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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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Features Deletion on Multiple Objects Recognition using Speeded-Up Robust Features, Scale Invariant Feature Transform and Randomized KD-Tree Samuel Alvin Hutama; Saptadi Nugroho; Darmawan Utomo
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.v14i2.3461

Abstract

This paper presents a multiple objects recognition method using speeded-up robust features (SURF) and scale invariant feature transform (SIFT) algorithm. Both algorithms are used for finding features by detecting keypoints and extracting descriptors on every object. The randomized KD-Tree algorithm is then used for matching those descriptors. The proposed method is deletion of certain features after an object has been registered and repetition of successful recognition. The method is expected to recognize all of the registered objects which are shown in an image. A series of tests is done in order to understand the characteristic of the recognizable object and the method capability to do the recognition. The test results show the accuracy of the proposed method is 97% using SURF and 88.7% using SIFT.
A novel deep learning architecture for drug named entity recognition T. Mathu; Kumudha Raimond
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 6: December 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i6.21667

Abstract

Drug named entity recognition (DNER) becomes the prerequisite of other medical relation extraction systems. Existing approaches to automatically recognize drug names includes rule-based, machine learning (ML) and deep learning (DL) techniques. DL techniques have been verified to be the state-of-the-art as it is independent of handcrafted features. The previous DL methods based on word embedding input representation uses the same vector representation for an entity irrespective of its context in different sentences and hence could not capture the context properly. Also, identification of the n-gram entity is a challenge. In this paper, a novel architecture is proposed that includes a sentence embedding layer that works on the entire sentence to efficiently capture the context of an entity. A hybrid model that comprises a stacked bidirectional long short-term memory (Bi-LSTM) with residual LSTM has been designed to overcome the limitations and to upgrade the performance of the model. We have contrasted the achievement of our proposed approach with other DNER models and the percentage of improvements of the proposed model over LSTM-conditional random field (CRF), LIU and WBI with respect to micro-average F1-score are 11.17, 8.8 and 17.64 respectively. The proposed model has also shown promising result in recognizing 2- and 3-gram entities.
Strategy to determine the foot plantar center of pressure of a person through deep learning neural networks Henry Hernández Martínez; Holman Montiel Ariza; Luz Andrea Gaviria Roa
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.v18i4.15200

Abstract

Some case studies treated by physiotherapists or orthopedists to measure the alignment of the lower extremities during a gait cycle are based on empirical methods of visual observation. This methodology does not guarantee total success, since it depends on the experience of the specialist, what can cause irreversible damage to patients, such as: hip displacement, wear and overload of the joints of a single lower limb. Although, this problem has been addressed in the investigation by means of devices implementation with sensors or methods of processing sequences of images and videos, this topic is still under investigation because the current methods depend on many external elements and data given by an expert in the area. Therefore, this paper proposes a partial solution to this problem by systematizing the experience of a specialist through a computational learning method.
Optimization of smart traffic lights to prevent traffic congestion using fuzzy logic Dian Hartanti; Rosida Nur Aziza; Puji Catur Siswipraptini
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.v17i1.10129

Abstract

One of the main causes of traffic congestion, especially at intersections, is because traffic lights have not been able to show the right time according to the existing traffic conditions. Time settings based on peak/off-peak traffic lights are not enough to handle unexpected situations. The fuzzy mamdani method makes decisions with several stages, the criteria used are the number of vehicles, the length of the queue and the width of the road to be able to optimize the time settings based on the real-time conditions required so that unwanted green signals (when there is no queue) can be avoided. The purpose of this research is to create a simulator to optimize traffic time management, so that the timers on each track have the intelligence to predict the right time, so that congestion at the intersection can be reduced by adding up to 15 seconds of green light from the previous time in the path of many vehicles.
A compact UWB monopole antenna with penta band notched characteristics Majed O. Al-Dwairi; Amjad Y. Hindi; Mohamed S. Soliman; Mohammad F. Aljafari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14542

Abstract

A modified rectangular monopole ultra-wideband (UWB) antenna with penta notched frequency bands is presented. An inverted U shaped and slanted U-shaped on the radiating patch are inserted to achieve WiMAX and ARN bands rejection respectively, two mirrored summation Σ-shaped and four mirrored 5-shaped slots are inserted on the partial ground to achieve WLAN and X-band bands rejection respectively, finally rectangular shaped slot with partially open on the feed is inserted to achieve ITU-8 band rejection. The proposed antenna which was simulated has a compact size 30×35×1.6 m3. It is operated with impedance bandwidth 2.8-10.6 GHz at |S11| < −10 dB, that supported UWB bandwidth with filtering the five narrowbands that avoid the possible interference with them. The simulated resonant frequency for notched filters received 3.55, 4.55, 5.53, 7.45, 8.16 GHZ, for WiMAX, ARN, WLAN, X-Band, ITU-8 respectively. The proposed antenna is suitable for wireless communication such as mobile communication and internet of everything (IoE). Throughout this paper, CST-EM software package was used for the design implementation. Surface current distributions for all notched filters were investigated and shown that it is concentrated around the feeding point and the inserted notched slots proving that there is no radiation to the space due to maximum stored electromagnetic energy around each investigated notch slot, proving that the slots play a role of a quarter wavelength transformer which generates for each notched band, maximum gain, and radiation pattern are also investigated.
Satellite Imagery and In-situ Data Overlay Approach for Fishery Zonation Khairul Munadi; Fardhi Adria
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 8, No 3: December 2010
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v8i3.623

