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Risanuri Hidayat
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INDONESIA
IJITEE (International Journal of Information Technology and Electrical Engineering)
Published by Universitas Gadjah Mada
ISSN : -     EISSN : 25500554     DOI : https://doi.org/10.22146/ijitee.48545
Core Subject : Engineering,
Electrical & Electronics Engineering
IJITEE (International Journal of Information Technology and Electrical Engineering), with registered number ISSN 2550-0554 (Online), is a peer-reviewed journal published four times a year (March, June, September, December) by Department of Electrical engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada. IJITEE (International Journal of Information Technology and Electrical Engineering) invites manuscripts in the various topics include, but not limited to, Information Technology, Power Systems, Digital Signal Processing, Communication Systems
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 5 Documents
 1 
Search results for , issue "Vol 4, No 1 (2020): March 2020" : 5 Documents clear
Improving Phoneme to Viseme Mapping for Indonesian Language Anung Rachman; Risanuri Hidayat; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 1 (2020): March 2020
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.47577

Abstract

The lip synchronization technology of animation can run automatically through the phoneme-to-viseme map. Since the complexity of facial muscles causes the shape of the mouth to vary greatly, phoneme-to-viseme mapping always has challenging problems. One of them is the allophone vowel problem. The resemblance makes many researchers clustering them into one class. This paper discusses the certainty of allophone vowels as a variable of the phoneme-to-viseme map. Vowel allophones pre-processing as a proposed method is carried out through formant frequency feature extraction methods and then compared by t-test to find out the significance of the difference. The results of pre-processing are then used to reference the initial data when building phoneme-to-viseme maps. This research was conducted on maps and allophones of the Indonesian language. Maps that have been built are then compared with other maps using the HMM method in the value of word correctness and accuracy. The results show that viseme mapping preceded by allophonic pre-processing makes map performance more accurate when compared to other maps.
LNA Prototype at 54 MHz to 88 MHz Using Discrete Components Prapto Nugroho; Ivan Muhammad Ihsan Izetbegovic; Wahyu Dewanto
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 1 (2020): March 2020
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.56153

Abstract

This paper presents a design and prototyping of a Low-Noise Amplifier (LNA) for Wireless Regional Area Network (WRAN) operating in TV broadcast bands between 54 MHz – 88 MHz. The LNA design was then implemented by using discrete components. Components values was obtained by utilized DC analysis according to specifications which follows the Institute of Electrical and Electronics Engineering (IEEE) 802.22 standard on WRAN technical specifications. Simulation with 88 MHz produced S11 = -5.72 dB, S12 = -41.57 dB, S21 = 15.07 dB, S22 = -4.76 dB, Noise Figure (NF) = 3.9 dB, Input Third Order Intercept Point (IIP3) = 2.21 dBm, and power consumption of 45.39 mW. Experiments results on 88 MHz showed S11 = -6.13 dB and S21 = 0.74 dB.
A Microstrip Antenna Design Using an Heuristic Algorithm I Made Adhi Wiryawan; Maria Veronica Astrid Wahyuningtyas; Anugerah Galang Persada; Dyonisius Dony Ariananda
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 1 (2020): March 2020
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.56343

Abstract

Microstrip antennas have several advantages. Some of them are that they have a compact shape and small dimensions. Moreover, they are also easy to be fabricated and easily connected as well as integrated with other electronic devices. Currently, designing antennas conventionally is limited by time, energy, and experience as well as expertise. As an alternative, a way to design antennas with revolutionary methods is developed using algorithms and computing. Algorithm design techniques can overcome limitations and automatically find practical solutions that usually take a long time to discover. The particle swarm optimization algorithm and a genetic algorithm can find solutions from microstrip antennas. Objective functions play an essential role in heuristic algorithms. With a proper objective function, simulation results are obtained on the particle swarm optimization algorithm with a return loss value of -47.837, VSWR of 1.0083, and impedance of 46.805 Ω. In contrast, the genetic algorithm obtains return loss of -16.157 dB, impedance of 50.233 Ω, and VSWR of 1.3687.
A High-Frequency Surface Wave Radar Simulation Using FMCW Technique for Ship Detection Ahmad Nugroho Jati; Ahmad Fauzi Haqqoni; Iswandi Iswandi; Risanuri Hidayat
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 1 (2020): March 2020
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.56344

Abstract

Indonesia is an archipelagic country with a vast sea area. This vast sea area becomes a challenge in conducting regional surveillance to maintain maritime conditions. The use of buoys and satellites still has shortcomings in carrying out surveillance despite its excellent surveillance capabilities. A high-frequency radar technology with 3-30 MHz frequency and surface wave propagation are very suitable because it has a radar range that can cross the horizon or commonly refer to as Over the Horizon (OTH). The Frequency Modulated Continuous Wave (FMCW) technique on this radar obtains distance and velocity information by a continuously transmitted frequency modulation. The use of radar in Indonesia for marine surveillance is still infrequent. Therefore, it is relatively difficult to conduct testing and obtain data. In addition, the direct examination requires extended time, so a simulation program is needed. This paper discusses the design of a High-Frequency Surface Wave Radar (HFSWR) simulation program using FMCW modulation technique. The simulation program detected two objects based on time delays due to the distance and velocity of the object with a maximum range of 350 km. It displayed the results in an informative manner. The object detection was based on the results of the Fast Fourier Transform (FFT) from the mixed signals. The mixed signal is a combination of transmitted signal and reflected signal in which there are time delay components due to the object. The simulation program had been tested with input values of distance and velocity that vary, both for one object and two objects, in the radial direction. It generated output that was close to the input value with a level of accuracy of ± 2 km.
Applying Machine Learning for Improving Performance Classification on Driving Behavior Ahmad Iwan Fadli; Selo Sulistyo; Sigit Wibowo
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 1 (2020): March 2020
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.56919

Abstract

Traffic accident is a very difficult problem to handle on a large scale in a country. Indonesia is one of the most populated, developing countries that use vehicles for daily activities as its main transportation.  It is also the country with the largest number of car users in Southeast Asia, so driving safety needs to be considered. Using machine learning classification method to determine whether a driver is driving safely or not can help reduce the risk of driving accidents. We created a detection system to classify whether the driver is driving safely or unsafely using trip sensor data, which include Gyroscope, Acceleration, and GPS. The classification methods used in this study are Random Forest (RF) classification algorithm, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) by improving data preprocessing using feature extraction and oversampling methods. This study shows that RF has the best performance with 98% accuracy, 98% precision, and 97% sensitivity using the proposed preprocessing stages compared to SVM or MLP.

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