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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 2,614 Documents
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Towards better performance: phase congruency based face recognition Muthana H. Hamd; Rabab A. Rasool
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 6: December 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i6.17300

Abstract

Phase congruency is an edge detector and measurement of the significant feature in the image. It is a robust method against contrast and illumination variation. In this paper, two novel techniques are introduced for developing alow-cost human identification system based on face recognition. Firstly, the valuable phase congruency features, the gradient-edges and their associate dangles are utilized separately for classifying 130 subjects taken from three face databases with the motivation of eliminating the feature extraction phase. By doing this, the complexity can be significantly reduced. Secondly, the training process is modified when a new technique, called averaging-vectors is developed to accelerate the training process and minimizes the matching time to the lowest value. However, for more comparison and accurate evaluation,three competitive classifiers:  Euclidean distance (ED),cosine distance (CD), and Manhattan distance (MD) are considered in this work. The system performance is very competitive and acceptable, where the experimental  results show promising recognition rates with a reasonable matching time.
Multiobjective H2/H∞ Control Design with Regional Pole Constraints Hardiansyah Hardiansyah; Junaidi Junaidi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 1: March 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i1.765

Abstract

This paper presents multiobjective H2/H∞ control design with regional pole constraints. The state feedback gain can be obtained by solving a linear matrix inequality (LMI) feasibility problem that robustly assigns the closed-loop poles in a prescribed LMI region. The proposed technique is illustrated with applications to the design of stabilizer for a typical single-machine infinite-bus (SMIB) power system. The LMI-based control ensures adequate damping for widely varying system operating conditions. The simulation results illustrate the effectiveness and robustness of the proposed stabilizer.
A Novel Part-of-Speech Set Developing Method for Statistical Machine Translation Herry Sujaini; Kuspriyanto Kuspriyanto; Arry Akhmad Arman; Ayu Purwarianti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 3: September 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i3.79

Abstract

Part of speech (PoS) is one of the features that can be used to improve the quality of statistical-based machine translation. Typically, the language PoS determined based grammar of the language or adopt from other languages PoS. This work aims to formulate a model to developing PoS as linguistic factors to improve the quality of machine translation automatically. The research method using word similarity approach, where we perform clustering of the words contained in a corpus. Further classes will be defined as PoS set obtained for a given language.We evaluated the results of the PoS that defined computational results using machine translation system MOSES as the system by comparing the results of the SMT are using PoS sets generated manually, while the assessment of the system using BLEU method. Language that will be used for evaluation is English as the source language and Indonesian as the target language.
Goal-seeking Behavior-based Mobile Robot Using Particle Swarm Fuzzy Controller Andi Adriansyah; Yudhi Gunardi; Badaruddin Badaruddin; Eko Ihsanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.1111

Abstract

Behavior-based control architecture has successfully demonstrated their competence in mobile robot development. Fuzzy logic system characteristics are suitable to address the behavior design problems. However, there are difficulties encountered when setting fuzzy parameters manually. Therefore, most of the works in the field generate certain interest for the study of fuzzy systems with added learning capabilities. This paper presents the development of fuzzy behavior-based control architecture using Particle Swarm Optimization (PSO). A goal-seeking behaviors based on Particle Swarm Fuzzy Controller (PSFC) are developed using the modified PSO with two stages of the PSFC process. Several simulations and experiments with MagellanPro mobile robot have been performed to analyze the performance of the algorithm.  The promising results have proved that the proposed control architecture for mobile robot has better capability to accomplish useful task in real office-like environment.
Data Selection and Fuzzy-Rules Generation for Short-Term Load Forecasting Using ANFIS Mamunu Mustapha; Mohd Wazir Mustafa; Saiful Nizam Abd. Khalid
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3413

Abstract

Forecasting accuracy depends on data identification and model parameters. Volume of data and good analysis are the key factors that influence the accuracy of forecasting algorithm. This paper focused on data analysis with aim of determining the actual variables that affect the load consumption. Correlation analysis was used to determine how the load consumption is related to the forecasting variables (model inputs), and hypothesis test to justify the correlation coefficient of each variable. This produced tree different scenarios which ware used to forecast the load within short-term time frame. On the other hand, subtractive clustering and Fuzzy c-means (FCM) algorithms ware compared in fuzzy rules generation using Adaptive Neuro-Fuzzy Inference System (ANFIS) model, for short term electric load forecasting. Forecasting using Hypothesis test data with Subtractive clustering algorithm gave better accuracy compared to the other two approaches. But FCM algorithm is faster in all the three approaches. In conclusion, hypothesis test on the correlation coefficient of the data is a commendable practice for data selection and analysis in short-term load forecasting. Also, subtractive clustering algorithm is good in generating appropriate number of fuzzy rules, and the number depends on the number of input variables. Fuzzy c-means algorithm reduces the number of the rules irrespective of the number of input variables. 
A Review on Methods of Identifying and Counting Aedes Aegypti Larvae using Image Segmentation Technique Mohamad Aqil Mohd Fuad; Mohd Ruddin Ab Ghani; Rozaimi Ghazali; Mohamad Fani Sulaima; Mohd Hafiz Jali; Tole Sutikno; Tarmizi Ahmad Izzuddin; Zanariah Jano
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 3: September 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i3.6422