Abstract

Remote sensing technology is useful to give a better understanding about the earth’s characteristics. SeaWiFS (sea-viewing wide field-of-view sensor) is one of remote sensors used to observe global ocean phenomena. Previous studies showed that the distribution of chlorophyll-a in the ocean indicates the presence of fish. However, only a few studies tried to directly relate the chlorophyll-a distribution obtained through interpretation of satellite imagery to in-situ data of fish distribution. This paper investigates the relation between chlorophyll-a distribution and fish-capturing points in Aceh Province sea waters using overlay image analysis. The results are useful to identify the potential fishing ground in Aceh. The profile of chlorophyll-a concentration was derived from SeaWIFS satellite imagery and fish-capturing points data was obtained from the fisherman communities of Banda Aceh, starting from June to November 2008. The results show that the chlorophyll-a profile derived from satellite imagery has a positive relationship to fish-capturing point data. The most potential fish-capturing zone in Aceh sea waters is identified at 5-8º north latitude (N) and 96-99º east longitude (E).
A hybrid algorithm for wave-front corrections applied to satellite-to-ground laser communication Mohammed Senan Al Gobi; Djamel Benatia; Mouadh Bali
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.v18i3.12960

Abstract

Laser communications hold accurate data rate for ground satellite links. The laser beam is transmitted through the atmosphere. The clear-air turbulence induces a number of phase distortions that damage wave-front. Adaptive optics (AO) treats wave front correction. The nature of AO systems is iterative; it can be integrated in metaheuristic algorithms such as genetic algorithm (GA). This paper presents improved version of algorithm for wave-front corrections. The improved algorithm is based on genetic algorithm (GA) and adaptive optics approach (OA). It is implemented in a computer simulation model called object-oriented matlab adaptive optics (OOMAO). The optimisation process involves best possible GA parameters as a function of population size, iteration count, and the actuators’ voltage intervals. Results show that the application of GA improves the performance of AO in wave-front corrections and the communication between satellite-to-ground laser links as well.
Controlling a knee CPM machine using PID and iterative learning control algorithm Dechrit Maneetham; Petrus Sutyasadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14876

Abstract

A conventional continuous passive motion (CPM) machine uses simple controller such as On/Off controller. Some better CPMs use PID controller. These kind of CPMs can not distinguish load different due to the different size of the patient leg. This may cause the CPM no longer follow the trajectory or the angle commands. Meanwhile, each patient may have different scenario of therapy from the others. When progress on the patient exists, the range of the flexion may be increased step by step. Therefore, the treatment can be different in term of the range of flexion from time to time. This paper proposes CPM with hybrid proportional integral derivative (PID) and iterative learning controller (ILC). The system has capability in learning the trajectory tracking. Therefore, the CPM will be able to follow any load or trajectory changes applied to it. The more accurate CPM machine can follow the trajectory command, the better its performance for the treatment. The experiment showed that the system was stable due to the PID controller. The tracking performance also improved with the ILC even there exist some disturbances.
Design of Digital to Analog Voice Data Packet Conversion from Ethernet Protocol using FPGA Barlian Henryranu Prasetio; Dahnial Syauqy
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.v15i2.3612

Abstract

This paper describes a system that is designed to be able to receive packet voice signal using the Ethernet protocol in local networks using FPGA which was programmed decode the data packets. The digital data packets are then converted back into analog data that will be used to control another system. The design was implemented as four components consisting of frame starter unit, address matching unit, buffer unit and DAC processing unit. The system was designed on Xilinx development board using ISE design suite and simulated on ISIM. The test results showed that the system response was less than 40 ms. The result also showed that our proposed design only occupies 11% of number of slices and it also requires 5% of total IOBs on Xilinx Spartan 3-E.
VRLA battery state of health estimation based on charging time Akhmad Zainuri; Unggul Wibawa; Mochammad Rusli; Rini Nur Hasanah; Rosihan Arby Harahap
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.v17i3.12241

Abstract

Battery state of health (SoH) is an important parameter of the battery’s ability to store and deliver electrical energy. Various methods have been so far developed to calculate the battery SoH, such as through the calculation of battery impedance or battery capacity using Kalman Filter, Fuzzy theory, Probabilistic Neural Network, adaptive hybrid battery model, and Double Unscented Kalman Filtering (D-UKF) algorithm. This paper proposes an approach to estimate the value of battery SoH based on the charging time measurement. The results of observation and measurements showed that a new and used batteries would indicate different charging times. Unhealthy battery tends to have faster charging and discharging time. The undertaken analysis has been focused on finding out the relationship between the battery SoH and the charging time range. To validate the results of this proposed approach, the use of battery capacity method has been considered as comparison. It can be concluded that there is a strong correlation between the two discussed SoH estimation methods, confirming that the proposed method is feasible as an alternative SoH estimation method to the widely known battery capacity method. The correlation between the charging-disharging times of healthy and unhealthy batteries is very prospective to develop a battery charger in the future with a prime advantage of not requiring any sensor for the data acquisition.

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