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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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Automated Navigation System based on Weapon-Target Assignment Gayuh Titis Permana; Maman Abdurohman; Mohammad Khairudin; Mohammad Lutfi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 3: December 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i3.735

Abstract

Operating of weapon on the tank is mostly by manually. It is not desired performance for a critical operation. An automatic control system is required to operate the weapon with the target while maintaining the accuracy. In this paper has designed an automatic weapon control system using object image proccessing. Various an image processing methods used to improve the weapon accuracy to obtain the intended target. The method used in digital image processing is the Camshift motion tracking method. This method is compared with the Lucas Canade motion tracking method. This comparison is conducted to found more precise results between the two methods. Results of object image processing are used to control the direction of the weapon that towards the desired goal. The results show that the implementation of the Lucas Canade motion tracking method using fire simulation tools have been successful. The performance of the Lucas Canade motion tracking methods is better than the CamShift method. Using Lucas Canade method for weapon controller is accordance with the purposes.
Phase Open Fault Tolerant Control of High Reliability Doubly-Salient Wound-Field Machine Liwei Shi; Bo Zhou
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 2: June 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i2.48

Abstract

Doubly Salient Wound-Field Machine (DSWFM) can be employed on aeronautics starter-generator because it has good performance on both power generation and starting. To improve the system reliability, a three-phase four bridge legs converter which has fault tolerant capability is proposed to solve one phase open-circuit fault problem of the DSWFM. And the advantage of the proposed converter to the full-bridge converter fault-tolerant mode is analyzed. With the study of DSWFM theory and torque equation, a constant torque fault-tolerant strategy is proposed to keep the performance and reduce the torque ripple. The drive system after fault identification can be reconstructed by the proposed method, and the machine performance can recover quickly. Simulations confirm the feasibility of the proposed fault tolerant system.
Countering Node Misbehavior Attacks using Trust Based Secure Routing Protocol Adnan Ahmed; Kamalrulnizam Abu Bakar; Muhammad Ibrahim Channa; Khalid Haseeb
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 1: March 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i1.1181

Abstract

Wireless sensor networks have gained remarkable appreciation over the last few years. Despite significant advantages and tremendous applications, WSN is vulnerable to variety of attacks. Due to resource constraint nature of WSN, applicability of traditional security solutions is debatable. Although cryptography, authentication and confidentiality measures help in preventing specific types of attacks but they cannot safeguard against node misbehavior attacks and come at significant cost. To address this problem, we propose a Trust Based Secure Routing Protocol (TBSRP) which adopts on-demand routing principle and relies on distributed trust model for the detection and isolation of misbehaving nodes. The TBSRP aims to establish shortest path that contain all trusted nodes, identify packet forwarding misbehavior caused by malicious and faulty nodes and reroute the traffic to other reliable paths. The performance of TBSRP is evaluated in terms of packet delivery ratio, average end-to-end delay, normalized routing load and average throughput. Simulations results show that TBSRP can achieve both high delivery ratio and throughput in presence of various numbers of misbehaving and faulty nodes.
H-WEMA: A New Approach of Double Exponential Smoothing Method Seng Hansun; Subanar Subanar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3096

Abstract

A popular smoothing technique commonly used in time series analysis is double exponential smoothing. Basically, it’s an improvement of simple exponential smoothing which does the exponential filter process twice. Many researchers had developed the technique, hence Brown’s double exponential smoothing and Holt’s double exponential smoothing. Here, we introduce a new approach of double exponential smoothing, called H-WEMA, which combines the calculation of weighting factor in weighted moving average with Holt’s double exponential smoothing method. The proposed method will then be tested on Jakarta Stock Exchange (JKSE) composite index data. The accuracy and robustness level of the proposed method will then be examined by using mean square error and mean absolute percentage error criteria, and be compared to other conventional methods.
Automatic Image Annotation Using CMRM with Scene Information Julian Sahertian; Saiful Akbar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.5160

Abstract

Searching of digital images in a disorganized image collection is a challenging problem. One step of image searching is automatic image annotation. Automatic image annotation refers to the process of automatically assigning relevant text keywords to any given image, reflecting its content. In the past decade many automatic image annotation methods have been proposed and achieved promising result. However, annotation prediction from the methods is still far from accurate. To tackle this problem, in this paper we propose an automatic annotation method using relevance model and scene information. CMRM proposed by [5] is one of automatic image annotation method based on relevance model approach. CMRM method assumes that regions in an image can be described using a small vocabulary of blobs. Blobs are generated from segmentation, feature extraction, and clustering. Given a training set of images with annotations, this method predicts the probability of generating a word given the blobs in an image. To improve annotation prediction accuracy of CMRM, in this paper we utilize scene information incorporate with CMRM. Our proposed method is called scene-CMRM. Global image region can be represented by features which indicate type of scene shown in the image. Thus, annotation prediction of CMRM could be more accurate based on that scene type. Our experiments showed that, the methods provides prediction with better precision than CMRM does, where precision represents the percentage of words that is correctly predicted.
Towards Improving Road Safety using Advanced Vehicular Networks Wajeb Gharibi; Nasrullah Armi
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.v16i2.8210

