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Contact Name
Nizirwan Anwar
Contact Email
nizirwan.anwar@esaunggul.ac.id
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telkomnika@ee.uad.ac.id
Editorial Address
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INDONESIA
TELKOMNIKA (Telecommunication Computing Electronics and Control)
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
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)
Articles 2,614 Documents
Nature grasping by a cable-driven under-actuated anthropomorphic robotic hand Li Tian; Nadia Magnenat Thalman; Daniel Thalmann; Jianmin Zheng
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.11006

Abstract

Human hand is the best sample for humanoid robotic hand and a nature grasping is the final target that most robotic hands are pursuing. Many prior researches had been done in virtual and real for simulation the human grasping. Unfortunately, there is no perfect solution to duplicate the nature grasping of human. The main difficulty comes from three points. 1. How to 3D modelling and fabricate the real hand. 2. How actuated the robotic hand as real hand. 3. How to grasp objects in different shapes like human hand. To deal with these three problems and further to provide a partial solution for duplicate human grasping, this paper introduces our method to solve these problems from robotic hand design, fabrication, actuation and grasping plan. Our modelling progress takes only around 12 minutes that include 10 minutes of 3D scanning of a real human hand and two minutes for changing the scanned model to an articulated model by running our algorithm. Our grasping plan is based on the sampled trajectory and easy to implement for grasping different objects. Followed these steps, a seven DOF robotic hand is created and tested in the experiments.
A brief review: security issues in cloud computing and their solutions Iqbal Ahmed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 6: December 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i6.12490

Abstract

Cloud computing is an Internet-based, emerging technology, tends to be prevailing in our environment especially in the field of computer sciences and information technologies which require network computing on large scale. Cloud Computing is a shared pool of services which is gaining popularity due to its cost, effectiveness, avilability and great production. Along with its numerous benefits, cloud computing brings much more challenging situation regarding data privacy, data protection, authenticated access, Intellectual property rights etc. Due to these issues, adoption of cloud computing is becoming difficult in today’s world. In this review paper, various security issues regarding data privacy and reliability, key factors which are affecting cloud computing, have been addressed and also suggestions on particular areas have been discussed.
Prediction schizophrenia using random forest Zuherman Rustam; Glori Stephani Saragih
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.14837

Abstract

Schizophrenia is a mental illness with a very bad impact on sufferers, attacking the part of human brain that disables the ability to think clearly. In 2018, Rustam and Rampisela classified Schizophrenia by using Northwestern University Schizophrenia Data, based on 66 variables consisting of group, demographic, and questionnaires statistics, based on the scale for the assessment of negative symptoms (SANS), and scale for the assessment of positive symptoms (SAS), and then classifiers that used are SVM with Gaussian kernel and Twin SVM with linear and Gaussian kernel. Furthermore, this research is novel based on the use of random forest as a classifier, in order to predict Schizophrenia. The result obtained is reported in percentage of accuracy, both in training and testing of random forest, which was 100%. This classification, therefore, shows the best value in contrast with prior methods, even though only 40% of training data set was used. This is very important, especially in the cases of rare disease, including schizophrenia.
Translating cuneiform symbols using artificial neural network Arwa Hamed Salih Hamdany; Raid Rafi Omar-Nima; Lubab H. Albak
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 2: April 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i2.16134

Abstract

Cuneiform language is an old language that was invented by the people of Sumerian nation. It is an essential language for many archeologists. Especially who are interested in studying and investigating the old nations of Iraq. Dealing with this type of language usually requires specialist to translate its symbols, which are basically forms of nail shapes. This study presents a new approach to translate the cuneiform writing by employing artificial neural network (ANN) technique. Effectively, multi-layer perceptron (MLP) neural network has been adapted for translating the Sumerian cuneiform symbol images to their corresponding English letters. This work has been successfully established and it attained 100%.
Blood Vessel Enhancement and Segmentation for Screening of Diabetic Retinopathy M. Usman Akram; Ibaa Jamal; Anam Tariq
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 2: June 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i2.802

Abstract

Diabetic retinopathy is an eye disease caused by the increase of insulin in blood and it is one of the main cuases of blindness in idusterlized countries. It is a progressive disease and needs an early detection and treatment. Vascular pattern of human retina helps the ophthalmologists in automated screening and diagnosis of diabetic retinopathy. In this article, we present a method for vascular pattern ehnacement and segmentation. We present an automated system which uses wavelets to enhance the vascular pattern and then it applies a piecewise threshold probing and adaptive thresholding for vessel localization and segmentation respectively. The method is evaluated and tested using publicly available retinal databases and we further compare our method with already proposed techniques. 
High Recognition Ratio Image Processing Algorithm of Micro Electrical Components in Optical Microscope Wu Jie; Zuren Feng; Lei Wang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i4.304

