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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 503 Documents
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Applying Programmable Logic Control (PLC) for Control Motors, Blower and Heater in the Rubber Drying Processing Hendra Hendra; Pebriyanto S; Hernadewita Hernadewita; Hermiyetti Hermiyetti; Yoserizal Yoserizal
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.20514

Abstract

Rubber is the largest commodity in Indonesia. Rubber is traditionally processed and dried using bamboo hangers, manual arrangement of bamboo drying rubber, heat from firewood for drying chambers and large areas. This drying process has disadvantages, namely inconsistent drying time, non-uniform room temperature, unequal product quality, and unfriendly drying process. The solution is to overcome the automatic rubber dryer machine that is made using PLC to get the motor operating system for automatic rubber handling in the drying chamber, fixed drying temperature, small drying area, and fast-drying time. The experimental method is used for the automatic rubber drying process with PLC to control the movement of rubber in/out of the chamber dryer, heater, and blower for distribution temperature and other components. From the test results, it is found that the control system can work well at the voltage of each component of 220V, such as a sensor with a current of 0.21A and a stop time of 0.01s-0.3 seconds. The motor, heater, and blower are active (ON) at 220V with a current of 8.27A. The heater requires a current of 1.99A for active (ON) and an active blower (ON) with a current of 0.75A.
Systematic Literature Review: Current Products, Topic, and Implementation of Graph Database Adhy Rizaldy; Sirli Fahriah; Nahrun Hartono
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.19007

Abstract

Planning, developing, and updating software cannot be separated from the role of the database. From various types of databases, graph databases are considered to have various advantages over their predecessor, relational databases. Graph databases then become the latest trend in the software and data science industry, apart from the development of graph theory itself. The proliferation of research on GDB in the last decade raises questions about what topics are associated with GDB, what industries use GDB in its data processing, what the GDB models are, and what types of GDB have been used most frequently by users in the last few years. This article aims to answer these questions through a Literature Review, which is carried out by determining objectives, determining the limits of review coverage, determining inclusion and exclusion criteria for data retrieval, data extraction, and quality assessment. Based on a review of 60 studies, several research topics related to GDB are Semantic Web, Big Data, and Parallel computing. A total of 19 (30%) studies used Neo4j as their database. Apart from Social Networks, the industries that implement GDB the most are the Transportation sector, Scientific Article Networks, and general sectors such as Enterprise Data, Biological data, and History data. This Literature Review concludes that research on the topic of the Graph Database is still developing in the future. This is shown by the breadth of application and the variety of new derivatives of GDB products offered by researchers to address existing problems.
Usefulness of Augmented Reality as a Tool to Support Online Learning Ismail Ismail; Nur Iksan; Siva Kumar Subramaniam; Azmi Shawkat Abdulbaqie; Salini Krishna Pillai; Ismail Yusuf Panessai
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21133

Abstract

The global crisis following the outbreak of the Covid-19 epidemic has had an impact on the teaching and learning process (PdP). The main problem with PdP during the Covid-19 epidemic was the limitation in conducting face-to-face activities in the classroom. Therefore, a learning aid is needed to enable PdP to run optimally even though there is no face-to-face interaction between teachers and students. The research contribution is to highlight the application of Augmented Reality to support distance learning in the Covid-19 epidemic situation, specializing in Wood Carving Art for the subject of Visual Arts Education Form 4. The AR Wood Carving Art mobile application uses the ADDIE design model based on five phases, namely Analysis, Design, Development, Implementation, and Testing. The AR Wood Carving Art mobile application is evaluated based on its usefulness. The AR Wood Carving Art mobile application was evaluated among 27 students from 4 of SMK Pasir Gudang (Johor, Malaysia) and registered to Visual Arts. Based on the result, 80% of respondents strongly agree that the AR Wood Craving Art mobile application help respondents be more effective. It helps users to be more productive and giving ideas to users to be creative and innovative. One hundred percent of respondents strongly agree that the AR Wood Craving Art mobile application makes things that users want to achieve easier to do, and the AR Wood Craving Art mobile application does what users want. Eighty percent of respondents strongly agree that the AR Wood Craving Art application is useful and the application saves time when users use it. Therefore, the AR Wood Craving Art application is effectively used in learning which makes users more productive, creative, and innovative. In addition, the AR Wood Craving Art mobile application makes it easy for users to understand wood carving topics in visual arts subjects, and users can carry out educational and teaching activities like in a classroom.
Reversible Data Hiding Using Hybrid Method of Difference Expansion on Medical Image Aulia Arham; Ozzy Secio Riza
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 6, No 2 (2020): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v6i2.16965

