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
577 Documents
<![CDATA[Person Reidentification pada Sistem Surveillance Cerdas Menggunakan Metode Bag of Visual Feature ]]>
<![CDATA[Muhammad Yusuf Manshur]]>;
<![CDATA[Wahyono]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.249
<![CDATA[Camera-based surveillance systems have been widely used to monitor public places for ensuring security and safety. One of the problems in the surveillance process is identifying human objects on different CCTV cameras, which is referred to as person reidentification (Re-ID). Re-ID is the process of identifying whether the images of human objects, captured from two or more images from CCTV cameras with the different viewpoints, are the same person or not. This paper proposes a method based on visual features of the object image, named as Bag of Visual Feature (BOVF). BOVF works by representing image data as a collection of local features that are used with a feature clustering mechanism. BOVF implementation uses the Density Based Spatial Clustering of Applications with Noise (DBSCAN) clustering methods in the Histogram of Oriented Gradient (HOG) features. The results of this study with 70 image frames from iLIDS-VID dataset obtained the best accuracy at R-20 by 88% using DBSCAN with a processing speed of 1.85 seconds.]]>
<![CDATA[Sistem Pemantauan dan Pengendalian Debit Fluida Berbasis Arduino dan Website ]]>
<![CDATA[Noviana Widyaningrum]]>;
<![CDATA[Unan Yusmaniar Oktiawati]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.261
<![CDATA[IoT can combine hardware and software for communication between them. The application of this system can be done on a solenoid valve to regulate the flow via online, which can be varied based on current temperature. The fluid flows are validated with a flow meter sensor that sends data to a server to decide whether the flows need to be added to the furnace or not. There is a database server that stores data in cloud from sensors so that the system can run realtime. The system is displayed on a website with dashboard display regarding the flow and the condition of the valves in realtime. In testing, black box testing is used to make more use of functional things in the system designed for the convenience of users of fluid flow monitoring and control, based on the appearance of the website used, the functions available, the results of the sensors provided, and the data transmission process that is running. Furthermore, the system can show that the function of the hardware or website to monitor and control fluid discharge has been running well and can be used by users easily and beneficially.]]>
<![CDATA[Analisis Layanan Sistem Informasi Akademik Perguruan Tinggi Berbasiskan Fuzzy Service Quality ]]>
<![CDATA[I.G.P. Asto Buditjahjanto]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.264
<![CDATA[A higher education institution as an organization that offers academic information system services must be able to analyze their academic information system services. To analyze academic information system services, higher education institution must be able to measure the gap between perceptions and expectations of the users. The analysis is carried out on the five dimensions of service quality (Servqual) and its indicators so that each gap can be identified whether positive or negative. Fuzzy service quality method is used in this study because it can eliminate inconsistencies, uncertainties, and inadequacy in assessing an existing problem in academic information system. The results show that all gap values in the service quality dimension show negative signs. This shows that the services provided do not meet user's expectations. Therefore, it needs improvement for those services. The highest gap in the dimension of service quality is reliability at -1.010, followed by responsiveness at -0.906, assurance at -0.831, empathy at -0.703, and tangibility at -0.685.]]>
<![CDATA[Navigasi Robot Penjaga Gawang Berdasarkan Prediksi Posisi dan Waktu Kedatangan Bola ]]>
<![CDATA[Setiawardhana]]>;
<![CDATA[Rudy Dikairono]]>;
<![CDATA[Djoko Purwanto]]>;
<![CDATA[Tri Arief Sardjono]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.295
