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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 644 Documents
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Perbandingan Dua Observer Kecepatan Motor Arus Searah pada Sistem Kendali tanpa Sensor Kecepatan Bernadeta Wuri Harini; Martanto; Tjendro
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 4: November 2022
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.v11i4.5019

Abstract

In a sensorless motor speed control system, the motor speed is not directly measured using a speed sensor, but it is estimated using an observer. The sensorless speed control systems are mostly applied to AC motors, while they have not been widely applied to DC motors. Therefore, this paper presents simple observers to estimate the DC motor speed. The observers used were based on the DC motor electric equation. Two methods were used in this research. The first method was the observer estimating the speed based on the resistance inductance values (L-R method), while the second was the observer estimating the motor’s speed only based on the motor’s resistance value (R method). The speed was estimated using armature current (ia) and voltage (va). Therefore, a current and voltage sensor was used. Not only was the observer estimated, but it was also implemented on a real DC motor. An Arduino microcontroller was used to calculate the speed. The LN298 was used as a DC motor drive. Even though the R method is simpler, the test result showed that its speed estimation was less precise than the L-R method. By manual calculation, the motor speed estimation result in the L-R method had an error of 0.14%, while the motor speed estimation results in the R method had an error of 5.03%. The estimation results of motor speed implemented on a real DC motor and microcontroller system in the L-R method had an error of 3.98%, while the result of the estimation of motor speed in the R method had an error of 4.87%.
Peningkatan Stabilitas Transien pada Turbin Angin Berbasis DFIG Menggunakan SFCL tipe Bridge Doane Puri Mustika; Sasongko Pramono Hadi; Mokhammad Isnaeni B; Mohd. Brado Frasetyo; Tumiran
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 4: November 2022
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.v11i4.5031

Abstract

Today’s electrical energy is mainly produced by burning fossil fuels, which actually has negative effects on earth, namely global warming. In the electricity sector, measures that can be taken to reduce emissions include replacing conventional generators with renewable ones. Wind energy is one type of new renewable energies (NREs) with the potential to reduce emissions. Wind turbines widely used today are variable speed wind turbines, such as the doubly-fed induction generator (DFIG). DFIG has numerous advantages, like having more flexibility and being able to control both active and reactive powers. However, it often encounters instability problems in its system when experiencing transients. Therefore, a solution that can improve transient stability in DFIG is needed. The bridge-type superconducting fault current limiter (SFCL) was used in this research as a solution to improve the transient stability in DFIG, which consisted of two diodes and two inductors. This bridge-type SFCL operates by limiting the current in the event of faults, preventing the system from voltage drops or trips. The simulation results were analyzed under two circumstances. In the first circumstance, the 9 MW DFIG wind turbine system which was given faults using SFCL produced a voltage value of 219 V, with a more stable frequency value of 50 Hz, and an active power value of 9 MW. Meanwhile, when a system that did not use SFCL was given faults, the voltage dropped from the normal state of 219 V to 100 V. The frequency value was less stable, fluctuating between 49.75 Hz and 50.25 Hz, while the active power dropped from 9 MW to 6 MW. This result proves that the bridge-type SFCL method effectively increases the transient stability in DFIG.
Estimasi Deviasi Parameter pada Motor DC Menggunakan Sliding-Mode Observer dan Algoritme Least-Square Dzuhri Radityo Utomo; Muhammad Faris
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 4: November 2022
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.v11i4.5036