Abstract

Aedes aegypti mosquitoes are a small slender fly insect that spreads the arbovirus from flavivirus vector through its sucking blood. An early detection of this species is very important because once these species turn into adult mosquitoes a population control becomes more complicated. Things become worse when difficult access places like water storage tank becomes one of the breeding favorite places for Aedes aegypti mosquitoes. Therefore, there is a need to help the field operator during the routine inspection for an automated identification and detection of Aedes aegypti larvae, especially at difficult access places. This paper reviews different methodologies that have been used by various researchers in identifying and counting Aedes aegypti. The objective of the review was to analyze the techniques and methods in identifying and counting the Aedes Aegypti larvae of various fields of study from 2008 and above by taking account their performance and accuracy. From the review, thresholding method was the most widely used with high accuracy in image segmentation followed by hidden Markov model, histogram correction and morphology operation region growing.
Optimizing Laying Hen Diet using Multi-Swarm Particle Swarm Optimization Gusti Ahmad Fanshuri Alfarisy; Wayan Firdaus Mahmudy; Muhammad Halim Natsir
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7765

Abstract

Formulating animal diet by accounting fluctuating cost, nutrient requirement, balanced amino acids, and maximum composition simultaneously is a difficult and complex task. Manual formulation and Linear Programming encounter difficulty to solve this problem. Furthermore, the complexity of laying hen diet problem is change through ingredient choices. Thus, an advanced technique to enhance formula quality is a vital necessity. This paper proposes the Multi-Swarm Particle Swarm Optimization (MSPSO) to enhance the diversity of particles and prevent premature convergence in PSO. MSPSO work cooperatively and competitively to optimize laying hen diet and produce improved and stable formula than Genetic Algorithm, Hybridization of Adaptive Genetic Algorithm and Simulated Annealing, and Standard Particle Swarm Optimization with less time complexity. In addition, swarm size, iteration, and inertia weight parameters are investigated and show that swarm size of 50 for each sub-swarm, total iteration of 16,000, and inertia weight of 6.0 should be used as a good parameter for MSPSO to optimize laying hen diet.
About Quality of Optical Channels in Wavelength Division Multiplexing Systems of Optic Fibers Mirazimova Gulnora Hasanovna
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.10300

Abstract

Researches and the analysis of factors of the systems influencing quality with division according to radiation wavelength are given in article. Especially the communication quality in systems with wave division of channels is influenced by hindrances from Four Wave Mixing. In this regard the technique of definition of number of products of nonlinear effect of Four Wave Mixing getting to ranges of working channels, results of calculation of combinational products for the different number of channels in systems with division according to radiation wavelength is given. Power of a hindrance of Four Wave Mixing in systems with wave division of channels is calculated. Methods of reduction of influences of these nonlinear effects are considered. Conclusions and recommendations on ensuring quality of optical channels are provided in systems with wave division.
Co-clustering algorithm for the identification of cancer subtypes from gene expression data Logenthiran Machap; Afnizanfaizal Abdullah; Zuraini Ali Shah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12773

Abstract

Cancer has been classified as a heterogeneous genetic disease comprising various different subtypes based on gene expression data. Early stages of diagnosis and prognosis for cancer type have become an essential requirement in cancer informatics research because it is helpful for the clinical treatment of patients. Besides this, gene network interaction which is the significant in order to understand the cellular and progressive mechanisms of cancer has been barely considered in current research. Hence, applications of machine learning methods become an important area for researchers to explore in order to categorize cancer genes into high and low risk groups or subtypes. Presently co-clustering is an extensively used data mining technique for analyzing gene expression data. This paper presents an improved network assisted co-clustering for the identification of cancer subtypes (iNCIS) where it combines gene network information with gene expression data to obtain co-clusters. The effectiveness of iNCIS was evaluated on large-scale Breast Cancer (BRCA) and Glioblastoma Multiforme (GBM). This weighted co-clustering approach in iNCIS delivers a distinctive result to integrate gene network into the clustering procedure.
Smart health monitoring system using IoT based smart fitness mirror Amgad Muneer; Suliman Mohamed Fati; Saddam Fuddah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.12434

Abstract

The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user’s body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user’s body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.

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