<![CDATA[Research on wheeled soccer robots has been developed especially for the accuracy of the object detection and classification. This paper solves the problem for ball's position and arrival time prediction also its navigation to block the ball. Previous research used Single Layer Neural Network (SLNN) and Two Layer Neural Network (TLNN) methods. This paper propose a Modified Two-Layer Neural Network (MTLNN) algorithm for increasing the prediction accuracy for ball’s position and its arrival time, also Goalkeeper Robot Navigation (GKRN) algorithm for its navigation. The algorithm was created by modifying the TLNN architecture in the number of nodes to eight inputs and two outputs, with the number of hidden being designed as needed. The accuracy of the prediction greatly affects ball blockade because it is used to navigate the robot. The GKRN algorithm was created by modifying the membership function of the Fuzzy Inferences System (FIS), which is adjusted to the robot's needs. The results showed an increase in prediction accuracy from up to 20 times better for ball position and 4 times better for the arrival time of the ball. Overall, the navigation system obtained a successful rate of 90% for blocking the ball.]]>
<![CDATA[Autentikasi Daun Herbal Menggunakan Convolutional Neural Network dan Raspberry Pi ]]>
<![CDATA[Haryono]]>;
<![CDATA[Khairul Anam]]>;
<![CDATA[Azmi Saleh]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.302
<![CDATA[At this time, the leaf authentication method is widely used in the classification process of herbal plants. Basically, the leaf authentication method compares the image to be identified and the reference image created in the dataset. This paper aims to identify the leaves of herbal plants using an artificial intelligence method, namely Convolutional Neural Network (CNN) that is embedded on Raspberry Pi. CNN has an advantage that it does not require feature extraction, because in CNN, automatic feature extraction already exists. This paper uses seven types of leaves from different herbal plants. Leaf images are taken using a camera and processed by Raspberry Pi, which is integrated with CNN. Identification was carried out on seven types of herbal plants divided into two-thirds of training data and one-third of testing data. The identification process results will be validated with other data not included in the training data and testing data, as well as leaf data other than the seven types of leaves identified. The CNN method shows good results in the authentication process, with an accuracy rate of 93.62% for testing data offline and 91.04% for testing data online.]]>
<![CDATA[Pengaruh Strategi Pengisian Daya Terhadap Kenaikan Beban Puncak Akibat Penetrasi Kendaraan Listrik ]]>
<![CDATA[Boy Ihsan]]>;
<![CDATA[Deny Hamdani]]>;
<![CDATA[Nanang Hariyanto]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.363
<![CDATA[To overcome the problem of energy crisis and global warming, many countries in the world are pushing growth in the use of electric vehicles. In the future, the use of electric vehicles in large numbers will also occur in Indonesia and charging electric vehicles will become a new load on the electricity system. One of the effects of electric vehicle penetration is an increase in the system's peak load. Therefore, this study examines how the increase in daily load due to penetration of electric vehicles and how the strategy of electric vehicles charging to reduce the increase in load on one of the electricity systems in Indonesia, namely the Jawa-Bali system. The calculation results show that the Jawa-Bali electrical system is only able to accommodate electric vehicle penetration by 20% if the problem of losses, instability, and line loading are ignored. In the case of 10% penetration of electric vehicles, the peak load of the Jawa-Bali system increased by 5,857 MW. However, by scheduling electric vehicle charging, the increase in peak load can be reduced by 3,232 MW and by using the V2G scheme, the energy supplied by the system generator can be reduced by 20,003 MWh.]]>
<![CDATA[Desain dan Simulasi Bidirectional DC-DC Converter untuk Penyimpanan Energi pada Sistem Fotovoltaik ]]>
<![CDATA[Armadilla Sukma Pratiwi]]>;
<![CDATA[Syechu Dwitya Nugraha]]>;
<![CDATA[Epyk Sunarno]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.377
<![CDATA[In this paper, a bidirectional DC-DC converter for energy storage in the photovoltaic system has been designed and simulated on MATLAB Simulink. The bidirectional DC-DC converter can work in two modes, charge and discharge mode. The energy storage system will work to store energy into the battery when the power generation capacity is higher than load demand. Then, the energy stored in the battery will be used for the DC bus supply when the power generation capacity is lower than the load demand. To get a constant voltage on the high voltage side (DC bus voltage) and a constant current on the low voltage side (charging current), a PI controller is used. Simulations were carried out with 1,000 W/m2 irradiation to get the power generation higher than the load demand (charge mode) and 200 W/m2 irradiation to get the power generation lower than the load demand (discharge mode) with constant temperature of 25 °C. The test result shows that a bidirectional DC-DC converter can work in charge and discharge modes, which is shown by battery charging currents and the increase or decrease in battery voltage.]]>
