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Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Published by Universitas Gadjah Mada
ISSN : 23014156     EISSN : 24605719     DOI : 10.22146/jnteti
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Topics cover the fields of (but not limited to): 1. Information Technology: Software Engineering, Knowledge and Data Mining, Multimedia Technologies, Mobile Computing, Parallel/Distributed Computing, Artificial Intelligence, Computer Graphics, Virtual Reality 2. Power Systems: Power Generation, Power Distribution, Power Conversion, Protection Systems, Electrical Material 3. Signals, Systems, and Electronics: Digital Signal Processing Algorithm, Robotic Systems and Image Processing, Biomedical Instrumentation, Microelectronics, Instrumentation and Control 4. Communication Systems: Management and Protocol Network, Telecommunication Systems, Wireless Communications, Optoelectronics, Fuzzy Sensor and Network
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 12 Documents
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Search results for , issue "Vol 12 No 2: Mei 2023" : 12 Documents clear
Desain Integrasi Sistem Instrumentasi dan Kendali untuk Commissioning Siklotron DECY-13 Frida Iswinning Diah; Fajar Sidik Permana; Emy Mulyani
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.5509

Abstract

A cyclotron is a particle beam accelerator used for various applications, one of which is to produce medical radioisotopes. Research Center for Accelerator Technology, Research Organization for Nuclear Energy - National Research and Innovation Agency (Pusat Riset Teknologi Akselerator, Organisasi Riset Tenaga Nuklir - Badan Riset dan Inovasi Nasional, PRTA ORTN-BRIN) is conducting research and development (R&D) for the DECY-13 cyclotron that has reached the stage of testing its primary components. The primary components of the DECY-13 cyclotron consist of seven systems. In commissioning, it is necessary to prepare an integrated instrumentation and control system (ICS) design that unites the operation of all DECY-13 cyclotron’s primary components to produce a particle beam as desired. The integration process was carried out in two stages: determining operating procedures during commissioning and identifying operating parameters; and designing the ICS integration. The process of identifying parameters and determining operating procedures was carried out by studying test data and operating standards for each component to obtain important parameters in operation. Next, the ICS architecture was developed by integrating the operating system on the primary components using the distributed control system (DCS) method. The DCS configuration consisted of three layers, namely the operator, the main control, and the device layers. Communication between the device and the main control layers was carried out using the RS-232 serial communication, while the communication between the main control and the operator layers used the Ethernet. The RS-232 communication between the device and main control layers was used to manage data acquisition, data logging, and operation control. At the operator layer, there was a host-PC that functioned as a data viewer and data logging. This design is expected to be a guide in the implementation of ICS improvements, and realizing ease during commissioning.
Deep Transfer Learning untuk Meningkatkan Akurasi Klasifikasi pada Citra Dermoskopi Kanker Kulit Qorry Aina Fitroh; Shofwatul 'Uyun
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.6502

Abstract

Benign and malignant cancers are the most common skin cancer types. It is essential to know skin cancer symptoms with an early diagnosis to provide an appropriate treatment and reduce the mortality rate. Dermoscopic image is one of the diagnostic media that many researchers have developed. It provides more optimal results in computational-based diagnosis than visual detection. Deep learning and transfer learning are two models that have been used successfully in computational-based analysis, although optimization is still needed. In this study, transfer learning was used to separate dermoscopic images of skin cancer into two categories: benign and malignant. This study used 2,000 images to increase previous research’s accuracy conducted on the Kaggle public dataset containing 3,297 images. Two pretrained models, namely VGG-16 and residual network (ResNet)-50, were compared and used as feature extractors. Fine-tuning was conducted by adding a flatten layer, two dense layers with the ReLU activation function, and one dense layer with the Softmax activation function to classify images into two categories. Hyperparameter tuning on the optimizer, batch size, learning rate, and epoch were performed to get each model’s best performance parameter combination. Before hyperparameter tuning, the model was tested by resizing the input image using different sizes. The results of model testing on the VGG-16 model gave the best performance at an image size of 128 × 128 pixels with a combination of Adam parameters as an optimizer, batch size of 64, learning rate of 0.001, and epoch of 10 with an accuracy value of 91% and loss of 0.2712. The ResNet-50 model yielded better accuracy of 94% and a loss of 0.2198 using the optimizer parameter RMSprop, batch size of 64, learning rate of 0.0001, and epoch of 100. The results indicate that the proposed method provides good accuracies and can assist dermatologist in the early detection of skin cancer.
Algoritma Genetika dalam Penentuan Alokasi Biaya Wheeling Menggunakan LRMC dan MW-Mile Angga Cahya Putra; Sasongko Pramonohadi; Sarjiya
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.4755

