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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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Technology Acceptance Model (TAM) untuk Sistem Smart Lighting di PT. XYZ Teja Laksana; Novian Anggis Suwastika; Muhammad Al Makky
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 2: Mei 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1231.796 KB) | DOI: 10.22146/jnteti.v11i2.3784

Abstract

This research was conducted to identify and measure the significance of the factors or variables that influence technology acceptance for a smart lighting system built based on the internet of things (IoT) and artificial intelligence (AI) technology implemented in XYZ company. The smart lighting system implemented was a dedicated smart lighting system for office space (more than 20 m2 to 60 m2) to sense the conditions and make automatic adjustments to room conditions. Before mass production, the smart lighting system would be reviewed for its technology acceptance by users using the technology acceptance technology model (TAM). TAM is a method used to identify factors that affect the technology acceptance based on the functionality of the smart lighting system. Based on the smart lighting purposes and conditions from the XYZ company, six variables influencing the acceptance of smart lighting systems, namely reliability and accuracy (RA), perceived ease of use (PEOU), perceived usefulness (PU), attitude toward using (ATU), behavior intention (BI), and actual system use (AU) were proposed. These variables influenced each other and formed eight hypotheses, namely H1, H2, H3, H4, H5, H6, H7, and H8. Using the purposive sampling technique, validity test with product-moment correlation, and Cronbach’s alpha validity test, five hypotheses had a positive and significant effect, namely H1, H4, H5, H6, and H7. The RA variable influenced the PU variable, the PU variable influenced the ATU variable, the PEOU variable affected the ATU variable, the ATU variable influenced BI, and the PU variable affected BI. Meanwhile, the three hypotheses had negative and insignificant impacts, namely H2, H3, and H8. The RA variable did not affect the PEOU, the PEOU variable did not affect the PU, and the BI variable did not affect the AU variable.
Sistem Pengenalan Penggunaan Masker dan Pemantauan Suhu Penumpang Pesawat Menggunakan Sensor Fusion Feni Isdaryani; Noor Cholis Basjaruddin; Aldi Lugina
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 2: Mei 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1503.82 KB) | DOI: 10.22146/jnteti.v11i2.3835

Abstract

Transportation is currently an unavoidable necessity. However, the COVID-19 pandemic has impacted all lines of industry, including the Indonesian aviation transportation industry. Technology is one of the solutions to deal with these problems. The monitoring system of masked face recognition and body temperature detection for the check-in process of passengers at the airport is aimed to be developed in this research. The contribution of this research is that the system can distinguish the type of face mask used. Therefore, this monitoring system classified only medical masks and N95/KN95 respirator masks as ‘Good Masked’. IP camera and thermal camera are used to identify a masked face and body temperature, respectively. The sensor fusion method was used for decision-making on passengers whether they can be departed or not. The decision was taken based on the measured body temperature, the use of standardized face masks, and the face recognition of the airport passengers. Convolutional neural network (CNN) method was used for face and face mask recognition. The CNN model training was conducted four times according to the four proposed scenarios. The CNN model that has been trained can distinguish a masked face and a face without a mask. The best results were obtained in the fourth scenario with the comparison of the training dataset to the testing dataset was 9:1 and the epoch was 500 times. The basic deep learning model used for face detection was the single shot multibox detector (SSD) using the ResNet-10 architecture. Meanwhile, the CNN method with the MobileNetV2 architecture was used to detect the use of masks. The accuracy of the CNN model for face recognition and mask recognition was 100%. All check-in monitoring and verification process data were displayed on the web application which was built on the localhost.
Optimasi Sistem Pembangkit Listrik Tenaga Hybrid di Pulau Enggano Dyah Ayu Kartika Sari; Fransisco Danang Wijaya; Husni Rois Ali
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 2: Mei 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1085.491 KB) | DOI: 10.22146/jnteti.v11i2.3849

