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
Articles
644 Documents
<![CDATA[Model Rangkaian-T Pembangkit Listrik Tenaga Bayu untuk Analisis Aliran Daya Tiga-Fase ]]>
<![CDATA[Rudy Gianto]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.902
<![CDATA[Recently, penetration of wind power plant in electric power distribution system has increased significantly. The wind power plant penetration can affect the system’s steady state and dynamic conditions. Furthermore, as the electric power distribution system is usually unbalanced, it has to be analyzed in a three-phase manner. Therefore, in order for the system conditions to be properly evaluated, development of a three-phase model of the system components (including wind power plant) is necessary. This paper proposes a simple method for modeling and integrating fixed-speed wind power plant for steady state analysis (i.e., power flow analysis) of the three-phase distribution system. The proposed method is based on the T-circuit model which has previously been successfully applied to single-phase electric power systems. In this study, the single-phase T-circuit model is modified and extended so as to facilitate three-phase power flow analysis under unbalanced system conditions. Application of the proposed model in two three-phase distribution systems (i.e. 33-node and 25-node systems) is also investigated and presented in this paper. Results of the investigation show that the proposed method is valid and accurate.]]>
<![CDATA[Kombinasi Protokol Routing OSPF dan BGP dengan VRRP, HSRP, dan GLBP ]]>
<![CDATA[Debbi Irfan Mudhoep]]>;
<![CDATA[Linawati]]>;
<![CDATA[Oka Saputra]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.942
<![CDATA[Vocational High Schools as educational institution that adopt vocation based curriculum get the advantages and benefits of the development of the teaching factory. Teaching factory is a product and business oriented concept of learning in response to the challenges and development of the industry. However, during the pandemic period, teaching factory management faces many obstacles, one of which is in the performance of the network. The current network uses static routing network protocol which has no backup line or track. It is, therefore, suggested to apply dynamic routing OSPF and BGP with the VRRP, HSRP, and the GLBP workload method as the backup line which is measured through the throughput, delay, and packet loss parameter, for its Quality of Service (QoS). The research scenario stage applies each routing protocol to each performance method, so that it can be measured to obtain the expected QoS results at end users. The best result that will be recommended is routing OSPF by VRRP method because it has less than 1 second time comparison when there is a network failure. It is shown in the QoS result of 3.96, which shows that it is very satistactory compared to others.]]>
<![CDATA[Analisis Perbandingan Kinerja Brushless Motor Menggunakan Metode Eksperimen ]]>
<![CDATA[Erwan Eko Prasetiyo]]>;
<![CDATA[Wahyuni Fajar Arum]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.987
<![CDATA[Energy-saving effort is a challenge in designing a UAV technology. One of many UAV components on the market is brushless motor. There is a possibility that the UAV component's performance does not match the existing specification data. Therefore, it is necessary to do component testing before designing a UAV. This paper presents the results of performance testing of brushless motors types A2212(6T), MR2205, and MT2204. Brushless motor performance is seen based on the amount of thrust, power, and the ratio between thrust to power (N/W). This testing uses an experimental method. The test uses a four-blade propeller type 5140 and a power supply with a DC output capacity of 15-30 V/50 A. The results of the brushless motor test at low power show that the A2212(6T)-2200KV type requires an average power of 25.858 W with a ratio of 0.042 N/W, the MR2205-2300KV type requires an average power of 22.166 W with a ratio of 0.052 N/W, and the MT2204-2300KV type requires an average power of 24.675 W with a ratio of 0.047 N/W. Based on the test data at working current below 1.877 A, it can be seen that the brushless motor type MR2205-2300KV has the best performance because it requires the least power and has the highest ratio value, compared to the other types.]]>
<![CDATA[Implementasi Algoritme Support Vector Machines untuk Klasifikasi Area Terbakar di Lahan Gambut ]]>
<![CDATA[Edi Saputra]]>;
<![CDATA[Ulfa Khaira]]>;
<![CDATA[Zainil Abidin]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.990