Abstract

Electricity deregulation has occurred in many countries. This deregulation primarily aims to introduce competitions to increase the efficiency and quality of service in the electricity supply industry. Generation values and transmission line functions will change significantly. Customers will welcome the free market, causing many companies to build their own generators in a wheeling operation scheme to meet their needs. Wheeling is the solution to this problem. The power flow method was used after adding wheeling to the system. This method was used to determine the system conditions after wheeling was added, considering that power flow map will change when there is a wheeling costumer. The study of the power flow method provides information on the amount of total power generated by the generator yet does not provide information on the power supplied by the generator in each transmission network. To address this shortcoming, the power tracing method was used. This method can provide information on the allocation of power supplied by generators in each transmission network in the system. This research discusses the power tracing method using the genetic algorithm (AG) method. AG is one of several optimization methods; it assumes the allocation of power flowing by the generator as the problem to be optimized. The wheeling pricing used the long run marginal cost (LRMC) method. This method projects future costs by taking into account changes in expenses that occur at any time within a specified period. In this study, the LRMC method was compared with another wheeling costing method, namely the MW-Mile method. The results showed that the LRMC method was cheaper than the MW-Mile method. From an economic perspective, the wheeling costs determination using the LRMC method is 14%-20% cheaper than the MW-Mile method.
Fast Charging pada Baterai Li-Ion dengan Kontrol ANFIS Renny Rakhmawati; Zhafira Rana Khalisa Permana; Rachma Prilian Eviningsih; Suhariningsih
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.5143

Abstract

Most electrical energy used today comes from fossil fuels, which can deplete and contribute to air pollution. In Indonesia, the sun can be used as an alternative energy source and converted into electrical energy utilizing solar panel technology. The voltage generated by the solar panel is relatively high, so it needs to be lowered using a DC-DC converter type buck converter. This electrical energy can be stored using a battery which can be charged in a fast-charging mode to shorten the charging time. The most suitable battery type for fast charging is the lithium-ion (Li-ion) type for its capability to receive large current as big as 1C or equal to the battery capacity. Due to the temperature and solar irradiance effects, the output generated by the solar panel source is not constant. Moreover, to prevent overcharging, a constant current (CC) method with a constant current of 10 A and a constant voltage of 14.4 V was used which the PWM duty cycle driver was controlled using the adaptive neuro-fuzzy inference system (ANFIS) algorithm to obtain a faster response to reach the specified set point. ANFIS is a combination of two algorithms, i.e., artificial neural network (ANN) and fuzzy inference system (FIS). This research was conducted in simulation, the charging current results at the CC method of 10.01A were obtained and would move from the CC method to constant voltage (CV) when the state of charge (SoC) was 85% and the voltage reached 14.4 V. Then, the charging method would change to CV with a constant charging voltage of 14.4 V. When compared to the previous research using fuzzy control, the time required for ANFIS controls to reach set points was 3.2 ms, which is 2.3 ms faster than fuzzy controls, and ANFIS controls can reach set points with fewer errors.
Model Library Support Vector Machine (LibSVM) untuk Sentiment Review Penilaian Pesisir Pantai Oman Somantri; Ratih Hafsarah Maharrani; Santi Purwaningrum
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.6367