Abstract

Performing system/plant maintenance is very important as an attempt to avoid any failure during system/plant operation. One of the methods that can be adopted to detect any potential failure inside a plant is by estimating the value of the plant’s parameters. When the plant’s parameters deviate too far from their nominal values, the plant will be more likely to fail. In this paper, an estimation method for estimating the deviation in the parameters of a linear system/plant is proposed as an improvement of the previously proposed method. The main component of this parameter deviation estimator system was an observer block which adopted the sliding-mode observer in combination with an adaptive filter block. The adaptive filter block used in this system adopted the least-square algorithm instead of adopting the gradient-descent algorithm as in the previously proposed method. This method was simulated to estimate the deviation in the parameters of DC motor to verify the effectiveness of the proposed metho. The simulation results showed that this method could successfully estimate the deviation of DC motor parameters with a maximum estimation error of less than 4 %. This method could estimate the deviation in DC motor parameters for both constant deviation value and slowly-changing deviation value as time goes by. In addition, estimating the parameter deviation using this method could produce a good level of accuracy even when using a fairly low-frequency input signal. This method is suitable to be adopted in parameter monitoring process of a linear system so that any fault occurring in the system can be detected and isolated before the plant is fatally damaged.
TopC-CAMF: Sistem Perekomendasi Matrix Factorization Berbasis Top Context Rosni Lumbantoruan; Paulus Simanjuntak; Inggrid Aritonang; Erika Simaremare
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 4: November 2022
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.v11i4.5399

Abstract

Online activities have been more and more vital as the digital business has expanded. Users can conduct most activities online such as online shops, hotel bookings, or online educations and courses. A large number of social users are drawn to the abundance of goods available on the Internet. The huge amount of information makes it impossible for social users to navigate it properly and efficiently. Many companies have offered a personalization to tackle this issue. It is proven that the personalized recommendation systems are able to suggest items to users based on their interests and needs that best suit them, which can be captured from user’s contextual information. However, most of the studies capture this contextual information from the predefined contexts such as location and time. In this study, the personalized user context from the user’s text review that they posted as they gave rating to an item was obtained. To this end, a new approach based on the matrix factorization recommendation model, TopC-CAMF, was proposed. TopC-CAMF investigates and finds the most important contexts or needs for each user by leveraging the deep learning model. First, all important contexts from user’s text reviews were extracted. The next step was representing user preferences with the variations of most important contexts, namely top 5, top 10, top 15, top 20, and top 25 contexts. Then, the best top context variation was evaluated and the optimal one was used as the input for the matrix factorization method in providing better recommendations. Extensive experiments using three real datasets were conducted to prove the effectiveness of the TopC-CAMF in terms of root mean square error (RMSE), mean absolute error (MAE), mean squared error (MSE), normalized discounted cumulative gain (NDCG), and Recall.
Perbandingan Kinerja Generalized Frequency Division Multiplexing Menggunakan Modulasi QAM dan Offset QAM Ari Endang Jayati; Budiani Destyningtias
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 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.v12i1.2548

Abstract

Generalized frequency division multiplexing (GFDM) is a future nonorthogonal multicarrier system. GFDM is a block-shaped data transmission technique in which each subcarrier is formed from nonrectangular shaped pulses. The application of quadrature amplitude modulation (QAM) mapping for GFDM is excellent because of the increased spectral efficiency. QAM also has limitations, namely increasing complexity when implemented. Apart from that, the inter carrier interference (ICI) persists and greatly influences the system. The technique for mitigating this weakness is by using offset QAM (OQAM) mapping. The advantages of GFDM/OQAM over GFDM/QAM are that the quadrature and in-phase components in OQAM modulation do not experience shifts in the same time slot, low out of band (OOB), high data rate and is ICI free. This study compares two scenarios namely the GFDM/OQAM and the GFDM/QAM systems. It analyzes the performance of the bit error rate (BER) if additive white gaussian noise (AWGN) and Rayleigh channels are passed. The simulation results show that GFDM/OQAM has better performance results. The simulation results showed that in order to obtain BER 10-2, there should be a decrease in the value of Eb/N0 (ratio of energy per bit to noise power) by 8 dB in QAM to OQAM when they were passed AWGN channels. Meanwhile, when passed the Rayleigh Fading channel, there was a decrease in the Eb/N0 value by 9 dB in the QAM to OQAM to get a BER value of 10-2. This study has also succeeded in investigating the performance of the two systems for parameters of the constellation diagram and signal spectrum. Moreover, it has succeeded in obtaining a roll off factor reference value that can be used in the application of the GFDM/OQAM system with the best performance result of 0.3. The roll off factor value greatly affects the performance of the GFDM system.
Subarray 4×4 untuk Antena MIMO 5G dengan Elemen yang Menerapkan Teknik Parasitic Fitri Amillia; Eko Setijadi; Gamantyo Hendrantoro
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 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.v12i1.5310

