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All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik IJITEE (International Journal of Information Technology and Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Agus Bejo, Agus
Universitas Gadjah Mada
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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IMPLEMENTASI ENCODER SANDI REED SOLOMON PADA CONTROLLER AREA NETWORK Wisnu Kartika; I Wayan Mustika; Agus Bejo
Prosiding SNST Fakultas Teknik Vol 1, No 1 (2015): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 6 2015
Publisher : Prosiding SNST Fakultas Teknik

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Abstract

EMI (Electromagnetic Interference) banyak ditemui pada sistem otomotif dan industri yang menggunakan kabel untuk menghubungkan antar device. Masalah utama saat ini ialah rentan terjadinya interferensi pada komunikasi antar device pada  Controller Area Network (CAN). Maka akan diusulkan suatu skema rancangan untuk mengatasi burst error. Akan digunakan metode Reed Solomon Code dengan panjang kode (31, 27). Penelitian ini dapat membantu untuk mengurangi electromagnetic interference yang sering terjadi pada industri dan otomotif. Hasil dari penelitian ini ialah perhitungan bit paritas dan informasi yang akan dikirim melalui encoder sandi Reed Solomon. Kata kunci- ARQ, Controller Area Network, CRC, Reed Solomon codes.
PENGUKURAN BLOK WINDOW TERBAIK BERDASARKAN MSE UNTUK SEGMENTASI CITRA SIDIK JARI BERBASIS MEAN DAN VARIANS Dwiyanto Dwiyanto; Agus Bejo; Risanuri Hidayat
Prosiding SNST Fakultas Teknik Vol 1, No 1 (2016): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 7 2016
Publisher : Prosiding SNST Fakultas Teknik

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Abstract

Segmentasi citra sidik jari merupakan langkah yang dilakukan untuk memisahkan bagian objek dengan bagian background. Paper ini akan melakukan segmentasi citra sidik jari dengan cara membagi citra sidik jari dengan 6 ukuran blok window (3x3, 6x6, 10x10, 15x15, 20x20, 25x25) yang tidak saling tumpang tindih untuk tiap citra sidik jari. Segmentasi dilakukan berdasarkan mean dan varians tiap blok window. Pengukuran hasil segmentasi citra sidik jari dilakukan dengan memberikan noise titik putih (salt) dan titik hitam (pepper) untuk tiap citra sidik jari hasil segmentasi. Citra sidik jari yang terdapat noise titik putih (salt) dan titik hitam (pepper) kemudian diperbaiki dengan median filter dengan ukuran kernel yang berbeda dan dihitung nilai MSE masing-masing citra. Hasil eksperimen menunjukkan  bahwa ukuran blok window 15x15 mempunyai nilai rata-rata MSE  terkecil yaitu 37,17. Kata kunci: Blok Window, Mean, MSE, Sidik jari, Varians
Perancangan Smart Card Reader Menggunakan STM32F4 Discovery Kit Agus Bejo; Mohamad Faiz Hamzah; Addin Suwastono
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 3: Agustus 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Smart card has been a new trend as practical and secure authentication solution in online transactions such as epayment, net-banking, e-money, and other online services. The increasing of smart card-based applications demands higher supply of smart card readers as well. Many types of smart card readers in the market have been existed. However, their feature and software are mostly closed and can not be modified to satisfy the application developer’s requirements to optimize the performance and security of the applications. Therefore, a selfdesigned smart card reader is needed to offer flexibility and ability to be costumized in order to satisfy application developer’s needs. In this research, a smart card reader is designed based on 32-bit microcontroller STM32F407VG which is implemented on STM32F4 Discovery Kit. The proposed smart card reader is evaluated by accessing information resides on the JCOP31 smart card which has been pre-installed by applet with certain APDU. Evaluation results show that the proposed smart card reader is able to access smart card properly, having good portability on different platform machines and having good performance as indicated by the CWT and CBT which are faster than the recommended ones.
Integrasi Login Tanpa Mengetik Password pada WordPress Mochamad Arifin; Agus Bejo; Warsun Najib
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 2: Mei 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Nowadays, almost everyone has an account on the internet, but some of them often use simple and guessable password, since a complex password is difficult to memorize. Surely, it will compromise the account security and system themselves. Therefore, an integrated login system without typing and remembering password is needed. This paper describes the development of an integrated login system that can perform authentication on a device without typing and remembering password by developing a WordPress plugin and a smartphone application. The development of the system has successfully shown the QR Code on the WordPress login page and automatically redirect the user to the admin page when the login process is done through scanning the QR code by using smartphone. Password only needs to be typed in the first login, and users do not have to retype it for the next login process. Android application development has resulted a password manager application that helps the users to manage the password and to have a secure password storage. Login integration without typing a password can improve account security and reduce the risk of man-in-the-middle and key-logger attack.
Real-Time Indonesian Language Speech Recognition with MFCC Algorithms and Python-Based SVM Wening Mustikarini; Risanuri Hidayat; Agus Bejo
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 2 (2019): June 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1031.978 KB) | DOI: 10.22146/ijitee.49426