Abstract

Data hiding in the image can cause permanent distortion (irreversible), in other applications such as medical images, distortion can cause misdiagnosis. To overcome these problems, a special scheme is required for the embedding data on medical image. Reversible data hiding is a scheme that can restore the image to original image without distortion after the embedded information is extracted. Difference Expansion (DE) is one of the schemes in reversible data hiding that is simple and easy to implement. In this paper, we propose two schemes based a hybrid combination of DE to increase on capacity and visual quality. Medical image has characteristics is the large of smooth block areas, in which DE method is applied to the non-smooth areas image. We used four different medical images to evaluate the proposed scheme. The results showed that the proposed scheme has a high capacity and better visual quality than the original scheme and similar schemes have been proposed previously. Embedding capacity of the proposed scheme is up to 0.66 bpp with visual quality of PSNR value is up to 48 dB.
HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text Md Shofiqul Islam; Mst Sunjida Sultana; Mr Uttam Kumar; Jubayer Al Mahmud; SM Jahidul Islam
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.20550

Abstract

We present a modern hybrid paradigm for managing tacit semantic awareness and qualitative meaning in short texts. The main goals of this proposed technique are to use deep learning approaches to identify multilevel textual sentiment with far less time and more accurate and simple network structure training for better performance. In this analysis, the proposed new hybrid deep learning HARC model architecture for the recognition of multilevel textual sentiment that combines hierarchical attention with Convolutional Neural Network (CNN), Bidirectional Gated Recurrent Unit (BiGRU), and Bidirectional Long Short-Term Memory (BiLSTM) outperforms other compared approaches. BiGRU and BiLSTM were used in this model to eliminate individual context functions and to adequately manage long-range features. Dilated CNN was used to replicate the retrieved feature by forwarding vector instances for better support in the hierarchical attention layer, and it was used to eliminate better text information using higher coupling correlations. Our method handles the most important features to recover the limitations of handling context and semantics sufficiently. On a variety of datasets, our proposed HARC algorithm solution outperformed traditional machine learning approaches as well as comparable deep learning models by a margin of 1%. The accuracy of the proposed HARC method was 82.50 percent IMDB, 98.00 percent for toxic data, 92.31 percent for Cornflower, and 94.60 percent for Emotion recognition data. Our method works better than other basic and CNN and RNN based hybrid models. In the future, we will work for more levels of text emotions from long and more complex text.
Design of an Adaptive Super-Twisting Control for the Cart-Pole Inverted Pendulum System Yusie Rizal; Muhammad Wahyu; Imansyah Noor; Joni Riadi; Feriyadi Feriyadi; Ronny Mantala
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.20420

Abstract

A cart-pole inverted pendulum system is one of the underactuated systems that has been used in many applications. This research aims to study the design and the effectiveness of the Adaptive Super-Twisting controller to stabilize the system by comparing it with other previous control methods. A stabilization control of the pendulum upright using the Adaptive Super-Twisting algorithm (ASTA), was investigated. The proposed controller was designed based on the decoupling algorithm method to solve the coupled control input in the system model. We then compared the proposed stabilizing controller with first-order sliding mode control (FOSMC) and Super-Twisting algorithm (STA) in Matlab/Simulink simulation and realistic computer simulation. We developed the computer simulation using anyKode Marilou software, which adopted Open-Dynamic Engine (ODE) as a physics engine. In Matlab/Simulink simulation, we considered three different scenarios: a nominal system, a system with uncertainty, and a disturbed system. Meanwhile, in a computer simulation, we only presented the comparison of different controllers' performances for the realized system. Both results showed that the three controllers could stabilize the pendulum upright with a 0.1 rad initial angular position around the vertical axis. Under the same conditions, the ASTA and STA controllers had similar performances; they both have less chattering and faster convergence than the FOSMC approach. However, the FOSMC approach had the least energy delivered and smallest errors than the other two approaches.
Towards Efficient Sensor Placement for Industrial Wireless Sensor Network Pavithra Ravikumar; D Arivudainambi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 6, No 2 (2020): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v6i2.19134