<![CDATA[Media Informasi untuk Bank Baterai Berbasis Augmented Reality ]]>
<![CDATA[Raymond Y. Purba]]>;
<![CDATA[Suci Aulia]]>;
<![CDATA[Agus Gunarso]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.381
<![CDATA[Based on data from the pre-questionnaire related information media needs at PT. Telkom WITEL Bandung, 75% of employees have not known yet about battery bank information in detail and the rest of population only know from manual book and internet. The difficulty to get information from a device causes few actions and decisions that are not in accordance with standard procedures. On the other hand, manual book only give information concretely, making it difficult for employees to understand the information quickly and precisely which causes low reading interest. Implementation of Augmented Reality (AR) as a battery bank information media could be the best option of technology application that could deliver information digitally. In AR, users will get the experience that information appears directly like physical object so it would be more realistic, interactive, and easy to understand. In this study, a design of AR applications uses Luther Sutopo methodology based on Multimedia Development Life Cycle (MDLC) with AR Marker Based Tracking Type. The results of functional test show that the application is running properly and ready to be used as a battery bank information media system at PT. Telkom WITEL Bandung. This application can also be downloaded at Google Play Store.]]>
<![CDATA[Metode Naive Bayes Classifier – Smoothing pada Sensor Smartphone untuk Klasifikasi Aktivitas Pengendara ]]>
<![CDATA[Haniah Mahmudah]]>;
<![CDATA[Okkie Puspitorini]]>;
<![CDATA[Nur Adi Siswandari]]>;
<![CDATA[Ari Wijayanti]]>;
<![CDATA[Eliya Alfatekha]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.382
<![CDATA[Most causes of death are traffic accidents. This paper aims to obtain parameters of identification of driving activities that can be developed to detect accidents in the next studies. Data is collected by sensors on smartphones, using accelerometer and gyroscope sensors. The proposed method uses Naive Bayes Classifiers (NBC) algorithm to determine driving activity, by dividing dataset into training and testing data using k-fold parameters. NBC can work using less training data, by calculating the probability value of each class from means and variance of each feature to classify classes efficiently. The results show that the accuracy of the classification is higher if a smoothing process is carried out, using single exponential smoothing method, before the clacification process of the NBC algorithm is done. The testing using 8 k-fold CV without smoothing process, using smoothing alpha (α) = 0.1, and using α = 0.9 obtain the accuracy of 98.43%, 99.27%, and 98.43%, respectively. It can be concluded that the NBC method combined with smoothing method using α = 0.1 produces greater accuracy.]]>
<![CDATA[Studi Teknis Genset Termodifikasi Menggunakan Gas Alam dengan Variasi Tekanan Masukan ]]>
<![CDATA[Faiz Husnayain]]>;
<![CDATA[Agung Budiyanto]]>;
<![CDATA[Fauzan Hanif Jufri]]>;
<![CDATA[I Made Ardita Y.]]>
<![CDATA[ Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020 ]]>
Publisher : <![CDATA[Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada ]]>
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DOI: 10.22146/.v9i3.393
<![CDATA[Every year Indonesia experiences an increase in the number of electricity customers. However, there are still many areas that do not yet have electricity supply or have frequent disturbances. Therefore, we need a generator set as the main electricity supply or as a backup for these areas. Natural gas can be used as generator fuel because of its abundant availability and is more environmentally friendly. However, the availability of gasfueled generators in Indonesia is still very rare, so that additional equipment such as regulators, converter kits, and air mixing equipment for gas can be used on gasoline generators. Due to this background and its potential, testing is carried out to determine the performance of the modified generator set when using natural gas fuels. The method used is to compare engine performance by varying the value of the generator's input pressure, which is 0.5 and 0.03 bar. The results observed were the SFC value, power quality, exhaust gas temperature, and the noise level produced by the generator. The results of this test are that the voltage and frequency generated is still within the specified normal limits, the exhaust gas temperature and the noise level generated when the input pressure is 0.5 bar and 0.03 bar are relatively the same, and the SFC value generated when the input pressure is 0.5 bar is 5.7-25% smaller than the SFC value at 0.03 bar input pressure.]]>