Abstract

Enggano Island is one of the outermost regions using diesel power plants (Pembangkit Listrik Tenaga Diesel - PLTD) as their source of electrical energy. PLTD, which began its operations in 2017, consists of three units of generator machines capable of generating 730 kW of power, with a total of 1,050 customers and electricity needs of 1,097,883 kWh/year. Although power plants are readily available, in reality, the electricity problem is still a fundamental unresolved issue on the island. The average fuel consumption to operate a PLTD is 21 tons/month or Rp582,757,000.00 per month, assuming the fuel price is Rp9,800.00 per liter. The high operating expenses resulted in electricity only being supplied for sixteen hours per day. The utilization of PLTD also produces very high carbon dioxide (CO2) emissions. It is not in line with the government's commitment to transition to net zero emissions by 2060. The utilization of new renewable energy (Energi Baru dan Terbarukan - EBT), targeted at 23% by 2025, is still not optimal. The paper aims to discover Enggano Island's optimal hybrid power plant configuration in terms of technicality and economic feasibility. Economic feasibility is reviewed using the net present cost (NPC), and cost of economic (COE) approaches. In addition, sustainability analysis is also carried out from environmental aspects. From this study, the most optimal configuration based on the lowest system cost was configuration 2 of scenario 1, consisting of photovoltaic (PV) 1,005 kW, diesel of 250 kW, and 594 battery units. This configuration can produce electricity of 1,576,115 kWh/year with an NPC value of Rp31.7 billion rupiah and a COE value of Rp1,998.75 per kWh. This configuration also has good environmental sustainability because it has a renewable fraction value of 91%.
Exploratory Data Analysis untuk Pembelajaran Daring Sinkron Berdasarkan Gambar Digital AFEA Syefrida Yulina; Mona Elviyenti
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 2: Mei 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1132.318 KB) | DOI: 10.22146/jnteti.v11i2.3867

Abstract

The spread of COVID-19 throughout the world has affected the education sector. In some higher education institution, such as Polytechnic Caltex Riau (PCR), it is mandatory for students to participate in synchronous or asynchronous learning activities via virtual classroom. Synchronous online learning is usually supported by video conferencing media such as Google Meeting or Zoom Meeting. The communication between lecturers and students is captured as an image as evidence of students’ interaction and participation in certain learning subjects. These images can provide information for lecturers in determining students’ internal feelings and measuring students’ interest through facial emotions. Taking this reason into account, the current research aims to analyze the emotions detected in facial expression through images using automatic facial expression analysis (AFEA) and exploratory data analysis (EDA), then visualize the data to determine the possible solution to improve the educational process’ sustainability. The AFEA steps applied were face acquisition to detect facial parts in an image, facial data extraction and representation to process feature extraction on the face, and facial expression recognition to classify faces into emotional expressions. Thus, this paper presents the results obtained from applying machine learning algorithms to classify facial expressions into happy and unhappy emotions with mean values of 5.58 and 2.70, respectively. The data were taken from the second semester of 2020/2021 academic year with 1,206 images. The result highlighted the fact that students showed the facial emotion based on the lecture types, hours, departments, and classes. It indicates that there are, in fact, several factors contributing to the variances of students’ facial emotions classified in synchronous online learning.
Pemodelan Pembangkit Listrik Tenaga Bayu Kecepatan Variabel untuk Analisis Aliran Daya Rudy Gianto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 3: Agustus 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.v11i3.1749

Abstract

The use of variable speed wind turbines (pembangkit listrik tenaga bayu, PLTB) for electricity generation has increased. It contrasts with the fixed-speed PLTB, whose usage is decreasing. The major reason for PLTB’s rapid development is that it has better wind power extraction or collection capabilities than the fixed-speed PLTB. Variable speed operation in a PLTB can be achieved using a doubly-fed induction generator (DFIG) application as the primary energy converter. The crucial initial step in investigating and analyzing power system containing PLTB that must be done is modeling all the components of the power system (including PLTB). An analysis of this power system is mostly conducted to evaluate its performance or appearance. This paper discusses the DFIG-based modeling of the variable speed PLTB to be applied in a power flow analysis of electric power systems. The proposed PLTB model was obtained based on formulas that calculate the power and power losses of the PLTB. The typically challenging power electronics converters modeling of DIFG was not required during the process of building the model. It differs from the previously reported methods in which two different models must be used to accommodate the power flow analysis in subsynchronous or super synchronous conditions. In this paper, the DFIG-based PLTB is represented through a mathematical model. This model could be used to express the DFIG, either in the subsynchronous or super synchronous conditions. It was subsequently integrated into the power flow analysis to evaluate the system’s steady-state performance. The results of this case study will be further presented in this paper. In this study, the application of the proposed methods in the interconnected powers system containing PLTB was then examined. The results confirm the validity of the proposed DFIG model.
Penerapan Floyd-Warshall untuk Pencarian Rute Terpendek pada Aplikasi Notifikasi Kecelakaan Lalu Lintas Haniah Mahmudah; M. Fajar Ibrahim; Okkie Puspitorini; Ari Wijayanti; Nur Adi Siswandari
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.v11i4.2201