Abstract

Industrial Wireless Sensor Network (IWSN) is the recent emergence in wireless technologies that facilitate industrial applications. IWSN constructs a reliable and self-responding industrial system using interconnected intelligent sensors. These sensors continuously monitor and analyze the industrial process to evoke its best performance. Since the sensors are resource-constrained and communicate wirelessly, the excess sensor placement utilizes more energy and also affects the environment. Thus, sensors need to use efficiently to minimize their network traffic and energy utilization. In this paper, we proposed a vertex coloring based optimal sensor placement to determine the minimal sensor requirement for an efficient network.
The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm Bhakti Yudho Suprapto; A. Wahyudin; Hera Hikmarika; Suci Dwijayanti
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.20684

Abstract

The challenge with using the Unmanned Aerial Vehicle (UAV) is when the UAV makes a landing. This problem can be overcome by developing a landing vision through helipad detection. This helipad detection can make it easier for UAVs to land accurately and precisely by detecting the helipad using a camera. Furthermore, image processing technology is used on the image produced by the camera. You Only Look Once (YOLO) is an image processing algorithm developed to detect objects in real-time, and it is the result of the development of one of the Convolutional Neural Network (CNN) algorithm methods. Therefore, in this study the YOLO method was used to detect a helipad in real-time. The models used in the YOLO algorithm were Mean-Shift and Tiny YOLO VOC. The Tiny YOLO VOC model performed better than the Mean-Shift method in detecting helipads. The test results obtained a confidence value of 91.1%, and the system processing speed reached 35 frames per second (fps) in bright conditions and 37 fps in dark conditions at an altitude of up to 20 meters.
Modeling / Optimization and Effect of Environmental Variables on Energy Production Based on PV / Wind Turbine Hybrid System Reza Alayi; Javad Javad Velayti
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.20515

Abstract

The use of fossil fuels to supply human energy needs is increasing day by day, which contributes to environmental pollution. In addition, they have a limited supply and are not continuously being made, or they are made very slowly. Thus, to reduce human dependence on this type of energy, the use of renewable energy sources is increasing, which has problems because of the high cost of investment and the stochastic nature. In this study, a sensitivity analysis of renewables was conducted to evaluate the impact of these resources on the costs of hybrid power plants based on renewable energies. In this regard, the amount of wind and intensity of sunlight was studied in the Kermanshah region. Significant results can be attributed to a reduction in the rate of return of capital to 9.22 years for the radiation intensity of 4.5Kwh / m2 / d. Then, by Sensitivity analysis to wind intensity, the Optimal wind turbine speed was 4.99 m/s, for COE 0.93($/Kwh).
Jatropha Curcas Disease Identification using Random Forest Triando Hamonangan Saragih; Vivi Nur Wijayaningrum; Muhammad Haekal
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.20141

Abstract

As one of the most versatile plants, Jatropha curcas is spread in various regions around the world because of the great benefits it provides. However, Jatropha curcas is easily attacked by viruses which then cause damage to the plant, such as yellowing leaves and secreting sap, making it necessary to identify Jatropha curcas disease to deal with the problem as early as possible so that the losses incurred are not too large. An expert system was built to be able to identify Jatropha curcas disease by adopting expert knowledge. The use of the Random Forest algorithm as one of the classification algorithms was applied in this study. By using a random forest, several disease prediction classes are generated by each decision tree that has been formed. The disease class with the most votes was used as the final result. In this study, the data used were 166 data with 9 diseases and 30 symptoms. The results showed that Random Forest outperformed other algorithms such as Fuzzy Neural Network and Extreme Learning Machine with an accuracy of 98.002% using the composition of training data and test data of 70:30.

Page 14 of 51 | Total Record : 503

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