Abstract

Improving services as an effort to provide the convenience of tourist destinations, especially on the south coast of Java, is a demand placed on tourism managers, which in the long run will yield positive impacts. The assessment is conducted to determine whether the tourism destination give positive impressions to the tourists. The application of machine learning-based text mining technology, especially a sentiment review, is one of the solutions proposed to overcome this problem, therefore predictions of coastal tourism potential can be known beforehand. This research proposed a coastal sentiment review model using the library support vector machine (LibSVM) method. The process proposed a model optimization based on feature weights using the particle swarm optimization (PSO) algorithm as a model optimization to increase the accuracy level. Efforts to improve the accuracy of the proposed model are the main contribution of this research. The results of research and experiments on the proposed model produced the best model named LibSVM_IG+PSO using the information gain (IG). On the other hand, PSO-based LibSVM method generated an accuracy level of 88.97%. The model proposed in this research is expected to serve as a decision support for tourists, government, and tourism managers in assessing sentiment towards the coastal maritime tourism.
Sistem Estimasi State of Charge untuk Aplikasi Sistem Tertanam Berbasis Neural Networks Muhammad Adib Kamali; Wansu Lim
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.6632

Abstract

The conventional state of charge (SOC) estimation model has several concerns, such as accuracy and reliability. In order to realize robust SOC estimation for embedded applications, this study focuses on three concerns of the existing SOC estimation model: accuracy, robustness, and practicality. In improving the estimation accuracy and robustness, this study took into account the dynamic of the actual SOC caused by the dynamic charging and discharging process. In practice, the charging and discharging processes have characteristics that must be considered to realize robust SOC estimation. The model-based SOC estimation developed based on the virtual battery model causes difficulties for real-time applications. Additionally, model-based SOC estimation cannot be reliably extrapolated to different battery types. In defining the behavior of various types of batteries, the model-based SOC estimation must be updated. Hence, this study utilized data-driven SOC estimation based on an artificial neural network (ANN) and measurable battery data. The ANN model, which has excellent adaptability to nonlinear systems, is utilized to increase accuracy. Additionally, using measurable battery data such as voltage and current signals, the SOC estimation model is suitable for embedded applications. Results indicate that estimating SOC with the proposed model reduced errors with respect to actual datasets. In order to verify the feasibility of the proposed model, an online estimation was out on the embedded system with the use of C2000 real-time microcontrollers. Results show that the proposed model can be executed in an embedded system using measurable battery data.
Pengaruh Perubahan Tegangan Masukan Terhadap Efisiensi Energi Kompor Induksi Budi Sudiarto; Justinus Dipo Nugroho; Faiz Husnayain; Agus R. Utomo; I Made Ardita
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.6784

Abstract

Efficiency in energy use is essential for achieving national energy security. Dependence on energy supplies with high levels of imports can make a nation to be more susceptible to crises and dependence. It also includes the provision of energy sources for cooking needs. An electric induction cooker is one of the alternatives to the liquified petroleum gas (LPG) gas stove used for cooking. Given the high government import subsidy for LPG procurement, diversification of energy sources for cooking needs to be done. Cooking with an induction cooker is more efficient than cooking with a gas stove because it requires a shorter cooking time, and less heat energy is wasted. The energy efficiency of induction cookers ranges is approximately 80% or twice that of gas cookers ranges, which is at 40%. Nonetheless, the level of energy efficiency of induction cookers can be affected by the electricity supply voltage. Electricity conditions in Indonesia with a voltage service quality level of 220 V ± 10% result in the energy efficiency of induction cookers varying. This study analyzes the effect of input voltage variations on the energy efficiency of induction cookers. The input voltage was varied from 230 V to 200 V with a difference of 10 V using four brands of induction cookers. The test results indicate that the efficiency is directly proportional to the input voltage, where the higher the input voltage will provide the greater the induction cooker’s energy efficiency.
Alat Pendeteksi Formalin Menggunakan Deret Sensor HCHO dan MQ-7 dengan Logika Fuzzy Cyntiya Laxmi Haura; Indri Yanti; Muh Pauzan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.7097