Abstract

In the case of an accident, a prompt response is needed to prevent accidents or provide assistance to traffic accident victims. Several ways can be carried out to address this problem. One of them is by developing several smartphone applications for accident detection and accident notification that provide aid in traffic accidents. The existing application to assist the victims merely presents the shortest route from the respondent to the victim’s location without any features that help the respondent find a route to the nearest hospital and police station. Therefore, this study develops a smartphone application for accident alerts for victims’ relatives and respondents, which assists in locating the victim’s position and the closest hospitals and police stations. This accident notification app for smartphones utilizes open-source software and is very scalable. The outcome of this study is an Android application capable of sending accident notification broadcasts, allowing the victim’s relatives and respondents to get accident notifications and drive to the accident place using the route given by the application. In addition, the developed app also provides information about the location of the nearest hospital and police station, allowing respondents nearby the location to help the victim promptly. The results of testing the application using the black box method on the Android platform indicated that 100% of the features of this application were running well. The shortest route with the Floyd-Warshall algorithm was 4.199 km, with no route deviations from the distance testing scenario. The average speed of notification delivery response from victims to respondents was 27.86 ms.
Identifikasi Penggunaan Masker yang Tepat pada Wajah Berbasis Deteksi Mulut dan Hidung Denny Hardiyanto; Ihtiari Prastyaningrum; Umi Kholifah; Dyah Anggun Sartika
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.v11i4.3077

Abstract

During the pandemic, the proper use of face masks is very critical to reduce and prevent the transmission of the COVID-19 between people. Unfortunately, many people are still careless about this proper use of masks like using masks to cover only their mouth or chin. There are also people who do not wear masks when traveling or interacting. Such conducts indicate the lack of concern for the mask use. This study aims to obtain an identification algorithm for using the face mask appropriately through digital photos/images. The basic algorithm used was the face, nose, and mouth detection algorithm developed by Viola and Jones. These algorithms were then combined so that they formed a strong algorithm for detecting the proper use of the face mask. The data tested were classified into five categories, namely images of proper use of masks, images of masks with visible noses, images of masks with visible mouths, images of faces with masks worn on the chin, and mixed images with various accessories. Results of the study employed sixty testing images with various variations of attributes, the result obtained an accuracy value of 90%, a sensitivity value of 100%, and a specificity value of 62.5%. The low specificity value was caused by many detection errors in the false positive (FP) attribute, meaning that the system can detect objects other than the mouth and nose. This research is expected to be developed and synergized with other applications so that it can raise public awareness about the proper use of masks.
Rekayasa Fitur Berbasis Machine Learning untuk Mendeteksi Serangan DDoS Muhammad Nur Faiz; Oman Somantri; Arif Wirawan Muhammad
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 3: Agustus 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.v11i3.3423

