Jurnal Nasional Teknik Elektro dan Teknologi Informasi
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
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<![CDATA[Perbandingan Kinerja Generalized Frequency Division Multiplexing Menggunakan Modulasi QAM dan Offset QAM ]]>
<![CDATA[Ari Endang Jayati]]>;
<![CDATA[Budiani Destyningtias]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.2548
<![CDATA[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.]]>
<![CDATA[Subarray 4×4 untuk Antena MIMO 5G dengan Elemen yang Menerapkan Teknik Parasitic ]]>
<![CDATA[Fitri Amillia]]>;
<![CDATA[Eko Setijadi]]>;
<![CDATA[Gamantyo Hendrantoro]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.5310
<![CDATA[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.]]>
<![CDATA[Sistem Deteksi Masker Berbasis Jetson Nano dengan Deep Learning Framework TensorFlow ]]>
<![CDATA[Muhammad Luqman Bukhori]]>;
<![CDATA[Erwan Eko Prasetiyo]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.5472
<![CDATA[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.]]>
<![CDATA[Penetrasi Fotovoltaik dengan Metode MILP dan Pertimbangan Pembebanan Minimal Teknis ]]>
<![CDATA[Alfi Bahar]]>;
<![CDATA[Muhammad Yasirroni]]>;
<![CDATA[Sarjiya]]>;
<![CDATA[M. Isnaeni Bambang Setyonegoro]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.4531
<![CDATA[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.]]>
<![CDATA[Mengoptimalkan Akurasi pada Klasifikasi Emosi Majemuk Berdasarkan Semantik Kalimat Menggunakan XLM-RoBERTa ]]>
<![CDATA[Aripin]]>;
<![CDATA[Steven Adi Santoso]]>;
<![CDATA[Hanny Haryanto]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.6084
<![CDATA[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.]]>
<![CDATA[Pengenalan Tanda Arah untuk Navigasi Automatic Guided Vehicle berbasis Raspberry Pi ]]>
<![CDATA[Florentinus Budi Setiawan]]>;
<![CDATA[Rachmat Hidayat]]>;
<![CDATA[Leonardus Heru Pratomo]]>;
<![CDATA[Slamet Riyadi]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.4959
<![CDATA[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.]]>
<![CDATA[Stochastic Unit Commitment dalam Berbagai Ukuran Sistem di bawah Ketidakpastian Peramalan PLTS yang Tinggi ]]>
<![CDATA[Muhammad Yasirroni]]>;
<![CDATA[Lesnanto Multa Putranto]]>;
<![CDATA[Sarjiya]]>;
<![CDATA[Husni Rois Ali]]>;
<![CDATA[Indra Triwibowo]]>;
<![CDATA[Qiangqiang Xie]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.5281
<![CDATA[This paper proposes a stochastic unit commitment (SUC) approach to solve a day-ahead unit commitment (UC) problem in a system with high uncertainty net load which is caused by photovoltaic (PV) power plants. In contrast with robust unit commitment (RUC) which only considers the worst-case scenario, SUC considers every possible scenario with its probability. Multiple possible PV curves were obtained using k-means clustering on historical data. The proportion of cluster members was used as a weight factor representing the occurrence probability of PV curves. The test was separated into two-step tests, namely day-ahead and real-time markets, using IEEE 10 generating unit system and solved using CPLEX. The results showed that in a day-ahead UC, SUC ($539,896) had lower cost than RUC ($548,005). However, when the total energy generated was considered, the SUC (20.78 $/MWh) cost higher compared to RUC (20.75 $/MWh). It is because the solution proposed by SUC is as robust as the RUC, but the generation cost formulation also considers over-commitment. Thus, SUC produced a fairer price for the independent power producer and electric utility in the day-ahead calculation. The results also showed that in the test environment of the real-time market, SUC was able to produce a robust solution without going into over-commitment. It is clearly shown in a 30 units system test with 10 centroids, in which SUC had a cheaper solution (20.7253 $/MWh) compared to RUC (20.7285 $/MWh), without violating power balance or going to load shedding.]]>
<![CDATA[Optimasi Klasifikasi Fonem Menggunakan Backpropagation Neural Network dan Principal Component Analysis ]]>
<![CDATA[Clara Maria Livia Suitela]]>;
<![CDATA[Aripin]]>;
<![CDATA[Erika Dina Permata]]>;
<![CDATA[Muzalfa Nakiatun Niza]]>;
<![CDATA[Naeli Laelal Khiaroh]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.5674