Abstract

Formalin is a hazardous chemical substance that has a pungent odor, is colorless or clear, and is flammable. It should be used to preserve corpses, but often misused by unscrupulous traders to preserve food. Formalin has harmful effects on the human body if it is ingested. Therefore, a practical tool that can detect the presence of formaldehyde in food is needed. Making a formalin detection tool using the Mamdani fuzzy inference system is very useful for detecting formalin and the level of food safety quickly and economically. This tool used the HCHO and the MQ-7 sensors combined with an expert system, namely fuzzy logic. The HCHO detects formalin in the food, like the sense of smell; meanwhile, the MQ-7 sensor detects carbon monoxide (CO). In the testing process, a heater was utilized to vaporize the food samples. The vapor was then detected by the two gas sensors and was processed using the fuzzy logic of the Mamdani method. To see the test’s accuracy using the tool, its results were compared with those of the formalin kit and the Fuzzy Logic Toolbox in MATLAB. The results showed that the lowest level of formalin in the tofu sample, namely sample H, was 0.60 ppm; meanwhile, the highest level was in sample E, with 13.64 ppm. The lowest formalin found in salted fish, namely sample P, was 7.14 ppm, while the highest formaldehyde level was in the salted fish sample, namely sample T, with 193.81 ppm. Compared with the formalin kit results, the accuracy value obtained from the total testing of twenty samples was 95%. The output of the tool was nearly identical to that of MATLAB: 85% with a difference of 0.01 and 15% with a difference of 0.02. The average error between tool output and MATLAB was 0.77%.
Reduksi Stripe Noise Berbasis Superpixel pada Citra Satelit Kamirul; Khairunnisa; Ega Asti Anggari; Dicka Ariptian Rahayu; Agus Herawan; Moedji Soedjarwo; Chusnul Tri Judianto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.7443

Abstract

This work introduces a novel noise removal algorithm for satellite imageries based on superpixel segmentation followed by statistics-based filtering. The algorithm worked in three main steps. First, the noisy input image was divided into subregions by employing simple linear iterative clustering (SLIC)-based superpixel segmentation. Then, the statistical property of each subregion was calculated, including their standard deviations and maximum values. Last, an adaptive statistics-based stripe noise removal was performed for each subregion by constructing adaptive filter sizes according to calculated properties. The algorithm was tested using real satellite imageries taken by the LAPAN-A2 and LAPAN-A3 satellites. Its performance was then compared to three existing methods in terms of image quality and computation speed. Extensive experiments on two datasets of 3-channel images captured by the LAPAN-A2 satellite showed that the algorithm was capable of reducing the stripe pattern as measured using the peak-signal-to-noise-ratio (PSNR) metric without introducing additional artifacts, which commonly appeared on over-corrected regions. Moreover, compared to existing methods, the proposed algorithm ran 42 to 103 times faster and provided better image quality by 2.46%, measured using the structural similarity metric (SSIM). The code of this work and the datasets used for the testing are publicly available on www.github.com/dancingpixel/SPSNR.
Pemanfaatan SFCL tipe Bridge untuk Meningkatkan Stabilitas Transien Microgrid dan Economic Feasibility Roy Bayu Negara; Fransisco Danang Wijaya; Lesnanto Multa Putranto; Mohd. Brado Frasetyo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 2: Mei 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i2.4679

Abstract

Currently, renewable energy (RE) generators are widely used by society to reduce emissions. Therefore, a RE-sourced microgrid system coexisting with conventional energy is being developed. However, these electrical energy systems experience transient disturbances such as short circuits, load increase, and decrease in generator output. These disturbances can result in voltage drops and frequency instability. Therefore, efforts are needed to maintain system stability by using a superconducting fault current limiter (SFCL). The SCFL selection is based on its capability to limit the fault current and its speed in providing protection during transient disturbances. The utilized SFCL model is the bridge-type SFCL with two inductors as its main components. Under normal conditions, the current flows through two inductors, and when a fault occurs, the current will go through one inductor. This research was conducted in a scenario where a fault occurred. The voltage value without a bridge-type SFCL during the fault condition was 2.5 V. When a bridge-type SFCL was used, the voltage value was 207 V. Without a bridge-type SFCL, the measured current was 30 kA, whereas the measured current was 1.1 kA with one. The frequency range was 49.7 Hz - 50.2 Hz without bridge-type SFCL and 49.9 Hz - 50.1 Hz with bridge-type SFCL. This research also added an economic feasibility calculation to determine the microgrid system feasibility when using bridge-type SFCL. The calculation consisted of four parts, i.e., net present value (NPV), profitability index (PI), discounted payback period (DPP), and internal rate of return (IRR). Economic feasibility was obtained for an NPV value of US$6,865,405, a PI value of 2.4, a DPP value of four years, and an IRR value of 28.59%. When the obtained value is compared to the feasibility standard, it is determined that a microgrid with SFCL is feasible.

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