Abstract

Distributed network attacks, also known as distributed denial of service (DDoS) are a major threat and problem for internet security. DDoS is an attack on a network aiming to disable server resources. These attacks increase every year with the current state of the COVID-19 pandemic. One of countermeasures to minimize the DDoS impact is the intrusion detection system (IDS) command. IDS techniques are currently still employing traditional methods so that they have many limitations compared to techniques and tools used by attackers because traditional IDS methods only use signature-based detection or anomaly-based detection models which cause many errors. Network data packet traffic has a complex nature, both in terms of sizes and sources. This research utilized the ability of artificial neural network (ANN) to detect normal attacks or DDoS. A classification technique with ANN method is a solution to these issues. Based on the shortcomings of the traditional IDS, this study aims to detect DDoS attacks using feeder machine learning-based feature engineering techniques to improve the IDS development. Using the UNSW-NB15 dataset with the ANN method, this study also aims to analyze and obtain training function combinations and the best hidden layer architectures of ANNs to solve the detection and classification problems of DDoS packets in computer networks. As a result, the training function combinations and hidden layer architectures of the ANN can provide a high level of DDoS recognition accuracy. Based on experiments conducted with three schemes and an ANN schema architecture technique with eight features as input, the highest accuracy was 98.22%. Feature selection plays an essential role in detection result accuracies and machine learning performances in classification problems.
Perencanaan Pengembangan Pembangkit Sistem Muna-Buton dengan Mempertimbangkan Sistem Interkoneksi Ahmad Fatana; Sarjiya; Lesnanto Multa Putranto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 3: Agustus 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.v11i3.3508

Abstract

Electrical energy consumption has increased annually. It is in line with the fulfillment of electricity sales for the last five years (2013-2017) with a 5.1% growth per year. Muna and Buton are large islands in Southeast Sulawesi with a population of 360,682 and an area of 7,712.18 km2. Muna and Buton are two main cities in Southeast Sulawesi that are developing rapidly. Those two regions are relatively rich in natural potential, promoting local economic growth. The primary source of electricity for both regions is Buton. Current electricity consumption in Muna and Buton is relatively high, with a peak load of 37 MW primarily fulfilled by diesel power plants (pembangkit listrik tenaga diesel, PLTD) of 30.15 MW. The government's target to achieve a new renewable energy mix (NRE) of 23% in 2025 and 31% in 2050 is contrary to the situation of generations in Muna and Buton, which is currently still dominated by PLTD. The planning was conducted by looking at its effect on the cost of generation construction, reserve margin, energy mix, and total cost. The desired optimization value was achieved through several performed scenarios, i.e., an isolated or pre-interconnection scenario, assuming each system was separated, and an interconnection system, assuming that interconnection was performed in Muna and Buton system. The optimization method was carried out using mixed-integer linear programming (MILP) by employing the OSeMOSYS software platform. The optimization results show that the Muna-Buton generation expansion planning has been successfully carried out. Of the several performed scenarios, the scenario with the interconnection system can be selected as the best option. It is based on the total cost value and reduced generation costs of 1,073 IDR per kWh in 2022 and 1,362 IDR per kWh in 2047, with an average of 1,202 IDR per kWh.
Evaluasi Laman Penerimaan Mahasiswa Baru dengan WebQual 4.0 dan Importance-Performance Analysis Aditya Gusti Mandala Putra; Dinan Yulianto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 3: Agustus 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.v11i3.3522

Abstract

An evaluation of the website quality must be considered on an ongoing basis by an institution because the website quality is part of the institution’s image in cyberspace. As a higher education institution, Universitas Ahmad Dahlan (UAD) utilizes the website in the new student admission (NSA) process. Referring to the initial review process using a Blackbox method, it was found that the UAD NSA website had a function that was not working properly. It was also identified that the information content of the registration process displayed was incomplete. This study aims to determine the quality of the UAD NSA website based on the interpretation of the end-users with instruments adopted from the WebQual 4.0 method including usability quality, information quality, and service interaction quality variables. The evaluation process began with the instrument testing which included validity and reliability testing. The process of WebQual 4.0 statistical test was carried out through classical assumption testing which included normality, autocorrelation, multicollinearity, heteroscedasticity testing, t-test, and f-test. The final evaluation process was an importance-performance analysis (IPA) test with the level of conformity, gap, and quadrant analysis between performance and expectations. The results of testing the validity and reliability of 23 instrument items by 100 respondents got an overall value of rtable greater than the value of rcount, which was 0.195, and Cronbach’s alpha value was greater than 0.6 so that the research instrument was valid and reliable. The results of the test involving 250 respondents obtained WebQual 4.0 statistical results, each independent variable (A) partially and simultaneously correlated with the dependent variable (B). The results of the IPA quadrant test indicates that the A2.5 variable related to providing easy-to-understand information needs to be optimized by NSA and web service managers at UAD.

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