Abstract

In order to process small components of original image under the microscope, firstly, this paper adopts median filtering algorithm to enhance targets; and the targets are sharpened by using lateral inhibition algorithm, the edge of targets is outlined. In order to get reliable target region, adaptive threshold segmentation algorithm is used to extract need target region, and characteristics of target is used to distinguish multiple targets. Based on the chip resistor, one tiny component, in the captured image, we judge if the chip resistor is qualified by calculating the pixels area values. The experimental results show that, the image processing algorithm and qualified detection algorithm is reasonable, which provides the theoretical basis and implementation method of effective target extraction and further qualified test.
Distributed Cooperative Multicell Precoding Based on Local Channel State Information Jing An; Guofeng He; Youwu Xu; Bin Wang; Sen Xu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 3: September 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i3.1807

Abstract

Cooperative multicell precoding is an attractive way of improving the performance in multicell downlink scenarios especially for terminals at cell edges. Multiple base stations in a given area serve each terminal after precoding, which can coordinate the inter-cell interference and achieve higher performance. Most previous work in the area has focus on centralized precoding which requires gathering all transmitters’ channel state information (CSI) at central station (CS) through backhaul and then precoding at CS. However, the requirements on backhaul signaling and computational power scales rapidly in large and dense networks, which usually make such fully centralized approaches impractical. In this paper, we study two practical precoding strategies with only local CSI under a relatively realistic scenario. Performance is finally illustrated through numerical simulations.
A Comparison of Retweet Prediction Approaches: The Superiority of Random Forest Learning Method Hendra Bunyamin; Tomas Tunys
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.v14i3.3150

Abstract

We consider the following retweet prediction task: given a tweet, predict whether it will be retweeted. In the past, a wide range of learning methods and features has been proposed for this task. We provide a systematic comparison of the performance of these learning methods and features in terms of prediction accuracy and feature importance. Specifically, from each previously published approach we take the best performing features and group these into two sets: user features and tweet features. In addition, we contrast five learning methods, both linear and non-linear. On top of that, we examine the added value of a previously proposed time-sensitive modeling approach. To the authors’ knowledge this is the first attempt to collect best performing features and contrast linear and non-linear learning methods. We perform our comparisons on a single dataset and find that user features such as the number of times a user is listed, number of followers, and average number of tweets published per day most strongly contribute to prediction accuracy across selected learning methods. We also find that a random forest-based learning, which has not been employed in previous studies, achieves the highest performance among the learning methods we consider. We also find that on top of properly tuned learning methods the benefits of time-sensitive modeling are very limited.
A Proposed Design of Unit Cell of Metamaterial for 5G Mobile Communication Jamal Mohammed Rasool
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.v15i3.6079

Abstract

This paper is under in-depth investigation due to suspicion of possible plagiarism on a high similarity indexIn this manuscript a design of metamaterial unit cells which are new artificial materials made of periodic arrangement much smaller than the guided wavelength, are proposed which are suitable to work for 5G mobile communication working with millimeter frequency band at 28 GHz due the high demand for the frequency spectrum for mobile networks .The structures of unit cells were simulated using High Frequency Structure Simulator HFSS software. The design starts with the metamaterial structure which is composed of double rectangular (DRR) and circular split ring resonator (DSRR). The results of simulation showed very good results such as wide operating frequency band which is 1.34 GHz with very law radiation losses the unit cell designed to overrun the radiation losses which are appear with the work of metamaterials.
Tree Physiology Optimization in Constrained Optimization Problem A. Hanif Halim; I. Ismail
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 2: April 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i2.9021

Abstract

Metaheuristic algorithms are proven to be more effective on finding global optimum in numerous problems including the constrained optimization area. The algorithms have the capacity to prevail over many deficiencies in conventional algorithms. Besides of good quality of performance, some metaheuristic algorithms have limitations that may deteriorate by certain degree of difficulties especially in real-world application. Most of the real-world problems consist of constrained problem that is significantly important in modern engineering design and must be considered in order to perform any optimization task. Therefore, it is essential to compare the performance of the algorithm in diverse level of difficulties in constrained region. This paper introduces Tree Physiology Optimization (TPO) algorithm for solving constrained optimization problem and compares the performance with other existing metaheuristic algorithms. The constrained problems that are included in the comparison are three engineering design and nonlinear mathematic problems. The difficulties of each proposed problem are the function complexity, number of constraints, and dimension of variables. The performance measure of each algorithm is the statistical results of finding the global optimum and the convergence towards global optimum.

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