<![CDATA[Forest fires have become annual disasters in Indonesia and have an impact on peatland degradation. Many forest fires occur on peatlands. In August 2019, 810 hotspots were detected in Jambi Province. Burned area of peatland information is needed so that the goverment can determine policy on the effectiveness and efficiency of forest management. Information about burned area of peatland is difficult to obtain from field measurements because the area is large and not easily accessible. Landsat data is a type of image from remote sensing technology that can be used to map this area. One method that is often used to estimate the burned area is visual on-screen interpretation. However, this technique requires experienced interpreters. For this reason, this study used digital interpretation techniques using the Support Vector Machine (SVM) algorithm to classify burned area, vegetation, and bare soil from remote sensed data of protected area of peat in Muaro Jambi District, Jambi Province. This study obtained a classifier with the accuracy of 99.8%. The estimated area of peat based on the SVM classifier on August 15th 2019 are 1,396.89 hectares at the burned area class, 7,069.5 hectares at the vegetation class, and 1,089.54 hectares at the bare soil class.]]>
<![CDATA[Perancangan Sistem Monitoring Konduktivitas dan Padatan Terlarut PDAM Banyumas Berbasis IoT ]]>
<![CDATA[Indah Permatasari]]>;
<![CDATA[Nia Annisa Ferani Tanjung]]>;
<![CDATA[Nur Afifah Zen]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.1023
<![CDATA[PDAM is a company engaged in the distribution of clean water for the community. Some Indonesian people have become PDAM water customers to meet their water needs for their daily activities. Water quality is an important issue because it is closely related to health. In this paper, the design of the water quality monitoring system in PDAM Banyumas based on IoT is carried out by reviewing the parameters of electrical conductivity (EC) and dissolved solids (TDS). The result of measurement data can be accessed via the Android App on smartphone. The application is designed using HTTP and MQTT protocols. HTTP protocol is used on the user interface to retrieve the last measurement data. Meanwhile, the MQTT protocol is used to update measurement data so that the data transmission process is faster. The system will send notification via telegram if the water quality is below quality standard. The measurement accuracy test is done by comparing the monitoring device with the certified measuring instrument on samples of bottled drinking water and PDAM water. The results show that the performance of the designed monitoring device was 97.31% and the quality of the PDAM Banyumas water is very stable and safe for consumption.]]>
<![CDATA[Ekstraksi Emosi Majemuk Kalimat Bahasa Indonesia Menggunakan Convolutional Neural Network ]]>
<![CDATA[Aripin]]>;
<![CDATA[Wisnu Agastya]]>;
<![CDATA[Hanny Haryanto]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i2.1051
<![CDATA[Facial expressions can strengthen the information conveyed in interactive communication. In the field of developing virtual characters specifically for facial characters, facial expressions are needed to animate a facial virtual character to make it look natural like a human. One type of emotional expression is a compound emotional expression, which is a combination of two or more basic emotions. For example, the expression of disappointed emotions is a combination of anger and sadness. Facial expressions can appear due to emotional stimulation, one of which is the meaning of the sentence. This research aims to extract emotional data from Indonesian sentences using the multi-label classification process of the CNN model so as to produce compound facial expressions that are applied in virtual character animation. The basic emotion classes used in the classification process are anger, disgust, fear, happiness, sadness, and surprise. Based on the experimental results, the CNN model can produce an accuracy of 94.5% with the composition of training data and test data is 8: 2. The classification process result shows that each sentence can produce more than one basic emotion class that forms compound expressions. The results of the visualization of compound expressions for each sentence can represent compound expressions.]]>
<![CDATA[Karakterisasi Conducted Emission Noise pada Inverter di Sistem Photovoltaic Off-Grid ]]>
<![CDATA[Yudhistira]]>;
<![CDATA[Dwi Mandaris]]>;
<![CDATA[Yoppy]]>;
<![CDATA[Hutomo Wahyu Nugroho]]>;
<![CDATA[Prayoga Bakti]]>;
<![CDATA[Bayu Utomo]]>;
<![CDATA[Tyas Ari Wahyu]]>;
<![CDATA[Siddiq Wahyu Hidayat]]>;
<![CDATA[Ferdaus Ario Nurman]]>;
<![CDATA[Tri Desmana Rachmilda]]>;
<![CDATA[Deny Hamdani]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.1066
<![CDATA[The conducted emission noise caused by the inverter in the off-grid photovoltaic (PV) system has been characterized. Noise that propagates in the conduction path was generated from the phenomenon of inverter switching for the power conversion process from direct current (DC) to alternating current (AC). The IEC 62920: 2017 and CISPR 25: 2016 standards were used to measure the noise generated by the inverter on the DC side. The conducted emission noise measurements for the inverter were carried out in three conditions, namely no-load condition, connected to a 60 W incandescent lamp load, and connected to the incandescent lamp load and dimmer for power variation. Measurements were made on five inverters with different power capacities and output types. The 200 W, 300 W, and 700 W outputs were for the modified sine wave output voltage, while the 500 W and 1,000 W were for pure sine wave output voltage. The measurement results show that when the inverter is connected to the load of the incandescent lamp and the dimmer, the 500 W and 1,000 W pure sine wave inverters have a low peak noise level and less potential to cause electromagnetic interference on the DC side.]]>