Abstract

Multiple-input multiple-output (MIMO) is a wireless communication system using multiple antennas on the transmitting and receiving sides. This system can improve the quality of wireless communication on 5G technology networks. The advantages of 5G include higher data rates and lower delays. The 5G network in Indonesia uses an intermediate frequency working in the 3.5 GHz frequency band. Antenna is an important device in a wireless network MIMO system. Therefore, this study proposes a single element design using parasitic techniques to widen the bandwidth to meet the needs of MIMO antennas and design a 4×4 subarray antenna for 5G MIMO. The method used began with determining the target antenna specifications, then designing a single element with a parasitic patch. The use of parasitic patches techniques on antenna elements aims to widen the bandwidth to meet target specifications. The resonant frequency of the microstrip antenna was affected by the increase in the number of parasitic patches. The number of resonant frequencies that arise resulted in a broad bandwidth. Then, the single elements with parasitic patches were arranged into a 4x4 subarray. All elements were arranged on the same substrate with a spacing between elements from one feed point to another was 64.28 mm or 0.75λ. The subarray design met the target antenna specifications if the subarray elements have a fractional bandwidth of more than 20% and mutual coupling of less than -20 dB. The material used in antenna design and fabrication was FR-4 (epoxy) substrate with a dielectric constant (ε_r) of 4.3 and a substrate thickness (h) of 1.6 mm. The results showed a bandwidth of 735 MHz or a fractional bandwidth of 20.35%, return loss of -14.65 dB, mutual coupling of -30.05 dB, and gain of 16.86 dB. Thus, the designed 4x4 subarray for MIMO antenna meets the desired specifications.
Sistem Deteksi Masker Berbasis Jetson Nano dengan Deep Learning Framework TensorFlow Muhammad Luqman Bukhori; Erwan Eko Prasetiyo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 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.v12i1.5472

Abstract

Indonesia is one of the countries experiencing COVID-19 impacts. Various measures have been conducted to prevent the spread of this virus. One of the efficient measures to prevent this impact is by implementing a strict health protocol and proper mask-wearing. Mask-wearing monitoring continues to be carried out in office buildings, supermarkets, and other public spaces. The supervisor’s role is indispensable in supervising proper mask-wearing. However, a supervisor has limitations in conducting supervision, creating a gap for people not to comply with mask-wearing rules properly. Therefore, it is necessary to have a system that works automatically to assist supervisors in monitoring proper mask-wearing. This paper aims to design a computer vision capable of detecting whether or not a person wears a mask using the TensorFlow deep learning framework. TensorFlow is used for its efficiency in processing digital image data. The classification of digital image data in TensorFlow uses a Keras deep learning structure. As a result, it is lightweight and can be used on embedded devices such as Jetson Nano to detect mask-wearing in real time. The stages of a mask detection system consisted of image dataset collection, feature extraction, data separation, modeling, model training, and model implementation. TensorFlow deep learning framework processed image data directly through a webcam. When the camera captured the object of the person not wearing the mask properly, the monitor screen displayed a red box on the face. The sign can help the supervisor when conducting supervision. The test results show that the system successfully correctly detects unmasked people, with an accuracy of 99.48%. In addition, the system also managed to detect people wearing masks properly and got an average accuracy of 99.12%. The monitor displays a green box on the face when the detected person properly wears a mask.
Penetrasi Fotovoltaik dengan Metode MILP dan Pertimbangan Pembebanan Minimal Teknis Alfi Bahar; Muhammad Yasirroni; Sarjiya; M. Isnaeni Bambang Setyonegoro
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 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.v12i1.4531

