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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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Voronoi diagram with fuzzy number and sensor data in an indoor navigation for emergency situation Nanna Suryana; Fandy Setyo Utomo; Mohd Fairuz Iskandar Othman; Mohd Nazrin Muhammad
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.v18i4.14905

Abstract

Finding shortest and safest path during emergency situation is critical. In this paper, an indoor navigation during an emergency time is investigated using the combination of Voronoi Diagram and fuzzy number. The challenge in indoor navigation is to analyses the network when the shortest path algorithm does not work as always expected. There are some existing methods to generate the network model. First, this paper will discuss the feasibility and accuracy of each method when it is implemented on building environment. Next, this paper will discuss selected algorithms that determine the selection of the best route during an emergency situation. The algorithm has to make sure that the selected route is the shortest and the safest route to the destination. During a disaster, there are many uncertainties to deal with in determining the shortest and safest route. Fuzzy logic can be hardly called for to deal with these uncertainties. Based on sensor data, this paper will also discuss how to solve shortest path problem using a fuzzy number.
A Review of immigration obstacles to PON-FTTH and its evolution around the world Mustafa H. Ali; Hazim M. ALkargole; Tariq A. Hassan
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.v19i2.16444

Abstract

The require a bandwidth of every person will be increased from 16 Mbit/s to 50 up to 100M bit/s in the next 5 years in most of the growing counties. To solve this problem, FTTH may be the appropriate solution in a wide range. We experimentally investigate the deploy of PON-FTTH based on different kinds of passive optical network technology (E-PON, G-PON and VCSEL) and study the Obstacles of PON-FTTH Immigration after comparing it with older service (XDSL). Then analysis the reason on why these technologies chose by some country not others and why the technological need in Europe different with need in Africa and America. We discussed the solutions in telecommunications networks and or the economic aspect of projects all over the world, we found that GPON is more appropriable for accomplishment PON-FTTH than other networks. Thus GPON has been chosen for Europe, America and middle east. Choosing GPON techniques is decided by many factors include the infrastructure that was made before, the people demand for service and how much service they need because the need in Europe different with need in Africa and American and so on. Finally, we will suggest the appropriate solution in the energy savings, cost effective, higher security, and side of service transparency over other access networks for the future demand.
Test Generation Algorithm Based on SVM with compressing Sample Space Methods Ting Long; Jiang Shiqi; Hang Luo
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.v13i2.1473

Abstract

Test generation algorithm based on the SVM (support vector machine) generates test signals derived from the sample space of the output responses of the analog DUT. When the responses of the normal circuits are similar to those of the faulty circuits (i.e., the latter have only small parametric faults), the sample space is mixed and traditional algorithms have difficulty distinguishing the two groups. However, the SVM provides an effective result. The sample space contains redundant data, because successive impulse-response samples may get quite close. The redundancy will waste the needless computational load. So we propose three difference methods to compress the sample space. The compressing sample space methods are Equidistant compressional method, k-nearest neighbors method and maximal difference method. Numerical experiments prove that maximal difference method can ensure the precision of the test generation.
Field Distribution of Environment and Vibration Chamber Wang Tong; Guan Yin; Xu He Xu He; Liang Qiong-chong
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 3: September 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i3.839

Abstract

Environment and vibration test system can test equipment such as radars in full load condition. Environment and vibration chamber is an opening rectangular cavity. In order to study the field distribution of environment and vibration chamber, the open rectangular cavity field distribution and parabolic antenna are analyzed by using the Dyadic Green’s functions. According to the Dyadic Green’s functions, the field distribution of environment and vibration chamber is concluded by MATLAB. The simulation result of FEKO proves that the method by using Dyadic Green’s functions is available. The innovation of this article is using the Dyadic Green’s functions to analyzed open cavity field and parabolic antenna.
ISSUES AND PROBLEMS IN BRAIN MAGNETIC RESONANCE IMAGING: AN OVERVIEW Novanto Yudistira; Daut Daman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 6, No 1: April 2008
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v6i1.551

Abstract

There are many issues and problems in the brain magnetic resonance imaging (MRI) area that haven’t solved or reached satisfying result yet. This paper presents an overview of the various issues and problems of the segmentation, correction, optimization, description and their application in MRI. The overview is started by describing the segmentation properties that are the most important and challenging in MRI brain manipulation. Then correction for reconstructing the brain MRI cortex, classification is utilized to classify the segmented brain image, and also review the uses of description is the great prospecting issue while some neurologist need the information resulted from brain imaging process including their potential problems from application applied by each technique. In each case, it is provided some general background information.
Classification of Non-Functional Requirements Using Semantic-FSKNN Based ISO/IEC 9126 Denni Aldi Ramadhani; Siti Rochimah; Umi Laili Yuhana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 4: December 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i4.2300