<![CDATA[Desain dan Simulasi Dual Input Single Output Buck Converter dengan Kontrol Fuzzy ]]>
<![CDATA[Abdul Rahman Wachid]]>;
<![CDATA[Endro Wahjono]]>;
<![CDATA[Syechu Dwitya Nugraha Nugraha]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i1.1069
<![CDATA[In this paper, a dual input single output buck converter with fuzzy control is designed and simulated for a DC load supply using the PSIM software. The dual input single output buck converter can work with two different sources. The use of the two power sources of photovoltaic and wind turbine is an alternative solution for obtaining a greater rated power to supply DC loads. The solar panel and the wind turbine will supply the power for the dual input buck converter circuit simultaneously. For the two power sources to work simultaneously, the duty cycle is set using fuzzy control, so that the output voltage can match the desired voltage. Simulation testing is carried out with photovoltaic conditions with varying irradiation and temperature values, as well as varying wind speeds in the wind turbine, i.e, between 4-8 m/s. The simulation results show that the dual-input single-output buck converter can work when powered by two different power sources with a stable output voltage of the converter at its set point, i.e., 14.4 volts.]]>
<![CDATA[Optimalisasi Keluaran Panel Surya Menggunakan Solar Tracker Berbasis Kamera Terintegrasi Raspberry Pi ]]>
<![CDATA[Agus Suryanto]]>;
<![CDATA[Noor Hudallah]]>;
<![CDATA[Tatyantoro Andrasto]]>;
<![CDATA[Cahyo Fajar Adhiningtyas]]>;
<![CDATA[Seftriana Anifa Khusniasari]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 3: Agustus 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i3.1142
<![CDATA[Maximum output from the operation of solar cell depends on the temperature of the solar cell, solar radiation, wind speed, the state of the earth's atmosphere, the orientation of the solar cell and the position of the location of the solar cell against the sun (tilt angle). Solar Tracker is a device that automatically change the orientation of a solar panel towards the position of the sun and increasing the insolation. Initially the solar tracker is set up using LDR then image processing-based settings can reduce tracking errors. Image-based solar tracker still uses a full-sized computer that requires a lot of energy and space. This research aims to improve the accuracy of the direction of the solar panel and optimize the output of the solar panel by increasing the angle of solar radiation (insolation) using the Solar Tracker with a camera sensor and a Raspberry Pi minicomputer. The use of cameras is intended to reduce errors from LDR-based systems and the use of Raspberry Pi replaces full-sized computer. The method to track position of the sun is by tracking the pixel with highest value. From the output analysis the solar panel proved to be optimized by the application of Raspberry Pi-integrated camera solar tracker. The comparison of the output power between the stationary solar panel and the solar panel installed on the Raspberry Pi-integrated camera solar tracker is 1: 1,389 (21,5487W: 29,8822W) in the no-load test and 1: 1,2042 (6,0344W: 7, 2671W) in tests with a 12V-5W bulb load.]]>
<![CDATA[Model Penahan Ketinggian Quadrotor Berbasis PID dengan Jaringan Syaraf Tiruan Propagasi Mundur ]]>
<![CDATA[Faisal Fajri Rahani]]>;
<![CDATA[Dinan Yulianto]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jnteti.v10i2.1249
<![CDATA[A quadrotor is a type of Unmanned Aerial Vehicle (UAV) or an unmanned flying vehicle flying remotely or using automatic control. In carrying out its mission, a quadrotor requires a good control system. One of the control systems in the quadrotor system is the altitude control system. Altitude control will control the quadrotor according to the desired altitude, whether there are interference and the quadrotor load. The widely used control method is the PID control. Unfortunately, the PID control produces a poor response because the PID constant is fixed, whereas the interference when the quadrotor flies will fluctuate. Therefore, this study offers control that can make a self-adjustment when exposed to specific interference. The method offered in this study is a PID control with Artificial Neural Networks (ANN). The ANN system will tune the PID components in real-time according to the occurring interference. The use of the PID with ANN results in a faster rise time response of 0.0594 seconds, a decrease in overshoot of 7.58%, a decrease in the steady-state error of ± 0.0672, and a decrease in settling time of 1.031 seconds compared to conventional PID. It shows that the PID with ANN results in better control than the PID alone.]]>
