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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 14 Documents
 1   2 
Search results for , issue "Vol 8, No 2: August 2010" : 14 Documents clear
SEBUAH MODEL BERBASIS PENGETAHUAN UNTUK PENGENDALIAN FORMASI SISTEM ROBOT MAJEMUK Andi Adriansyah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 8, No 2: August 2010
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v8i2.608

Abstract

Study of multi-robot system has been popular in recent years. This system is able to reduce processing time of some processes, the cost and complexity of the system. However, multi-robot system also has some problems. One of the problems faced by these systems is how to control robots in a certain formation when carrying out its functions. Several methods have been offered to resolve the existing problems. This study tries to offer a method to solve the problem, by modeling the multi-robot systems and implement a control system in order to maintain a specific formation. The study attempted to use a controller based on knowledge base system. Model is developed using MATLAB software and simulated to determine the performance. Several experiments are conducted to determine the movement of the robot and its ability to maintain a specific formation. From the experiments it can be said that the modeling of multiple-robot system has been reliable. In addition, formation control actions have also been running well, although there should be further development.
IMPROVED VOLTAGE OF CASCADED INVERTERS USING SINE QUANTIZATION PROGRESSION Bambang Sujanarko; Mochamad Ashari; Mauridhi Hery Purnomo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 8, No 2: August 2010
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v8i2.613

Abstract

The previous methods of cascaded multilevel inverter (CMLI) can improve power quality but the methods have low voltage output if the DC voltages limited by the voltage rating of power semiconductor. To improve the amplitude of CMLI output voltage, this paper proposes a new DC voltage progression. The progression based on sine quantization method (SQM), which determines a sequence of DC voltages from discrete amplitudes of sine wave function. The method also collaborates with step equal residual area method (SERAM) to minimized total harmonics distortions (THD). A single-phase CMLI that consist four H-Bridges simulated and implemented to verify the methods. Amplitude output voltage and THD results of simulations and experiments indicate that the sine quantization progression produce the highest output voltage than other DC voltage progressions, with power quality or THD in the accepted region. The amplitude of output voltage have linier function with amplitude equal 0.6665 times of H-Bridges numbers and have exponential function of THD with value below 5%.
A FUZZY LOGIC CLASSIFICATION OF INCOMING PACKET FOR VOIP Suardinata Suardinata; Kamalrulnizam Bin Abu Bakar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 8, No 2: August 2010
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v8i2.618

Abstract

The Voice over Internet Protocol (VoIP) technology is cheaper and does not need new infrastructure because it has availables in the global computer (IP) network. Unfortunately, transition from PSTN to VoIP networks have emerged new problems in voice quality. Furthermore, the transmission of voice over IP networks can generate network congestion due to weak supervision of the traffic incoming packet, queuing and scheduling. This congestion affects the Quality of Service (QoS) such as delay, packet drop and packet loss. Packet delay effects will affect the other QoS such as: unstable voice packet delivery, packet jitter, packet loss and echo. Priority Queuing (PQ) algorithm is a popular technique used in the VoIP network to reduce delays. But, the method can result in repetition. This recursive leads to the next queue starved. To solving problems, there are three phases namely queuing, classifying and scheduling. It will be applied to the fuzzy inference system to classify the queuing incoming packet (voice, video and text). To justify the research of the improved PQ algorithm be compared against the algorithm existing.
ENHANCED NEURO-FUZZY ARCHITECTURE FOR ELECTRICAL LOAD FORECASTING Hany Ferdinandoa; Felix Pasila; Henry Kuswanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 8, No 2: August 2010
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v8i2.609

Abstract

Previous researches about electrical load time series data forecasting showed that the result was not satisfying. This paper elaborates the enhanced neuro-fuzzy architecture for the same application. The system uses Gaussian membership function (GMF) for Takagi-Sugeno fuzzy logic system. The training algorithm is Levenberg-Marquardt algorithm to adjust the parameters in order to get better forecasting system than the previous researches. The electrical load was taken from East Java-Bali from September 2005 to August 2007. The architecture uses 4 inputs, 3 outputs with 5 GMFs. The system uses the following parameters: momentum=0.005, gamma=0.0005 and wildness factor=1.001. The MSE for short term forecasting for January to March 2007 is 0.0010, but the long term forecasting for June to August 2007 has MSE 0.0011. 

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