Abstract

Vehicular Ad-hoc Networks (VANETs) are advanced network technologies applied to improve safety on roads and to offer suitable solutions for Intelligent Transportation Systems (ITS). The goal of VANETs is to assistdrivers and to act as a smart co-pilot that can alret about accidents and help avoiding them while prodivding high-end infotainment systems for both the driver and passengers. Consequently, VANETs can save millions of lives around the world, especially in Saudi Arabia, which has a very high rate of road accidents annualy. In this paper, we introduce and discuss VANETs, related routing protocols, challenging problems, and the existing solutions. This work is a part of a bigger project that aims to enhance VANETs technologies and to updapteITS to significantly promote road safety in general and Saudi Arabia’s roads in particular.
A rapid classification of wheat flour protein content using artificial neural network model based on bioelectrical properties Sucipto Sucipto; Maffudhotul Anna; Muhammad Arwani; Yusuf Hendrawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.9450

Abstract

A conventional technique of protein analysis is laborious and costly. One rapid method used to estimate protein content is near infrared spectroscopy (NIRS), but the cost is relatively expensive. Therefore, it is necessary to find a cheaper alternative measurement such as measuring the bioelectrical properties. This preliminary study is a new rapid method for classified modeling of wheat flour protein content based on the bioelectrical properties. A backpropagation artificial neural network (ANN) was developed to classify the protein content of wheat flour. ANN input were bioelectrical properties, namely capacitance, and resistance and output was a type of the flour, namely hard, medium and soft flour. The result showed that the ANN model could classify the various type of flour. The best ANN model produces a mean square error (MSE) and regression correlation (R) of 0.0399 and 0.9774 respectively. This ANN model could classify the protein content of wheat flour based on the bioelectrical properties and have the potential to be used as a basic instrument to estimate the protein content.
Approximated computing for low power neural networks Gian Carlo Cardarilli; Luca Di Nunzio; Rocco Fazzolari; Daniele Giardino; Marco Matta; Mario Patetta; Marco Re; Sergio Spanò
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.12409

Abstract

This paper investigates about the possibility to reduce power consumption in Neural Network using approximated computing techniques. Authors compare a traditional fixed-point neuron with an approximated neuron composed of approximated multipliers and adder. Experiments show that in the proposed case of study (a wine classifier) the approximated neuron allows to save up to the 43% of the area, a power consumption saving of 35% and an improvement in the maximum clock frequency of 20%.
Low cost smart weather station using Arduino and ZigBee Zaid Khudhur Hussein; Hadi Jameel Hadi; Mousa Riyadh Abdul-Mutaleb; Yaqeen Sabah Mezaal
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.v18i1.12784

Abstract

This paper presents low cost-effective weather station with monitoring system by using ZigBee communication technique that serves as a communication channel by using hardware and sensors to transmit and receive data in the weather station system. Using ZigBee over the Bluetooth for the short coverage distance about (1-10 m) and over the (WLAN) (wireless local area network) or Wi-Fi, a WLAN has limitation like delay, lacking BW of the handover of a large amount of data, and some areas have no internet coverage. The system includes implementation and design for the weather station using Arduino Uno board and five sensors gives sixth reading data (rain state, wind level, air pressure, dust density, temperature and humidity). The data can be stored in SD card on receiving (clouding and main processing side) from more than one transmitter node (ZigBee Network). It can be retrieved the data in any time and date. Results showed the system has no delay and the data reputedly changing ever second with the new reading.
Evaluation of load balancing approaches for Erlang concurrent application in cloud systems Chanintorn Jittawiriyanukoon
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.13150

Abstract

Cloud system accommodates the computing environment including PaaS (platform as a service), SaaS (software as a service), and IaaS (infrastructure as service) that enables the services of cloud systems.  Cloud system allows multiple users to employ computing services through browsers, which reflects an alternative service model that alters the local computing workload to a distant site. Cloud virtualization is another characteristic of the clouds that deliver virtual computing services and imitate the functionality of physical computing resources. It refers to an elastic load balancing management that provides the flexible model of on-demand services. The virtualization allows organizations to improve high levels of reliability, accessibility, and scalability by having a capability to execute applications on multiple resources simultaneously. In this paper we use a queuing model to consider a flexible load balancing and evaluate performance metrics such as mean queue length, throughput, mean waiting time, utilization, and mean traversal time. The model is aware of the arrival of concurrent applications with an Erlang distribution. Simulation results regarding performance metrics are investigated. Results point out that in Cloud systems both the fairness and load balancing are to be significantly considered.

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