Abstract

Abstract — Automatic Speech Recognition (ASR) is a technology that uses machines to process and recognize human voice. One way to increase recognition rate is to use a model of language you want to recognize. In this paper, a speech recognition application is introduced to recognize words "atas" (up), "bawah" (down), "kanan" (right), and "kiri" (left). This research used 400 samples of speech data, 75 samples from each word for training data and 25 samples for each word for test data. This speech recognition system was designed using Mel Frequency Cepstral Coefficient (MFCC) as many as 13 coefficients as features and Support Vector Machine (SVM) as identifiers. The system was tested with linear kernels and RBF, various cost values, and three sample sizes (n = 25, 75, 50). The best average accuracy value was obtained from SVM using linear kernels, a cost value of 100 and a data set consisted of 75 samples from each class. During the training phase, the system showed a f1-score (trade-off value between precision and recall) of 80% for the word "atas", 86% for the word "bawah", 81% for the word "kanan", and 100% for the word "kiri". Whereas by using 25 new samples per class for system testing phase, the f1-score was 76% for the "atas" class, 54% for the "bawah" class, 44% for the "kanan" class, and 100% for the "kiri" class.
Evaluasi Platform Perangkat Keras Sistem Tertanam untuk Unit Kontrol Parkir Otomatis Wahyu Dewanto; Agung Fathurrahman; Agus Bejo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 4: November 2023
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.v12i4.6277

Abstract

Automatic parking system is one of the parking management technologies that is widely used in various institutions today. An automatic parking system works by controlling a parking gate automatically to open and close the gate and record the vehicle’s license plate when entering and exiting using access control such as a smart card or radio frequency identification (RFID). One of the challenges in implementing an automatic parking system is traffic congestion during high traffic conditions. This challenge arises because the control unit in the automatic parking system takes a relatively long time to process and store images from the camera. This research examined several embedded system platforms as automatic parking system control units, including Raspberry Pi 3B, Raspberry Pi 4B, and Orange Pi Zero Plus. The evaluation is intended to find the best control unit platform based on several criteria, such as the execution time in capturing images, storing images, and the consumed power. From the evaluation results, it can be concluded that the Raspberry Pi 4B platform results in the fastest execution time for capturing and storing images, with an average time of 1,827.9 ms. Meanwhile, the Orange Pi Zero Plus platform achieves the lowest power consumption at 1.9 W. Based on the evaluation results, the Raspberry Pi 4B is recommended as the control unit if the automatic parking system requires a high-performance device. Otherwise, the Orange Pi Zero Plus is more recommended if the automatic parking system requires a low-power device.
Co-Authors Addin Suwastono, Addin Agung Fathurrahman Arifin, Mochamad Dwiyanto Dwiyanto Hamzah, Mohamad Faiz I Wayan Mustika Mochamad Arifin Mohamad Faiz Hamzah Risanuri Hidayat Wahyu Dewanto Warsun Najib Wening Mustikarini Wisnu Kartika