disease still the main problem in Indonesia. However, this disease can be cured with drugs at a particular time after the patient is detected as having TB. TB diagnosis or screening can be made through x-ray imaging of the chest cavity by a radiology specialist. The Mantoux test can then be used to confirm the diagnosis.  X-ray images often have varying contrasts that lead to true negatives or false negatives. Whereas generally, a chest x-ray is the initial examination of TB. Error detection will have a fatal impact on treatment therapy. Therefore, this study proposed a system for TB detection based on x-ray images using deep learning. The system developed uses a Convolutional Neural Network (CNN) with the VGG-16 architecture. In the performance test stage, 700 normal and 140 TB chest x-ray images were used. The simulation results show that the proposed system can classify normal and TB lungs with an accuracy of 99.76%. The highest accuracy is achieved using batch size=50. This system is expected to assist radiology in detecting tuberculosis on X-Ray images of the lungs. The contribution of this study is to build a machine learning model for TB detection and optimization of model parameters to get the best accuracy.
UDP Pervasive Protocol Design and Implementation on Multi Devices using MyRIO Mochammad Hannats Hanafi Ichsan; Rizal Maulana; Octavian Metta Wisnu Wardhana
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23835

Abstract

Pervasive Computing is one of the practical computing applications to facilitate computer operations by minimizing human interaction with computers. Pervasive Computing has been developed using UDP protocol to recognize the other devices without manual configuration. NI MyRIO device is one of the most reliable devices for the prototyping process. However, there are still not many implementations of data transmission using specific protocols. And the direction of use for smart homes or smart environments is still not widely done. This research contribution implemented Pervasive UDP protocols on PC devices and two NI MyRIO using LabVIEW programming language. UDP protocols are used because they do not require a handshake to recognize another device to reduce delays and have smaller data sizes due to the absence of recognition fields and sequence fields. Each device uses a dual-state machine system design that has a function to detect other devices automatically and act as an application to use the address of another device. PC represents the host, and MyRIO represents the client. Using the same state machine to detect all devices can recognize more than one device on the same network. The obtained test results show that all functional testing scenarios succeeded 100%. The discovery time is averaged at 0.202754 seconds for First MyRIO as First Client and 0.303201 seconds for Second MyRIO as Second Client. The delay in sending data from the host to the client is no more than 2 seconds. Based on this research, MyRIO has the ability to pervasive Computing with other devices. And can be used for prototyping models with good capabilities.
Anti-Forensics with Steganographic File Embedding in Digital Image Using Genetic Algorithm Amadeus Pondera Purnacandra; Subektiningsih Subektiningsih
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.24208

Abstract

In this study, a steganography method on digital images as anti-forensics by utilizing genetic algorithms was proposed. Genetic Algorithms are artificial intelligence whose functions are optimization and search. The purpose of this research is to optimize steganography as anti-forensic by applying a Genetic Algorithm and combined with the Hilbert curve, lempel Ziv Markov chain, and least significant bit. The result provides a new steganography method by combining various existing methods. The proposed method will be tested for image quality using PSNR, SSIM, Chi-Squared steganalysis and RS-Analysis, and extraction test. The novelty obtained from the developed method is that the steganography method is as optimal as anti-forensic in keeping confidential data, has a large embedding capacity, and is able to be undetected using forensic methods. The results can maintain data confidentiality, have a large embedding capacity, and are able to be undetected using forensic methods. The proposed method got better performance rather than the previous method because PSNR and SSIM values are high, secret data can be received back as long as the pixel value doesn't change, and the size of the embedding capacity. The proposed method has more ability to embed various types of payload/ secret data because of the way it works, which splits byte files into binary. The proposed method also has the ability not to be detected when forensic image testing is carried out.
Embedded Instrumentation System Using Acquisition Mechanism for BLDC-Powered Electric Vehicle Agus Ulinuha; Ibnu Shokhibul Khak
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23634

