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Jurnal Nasional Teknik Elektro dan Teknologi Informasi

JNTETI
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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 10 Documents

Search results for , issue "Vol 10 No 2: Mei 2021" : 10 Documents clear

Ekstraksi Emosi Majemuk Kalimat Bahasa Indonesia Menggunakan Convolutional Neural Network Aripin; Wisnu Agastya; Hanny Haryanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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.

Model Penahan Ketinggian Quadrotor Berbasis PID dengan Jaringan Syaraf Tiruan Propagasi Mundur Faisal Fajri Rahani; Dinan Yulianto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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.

Bel Sekolah Otomatis Berbasis Arduino yang Dikontrol Menggunakan Aplikasi Mobile Muh Pauzan; Indri Yanti
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The school bell is one of the important devices in school. It has been used from years ago to the present. Bell has been improved along with time. Nowadays, research about school bell has been focused on the bell’s controller, such as using software in a computer, placing a keypad on the bell, and even controlling the bell’s schedule, which can only be performed using coding. However, these controllers are not practical; therefore, an efficient school bell is made by using an Android-based application as the controller. Bluetooth is used as a communication tool between the smartphone and the bell. The research method was by conducting a literature study and doing a survey to SDN 1 Sarapati Indramayu. Based on the method, it has been decided to make four modes on the Android application, i.e., regular mode, exam mode, free, dan emergency mode. Regular mode is used in a normal condition, and exam mode is used when the students are doing an exam. If teachers want to ring the bell directly, the free mode is operated. There are four types of bell ring in free mode, i.e., once, twice, three, and four-time rings. Emergency mode is useful when the school is in an emergency, such as earthquakes, floods, and fires. Results show that the maximum range to control the bell is 9 m.

Reduksi Dimensi untuk Meningkatkan Kinerja Pengklasteran Perilaku Siswa pada Sistem e-Learning Yuni Yamasari; Naim Rochmawati; Anita Qoiriah; Asmunin; Atik Wintarti
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The corona pandemic has changed the learning process from face-to-face (offline) to online learning. However, this online learning has caused difficulties in monitoring student behavior by teachers due to reduced direct interaction. Additionally, students often feel isolated. Therefore, this situation causes failure in their learning achievement. This problem encourages a lot of research on modeling related to student behavior. However, previous research did not focus much on improving the model's performance or system being built. In fact, the performance of this model significantly affects the result’s quality of this student behavior mapping. Therefore, this study focuses on improving the performance of student behavior clustering when they interact with the e-Learning system. Performance improvement was made by reducing dimensions of student data with Principal Component Analysis (PCA). Furthermore, two techniques for the centroid initialization were explored to obtain optimal results: random and K-means++. For measuring cluster quality, this study employed the silhouette index. The experimental results show that the clusters with the highest quality are achieved by applying PCA with seven components. In addition, the cluster number for all centroid initialization techniques is three to four. This quality cluster can assist teachers in monitoring student behavior in the e-Learning system.

Estimasi Kondisi Muatan dan Kondisi Kesehatan Baterai VRLA dengan Metode RVP Danang Widjajanto; Beny Maulana Achsan; Fajar Muhammad Noor Rozaqi; Augie Widyotriatmo; Edi Leksono
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Optimization of battery usage, including VRLA battery which is often used for large amounts of energy storage at low prices, is usually pursued by implementing Battery Management System (BMS). To carry out BMS, information about the condition of charge and health is needed. The State of Charge (SoC) is defined as the ratio of the current remaining capacity of the battery to the capacity of the battery before discharge, while the State of Health (SoH) is the ratio between the measured full capacity of a battery to its nominal capacity when it is still in a new condition. SoC and SoH estimation can be held indirectly by using the voltage and current at the battery terminals. This study uses the Coulomb Counting (CC) method and Support Vector Regression (SVR) to estimate SoC and SoH of VRLA batteries which are used as backup energy for the nanogrid system in the laboratory. This study uses a Python machine learning module which enables the implementation of SVR with various types of kernels including linear kernels, polynomial kernel, and RBF kernel. The tests carried out in this research using the grid search module show that the best performance is obtained when using the RBF kernel.

Pengembangan Aplikasi Pembelajaran dengan Menerapkan Model Pembelajaran Teams-Games-Tournament (TGT) Anita Rizky Agustina; Fajar Pradana; Fitra Abdurrachman Bachtiar
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

UPT SMP Negeri 6 Gresik is one of the few educational institutions that implement a Teams-Games-Tournament (TGT) learning model in their day-to-day class learning activities. The TGT learning model can assist students in understanding the learning materials by relying on their friends as age-equivalent tutors and via game elements. The current model that was being applied has several issues, where teachers formed the groups conventionally which could decrease the in-class study time. Conventional ways of forming a group leave room for an unfair knowledge distribution among groups, such as a group having only students who have high grades or low grades only. Other than that, the teachers will make a crossword puzzle conventionally. The playing board is made before a learning material is given to the students and the amount of “words” on the puzzle are determined on much material there is and how many groups are formed. The grouping feature is developed using k-means clustering. The development process used the waterfall development process and Codeigniter framework. This application requirement analysis resulted in four actors, 37 functional requirements, and one non-functional requirement. Testing for this research was done by blackbox testing techniques and whitebox testing techniques.