Abstract

Non-functional requirements is one of the important factors that play a role in the success of software development that is often overlooked by developers, so it cause adverse effects. In order to obtain the non-functional requirements, it requires an identification automation system of non-functional requirements. This research proposes an automation system of identification of non-functional requirements from the requirement sentence-based classification algorithms of FSKNN with the addition of semantic factors such as the term development by hipernim and measurement of semantic relatedness between the term and every category of quality aspects based ISO / IEC 9126. In the test, the dataset is 1342 sentences from six different datasets. The result of this research is that the Semantic-FSKNN method can reduce the value of hamming loss or error rate by 21.9%, and also raise the value of accuracy by 43.7%, and also the precision value amounted to 73.9% compared to FSKNN method without the addition of semantic factors in it.
Automatic Summarization in Chinese Product Reviews Li zhen Liu; Wan di Du; Han shi Wang; Wei Song
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.5099

Abstract

With the increasing number of online comments, it was hard for buyers to find useful information in a short time so it made sense to do research on automatic summarization which fundamental work was focused on product reviews mining. Previous studies mainly focused on explicit features extraction whereas often ignored implicit features which hadn't been stated clearly but containing necessary information for analyzing comments. So how to quickly and accurately mine features from web reviews had important significance for summarization technology. In this paper, explicit features and “feature-opinion” pairs in the explicit sentences were extracted by Conditional Random Field and implicit product features were recognized by a bipartite graph model based on random walk algorithm. Then incorporating features and corresponding opinions into a structured text and the abstract was generated based on the extraction results. The experiment results demonstrated the proposed methods outpreferred baselines.
Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling Budi Arif Dermawan; Yeni Herdiyeni; Lilik Budi Prasetyo; Agung Siswoyo
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.v16i2.6894

Abstract

Acacia nilotica planted in Baluran National Park aims to prevent the spread of fire from savanna to teak forest became developed into invasive and led to a decrease in the quality and quantity of savannas. Therefore, it is required to predict the spread of A. nilotica to minimize the impacts of invasion on savanna area. The study aims to identify environmental factors which affect spread of A. nilotica. Furthermore, the spread of A. nilotica is predicted using Maximum Entropy. Maximum Entropy is efficient model since it uses presence-only data while the most of other models use presence and absence data. The experimental results reveal six environmental factors, including elevation, slope, NDMI, NDVI, distance from the river, and temperature were identified affecting the spread of A. nilotica. The most dominant environmental factors were elevation and temperature with 40% and 39.6% contributions. Maximum Entropy performed well in predicting the spread of A. nilotica, it was indicated by AUC value of 0.938.
Text to Emotion Extraction Using Supervised Machine Learning Techniques Muhammad Anwarul Azim; Mahmudul Hasan Bhuiyan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.8387

Abstract

Proliferation of internet and social media has greatly increased the popularity of text communication. People convey their sentiment and emotion through text which promotes lively communication. Consequently, a tremendous amount of emotional text is generated on different social media and blogs in every moment. This has raised the necessity of automated tool for emotion mining from text. There are various rule based approaches of emotion extraction form text based on emotion intensity lexicon. However, creating emotion intensity lexicon is a time consuming and tedious process. Moreover, there is no hard and fast rule for assigning emotion intensity to words. To solve these difficulties, we propose a machine learning based approach of emotion extraction from text which relies on annotated example rather emotion intensity lexicon. We investigated Multinomial Naïve Bayesian (MNB) Classifier, Artificial Neural Network (ANN) and Support Vector Machine (SVM) for mining emotion from text. In our setup, SVM outperformed other classifiers with promising accuracy.
Facial image retrieval on semantic features using adaptive mean genetic algorithm Marwan Ali Shnan; Taha H. Rassem; Nor Saradatul Akmar Zulkifli
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.v17i2.3774

Abstract

The emergence of larger databases has made image retrieval techniques an essential component and has led to the development of more efficient image retrieval systems. Retrieval can either be content or text-based. In this paper, the focus is on the content-based image retrieval from the FGNET database. Input query images are subjected to several processing techniques in the database before computing the squared Euclidean distance (SED) between them. The images with the shortest Euclidean distance are considered as a match and are retrieved. The processing techniques involve the application of the median modified Weiner filter (MMWF), extraction of the low-level features using histogram-oriented gradients (HOG), discrete wavelet transform (DWT), GIST, and Local tetra pattern (LTrP). Finally, the features are selected using Adaptive Mean Genetic Algorithm (AMGA). In this study, the average PSNR value obtained after applying the Wiener filter was 45.29. The performance of the AMGA was evaluated based on its precision, F-measure, and recall, and the obtained average values were respectively 0.75, 0.692, and 0.66. The performance matrix of the AMGA was compared to those of particle swarm optimization algorithm (PSO) and genetic algorithm (GA) and found to perform better; thus, proving its efficiency.

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