Abstract

The primary component of an electric vehicle is the electric motor. In order for the motor to operate properly, some measurement and data acquisition are required for monitoring and controlling its performance. For this purpose, an embedded system is developed and attached to the vehicle. This paper presents the design and implementation of an embedded instrumentation system that includes a data acquisition device, data processor, and data display. A complete prototype-scale electric vehicle was developed and equipped with an embedded instrumentation system. A Brushless DC (BLDC) motor is employed as prime-mover taking power from a 10-Ah Battery. The input parameter is determined by the vehicle’s throttle opening, and the output variables are measured and processed. For the purpose of data acquisition, the system relies on Arduino and Raspberry Pi as processing and monitoring devices. The data and information are displayed on the vehicle dashboard to indicate the real-time vehicle performance and some related information. These include speed, power, motor temperature, distance achieved, and estimated distance that can still be reached with the remaining battery capacity. The data and information are graphically and numerically displayed, which would be useful for steering that enhances system efficiency. The system was tested in the lab and real system, where it demonstrated fine accuracy. The average deviations of the electrical data displayed in the instrumentation system with those given by the standard meter are 0.25 Volt, 0.03 Amp, and 0.43 Watt for voltage, current, and power, respectively. From a mechanical standpoint, the average deviations of speed and torque are 1.2876 km/h and 1.218*10-4 Nm, respectively. The contributions of this research are the development of a complete system to be operated in real conditions, and validation of the displayed information with standard measurement and manual calculation.
Blockchain Technology Purwono Purwono; Alfian Ma'arif; Wahyu Rahmaniar; Qazi Mazhar ul Haq; Dimas Herjuno; Muchammad Naseer
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.24327

Abstract

Blockchain came because of the occurrence of incredulity to single authorities by introducing the concept of network decentralization and data distribution saved in a ledger. Decentralization is used to validate discrepancies in the majority of data. The consensus mechanism collectively maintains the consistency of the ledger. A blockchain is a set of blocks containing transaction data interconnected to each other using the concept of cryptography. A mining process is an effort to add new blocks to the blockchain. The mining computer carries out the process after passing several complex mathematical problems. The fastest miner is rewarded with crypto coins. Some consensus mechanisms commonly used in blockchain are proof of work, proof of stake, practical byzantine fault tolerance, and proof of elapsed time. Blockchain network is designed and implemented in such a way that it can guarantee the security of its data, is easy to be audited, is robust to denial of service and majority attacks, and is private and confidential. The application of blockchain is not limited to finance systems; it can also be applied in health, education, supply chain, and state democracy systems.
A Hybrid DenseNet201-SVM for Robust Weed and Potato Plant Classification Muhammad Dzulfikar Fauzi; Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan; Nia Annisa Ferani Tanjung
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23886

Abstract

Potato plant growth needs to be protected from weeds that grow around it. Currently, the manual spraying of pesticides by farmers is not only precise on weeds but also on cultivated plants. Therefore, we need an intelligent system that can appropriately classify potato plants and weeds. The research contribution combines feature extraction and appropriate classification methods to obtain optimal accuracy. In addition, the small amount of data also contributes to this research. In this research, it is proposed to use a combination of feature extraction using deep learning techniques and classification using machine learning. We use the feature extraction method with the DenseNet201 model because this study's data is not too much. Complex vectors from DenseNet201 were reduced using Principal Component Analysis (PCA). Then we classified it with the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) classification methods. The experimental results show that the PCA method can reduce the complexity of high-dimensional features into 2 and 3 dimensions. The average of the best classification results using SVM was obtained with a 3-dimensional PCA configuration, but on the contrary, using KNN obtained the best results in a 2-dimensional PCA configuration. The results showed 100% accuracy on the DenseNet201-SVM hybrid. The SVM kernel configuration used is a linear kernel. The results of this study can be an insight into an accurate classification method for separating weeds and potatoes so that agricultural technology can apply this method for classification.
Simulation and Optimization of Rectangular Microstrip Patch Antenna for Mobile 5G Communications Hamzah M. Marhoon; Noorulden Basil; Ahmed R. Ibrahim; Hussein A. Abdualnabi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.21927

Abstract

Microstrip or patch antennas are becoming increasingly useful because they can be printed directly onto a circuit board. The microstrip antennas are becoming very widespread within the mobile phone market. Patch antennas are low fabrication cost, have lightweight, and are easily fabricated. The lightweight construction and the suitability for integration with microwave integrated circuits are two more of their numerous advantages. This work introduces a design of a rectangular Microstrip Patch Antenna (MPA) at a frequency of 28 GHz using the finite integration technique of the Computer Simulation Technology (CST). The simulated antenna is employed for the 5G mobile communication. The inset-fed technique has been used to feed the rectangular MPA because it is easy to fabricate and provides simplicity in modelling as well as impedance matching. In order, to facilitate the fabrication and reach the best results, an attempt has been made to improve parameters through optimized patch dimensions by trial and error.  A reasonable gain, bandwidth, radiation pattern, and return loss have been obtained after the antenna simulation process was completed.

Page 20 of 51 | Total Record : 505

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