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Risanuri Hidayat
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jnteti@ugm.ac.id
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Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281
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INDONESIA
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 13 Documents
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Search results for , issue "Vol 9 No 3: Agustus 2020" : 13 Documents clear
Metode Naive Bayes Classifier – Smoothing pada Sensor Smartphone untuk Klasifikasi Aktivitas Pengendara Haniah Mahmudah; Okkie Puspitorini; Nur Adi Siswandari; Ari Wijayanti; Eliya Alfatekha
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1913.01 KB) | DOI: 10.22146/.v9i3.382

Abstract

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.
Studi Teknis Genset Termodifikasi Menggunakan Gas Alam dengan Variasi Tekanan Masukan Faiz Husnayain; Agung Budiyanto; Fauzan Hanif Jufri; I Made Ardita Y.
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1267.343 KB) | DOI: 10.22146/.v9i3.393

Abstract

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.
Analisis Epitope Sel T pada SARS-Cov2 dengan Pendekatan Bioinformatika Miftahurrahma Rosyda; Faisal Fajri Rahani
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1048.241 KB) | DOI: 10.22146/.v9i3.408

Abstract

At the beginning of 2020, the world was shocked by the spread of global outbreaks that attacked respiratory like the SARS outbreak in 2003, namely COVID-19. The virus that causes the outbreak called SARS-Cov2. It turns out to have a similarity of ~ 87.5% with SARS-Cov. This similarity can be used to develop drugs and vaccines that are compatible with the current virus. In this case, the bioinformatics approach can be carried out as an initial stage of vaccine development. One way to develop vaccines is epitope-based vaccines. Biological data available and submitted to the public regarding T cell epitopes and protein sequences in viruses can be processed with several bioinformatics tools available online. This study compared the calculation of physicochemical characters between the SARS-Cov epitope and the SARS-Cov2 protein sequence at the same location. The characters being compared are molecular weight, point of isoelectric, aliphatic index, GRAVY, instability index, and antigenicity. Data processing is evaluated by correlation matrix. The results of the processing show that the physicochemical character between SARS-Cov and SARS-Cov2 has a strong relationship.

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