<![CDATA[A phoneme is the smallest sound in a sentence that has no meaning but plays the most important role in meaning formation. Phoneme identification from a video that shows an actor speaking Indonesian sentences is an important part of developing visual-to-text applications. This application can translate mouth movements from a video into a series of Indonesian texts so that it can facilitate communication for the deaf. This study aims to optimize the performance of the classification process on image data, including as many as 32 phonemes from video extraction results so that they can be used to support the phoneme identification process to realize visual-to-text applications in Indonesian. The classification algorithm used in this study was neural network backpropagation. Some of the proposed efforts to optimize the performance of the classification process included using a comparison of the proportion of datasets, estimating the number of hidden layers, and reducing the dimensions of the dataset using the principal component analysis (PCA) method to reduce the amount of data that is considered less important without reducing the level of information. The dimensions of the data before reduction were 1280 × 7100 data matrices and 1280 × 50 data matrices after reduction. The accuracy results obtained in data optimization using the PCA were equal to 87.16% with a data proportion of 8 : 2 and fifty important data points were used in the data optimization process using the PCA.]]>
<![CDATA[Sistem Monitoring Cairan Infus Berbasis IoT Menggunakan Protokol MQTT ]]>
<![CDATA[Nur Afiyat]]>;
<![CDATA[Raizly Helmi Navilla]]>;
<![CDATA[Mohamad Hariyadi]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.5862
<![CDATA[One of the medical equipment that is often used in hospitals is infusion; however, the infusion monitoring system is generally still manual so that medical staff must constantly monitor the infusion device condition, which is requiring more effort and time. In this study, a 500 ml Ringer’s lactate infusion fluid monitoring system was developed based on the internet of things (IoT) using the message queuing telemetry transport (MQTT) communication protocol and an IoT cloud server system using the MQTT Dash. This infusion fluid was chosen as it is the most widely used infusion fluid. The HX711 load cell was used as a sensor to determine the weight of the infusion fluid. In addition, the NodeMCU ESP8266 microcontroller was used since it is equipped with a WiFi module called the ESP8266 module, hence it can support the implementation of IoT systems. The MQTT protocol was used to send the data to users. It was then connected to the MQTT Dash application as a monitoring medium for medical personnel. The system’s performance based on the performance of the HX711 load cell sensor in terms of the accuracy of reading the weight of infusion fluids was very good. It is evidenced by the average error percentage value of 0.08% to 0.64%, meaning that load cell sensor works well as it remains within the error tolerance limit of 5%. Meanwhile, the quality of service (QoS) test revealed that the results of the average delay on all systems ranged from 0.014 ms to 0.023 ms. According to the telecommunications and internet protocol harmonization over networks (TIPHON) standards, these values are considered very good. After that, the average of packet loss testing results on all systems were 0% to 0.01%. According to the TIPHON standards, these values are likewise classified as very good.]]>
<![CDATA[Model Berbasis CNN untuk Estimasi dan Autentikasi Copy Detection Pattern ]]>
<![CDATA[Syukron Abu Ishaq Alfarozi]]>;
<![CDATA[Azkario Rizky Pratama]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v12i1.6205
<![CDATA[Counterfeiting has been one of the crimes of the 21st century. One of the methods to overcome product counterfeiting is a copy detection pattern (CDP) stamped on the product. CDP is a copy-sensitive pattern that leads to quality degradation of the pattern after the print and scan process. The amount of information loss is used to distinguish between original and fake CDPs. This paper proposed a CDP estimation model based on the convolutional neural network (CNN), namely, CDP-CNN. The CDP-CNN addresses the spatial dependency of the image patch. Thus, it should be better than the state-of-the-art model that uses a multi-layer perceptron (MLP) architecture. The proposed model had an estimation bit error rate (BER) of 9.91% on the batch estimation method. The error rate was 9% lower than the previous method that used an autoencoder MLP model. The proposed model also had a lower number of parameters compared to the previous method. The effect of preprocessing, namely the use of an unsharp mask, was tested using a statistical testing method. The effect of preprocessing had no significant difference except in the batch estimation scheme where the unsharp mask filter reduced the error rate by at least 0.5%. In addition, the proposed model was also used for the authentication method. The authentication using the estimation model had a good separation distribution to distinguish the fake and original CDPs. Thus, the CDP can still be used as the authentication method with reliable performance. It helps anti-counterfeiting on product distribution and reduces negative impacts on various sectors of the economy.]]>