Tinjauan Pustaka Sistematis: Implementasi Metode Deep Learning pada Prediksi Kinerja Murid Muhammad Haris Diponegoro; Sri Suning Kusumawardani; Indriana Hidayah
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The use of machine learning, which is one of the implementations in the field of artificial intelligence, has penetrated into various fields, including education. By using a combination of machine learning techniques, statistics, and databases, educational data mining can be carried out to find out the patterns that exist in a particular dataset. One use of educational data mining is to predict student performance. The results of student performance predictions can be used as an instrument for monitoring and evaluating the learning process so that it can help determine further steps in order to improve the learning process. This study aims to determine the state of the art implementation of deep learning which is part of machine learning in the context of educational data mining, especially regarding student performance predictions. In this study, a systematic literature review is presented to determine the variation of deep learning techniques or algorithms used and their performance. Twenty scientific publications were found and the average performance achieved in making predictions was 89.85%. The majority of the techniques used are Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) with demographic, behavioral, and academic data features.

Implementasi Struktur Meander Line untuk Mereduksi Ukuran Butler Matrix 2 × 2 Zulfi; Achmad Munir
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Butler matrix is a beamforming network that is commonly used in multibeam antennas because of its simple structure and high efficiency. However, the Butler matrix has relatively large dimensions. Meander line structure is a widely used approach to reduce the dimensions of various microwave devices. This paper describes the implementation of the meander line structure on a 2 × 2 Butler matrix to reduce dimensions. The method used is to apply a meander line structure to the through arm. The 2 × 2 Butler matrix with meander line structure is designed using FR4 epoxy dielectric material with dimensions of 17.9 mm × 36.4 mm to work at a 2.4 GHz resonant frequency. The measurement results show that the 2 × 2 Butler matrix with meander line structure has a reflection coefficient better than -10 dB from 1.88 GHz to 2.93 GHz (fractional bandwidth of 43.75%). The isolation of -6.15 dB, the transmission coefficients of -3.70 dB, and the phase difference between the output ports is 91.37o were achieved at the operating frequency of 2.4 GHz. The application of the meander line structure reduces the dimensions of the Butler matrix 2 × 2 by 34.54%.

Analisis Sentimen Masyarakat terhadap Tindakan Vaksinasi dalam Upaya Mengatasi Pandemi Covid-19 Brian Laurensz; Eko Sediyono
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Coronavirus has become a global pandemic and has spread almost all over the world, including Indonesia. Many negative impacts resulted from the spread of COVID-19 in Indonesia, so the government made vaccination measures to reduce the rate of spread of COVID-19. Responses from the public to vaccination measures are quite diverse on social media Twitter. Some are supportive and some disagree. The purpose of this study is to find out how people's sentiment towards vaccination measures. The data used 845 tweets, using two keywords, "vaksinmerahputih" and "vaksinsinovac." The data is then divided into 253 training data and 592 testing data. The classification will use the SVM and Naïve Bayes methods. The classification result of the Naïve Bayes method received an average accuracy of 85.59%, while SMV of 84.41%. Sentiment results on Naïve Bayes method with keyword "vaksinsinovac" gets positive sentiment of 66% and negative sentiment of 34%, while "vaksinmerahputih" obtains 89% and 11% for positive and negative sentiment, respectively. SVM method with keyword "vaksinsinovac" gets 96% positive and 4% negative, while "vaksinmerahputih" obtains 98% positive and 2% negative. It can be concluded that the results of public sentiment towards vaccination measures received a positive response.

Mobilitas Manusia dan Tingkat Penyebaran Covid-19: Sebuah Analisis Kuantitatif Lukito Edi Nugroho; Arkham Zahri Rakhman
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The Covid-19 pandemic has created many uncertainties and decisions are often made without the support of undisputable facts. The presentation of facts based on quantitative data becomes an important factor to improve the quality of decisions. This paper aims at building support for pandemic fact provisioning through a quantitative approach. Using community mobility data and data on Covid-19 daily transmission rate, this study analyzes the correlation between these two factors in the Special Region of Yogyakarta. Correlation was calculated between daily Covid-19 transmission rate and community mobility in six types of areas that could be linked to social gathering. In the time span between March 2020 and March 2021, the correlation between the daily transmission rate and community mobility in all areas was low (correlation coefficient between 0.03 and 0.33). The result explained that reduced community mobility developed social distancing, which was effective in controlling virus transmission. However, in shorter time spans which contain spikes in mobility to public destination areas triggered by several long holidays, the correlation between the increase of daily Covid-19 cases and the ‘stay at home’ activity increased significantly (correlation coefficient 0,64). This showed the fact that Covid-19 spread is characterized more by family clusters.

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Contact Name
Risanuri Hidayat

Contact Email
risanuri@ugm.ac.id

Phone
+62274-552305

Journal Mail Official
jnteti@ugm.ac.id

Editorial Address
Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281

Location
Kab. sleman,

Daerah istimewa yogyakarta

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Risanuri Hidayat

Contact Email risanuri@ugm.ac.id

Phone +62274-552305

Journal Mail Official jnteti@ugm.ac.id

Editorial Address Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281

Location Kab. sleman, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Risanuri Hidayat

Contact Email
risanuri@ugm.ac.id

Phone
+62274-552305

Journal Mail Official
jnteti@ugm.ac.id

Editorial Address
Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281

Location
Kab. sleman,

Daerah istimewa yogyakarta

INDONESIA