Abstract

Technological development and the reduction of installation costs have caused a rapid growth of solar power plants in Indonesia. The National Electricity Company (Perusahaan Listrik Negara, PLN) strives to achieve the energy mix of renewable energy to 23% by 2025. Solar power plants are unique in that they only supply their power during the daytime. It makes solar power plants connected to the power system change the load profile of the Java-Bali system. In this study, the penetration of solar power plants changed the scheduling of the Java-Bali system because the penetration was installed to the technical minimum loading of existing power plants. When penetration is too big, thermal generator scheduling failure is possible. Unit commitment and economic dispatch with mixed-integer linear programming (MILP) method using CPLEX and Python were carried out to calculate the fuel and generation costs per kWh before and after the penetration. MILP was used to solve the cost fuel equation, namely an integer and nonlinear mix equations, that are challenging to be solved using standar nonlinear programming methods. Due to the use of the MILP-UC, all objective function equations and restraint functions must be linear functions. The tests were conducted for three years, from 2023 to 2025. Simulation results on the Java-Bali system show that the capacity of solar power plants penetrating the Java-Bali system against the peak load will be 52%, 52%, and 50% in 2023, 2024, and 2025, respectively. Meanwhile, penetration of solar power plants to technical minimum loading of existing power plants resulted in the fuel cost falling by 23% in 2023 and 22% in 2024 and 2025. Lastly, the cost of generation per kWh will be decreased by 8% in 2023 and will be as low as 7% in 2024 and 2025.
Mengoptimalkan Akurasi pada Klasifikasi Emosi Majemuk Berdasarkan Semantik Kalimat Menggunakan XLM-RoBERTa Aripin; Steven Adi Santoso; Hanny Haryanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 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.v12i1.6084

Abstract

There are six basic emotions; they are anger, sadness, happiness, disgust, surprise, and fear. A combination of basic emotions creates a new type of emotion called a compound emotion. The examples of applying these compound emotions are in chatbots, translations, and text summarization. Several research on classifying these emotions based on Indonesian texts have used traditional models such as multinomial naïve Bayes, support vector machine (SVM), k-nearest neighborhood, and term frequency–inverse document frequency (TF-IDF). The previous research have a massive drawback, primarily on their less optimized performances. The models used could only classify things with the available data; thus, the text processing is required that results in a longer training time for larger This research aims to solve the issue from the previous research by using cross-lingual language model-robustly optimized bidirectional encoder representations from transformers approach (XLM-RoBERTa) model to classify compound emotions based on the semantics or meaning in words and sentences. The XLM-RoBERTa is a transformer model that can identify the meaning of a word from its attention mechanism and represent it as a vector to know the usage and position in a sentence. It is also a method to understand the meaning of a specific word. Using the attention mechanism, the model used the word position to recognize the sentence pattern and classify them even further to know the pattern and sequence to understand the semantics. The experiment result showed that the model could classify Indonesian texts into basic and compound emotion classes with an accuracy of up to 95.56%. This result is much higher than using traditional models to classify the compound emotion classes.
Pengenalan Tanda Arah untuk Navigasi Automatic Guided Vehicle berbasis Raspberry Pi Florentinus Budi Setiawan; Rachmat Hidayat; Leonardus Heru Pratomo; Slamet Riyadi
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 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.v12i1.4959

Abstract

The development of modern times in robotics and mechanization technology has increased significantly in the past few decades due to their high efficiency in time and energy. In the goods mobilization system for companies’ use, particularly the industrial and warehousing divisions, one of the robots that are used for transporting goods is an automatic guided vehicle (AGV). One of the old navigation methods in AGV is the use of a sensor to follow the line pattern on the detected object, namely the line on the floor. This method is rather ineffective because, gradually, these line pattern objects on the floor will fade caused by the effect of AGV wheels’ frictional forces, causing the camera sensor can no longer detect them. Therefore, it is necessary to improve the AGV navigation method so that it can be a sustainable innovation. This navigation method used four image objects positioned in the area traversed by the AGV robot and the camera served as a forward-facing sensor so that the AGV could detect the pattern of image objects with the help of computer vision using the OpenCV software library. The pattern of the detected image object was processed by a program designed on the Raspberry Pi 4 Model B minicomputer. The test results prove that this method can detect image objects within the camera’s field of view and successfully display the output of the image object. The system managed to recognize objects quite accurately, with parameters of 10–95 cm, and through several experiments. The analysis of the rotational speed of the front and rear wheels of the AGV was carried out using an oscilloscope and tachometer as a means of measuring wheel speed or rotation.

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