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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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Analysis of frequent itemset generation based on trie data structure in Apriori algorithm Ade Hodijah; Urip Teguh Setijohatmo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.19273

Abstract

Apriori is one technique of data mining association rules that aims to extract correlations between sets of items in the transaction database. The main problem with the Apriori algorithm is the process of scanning databases repeatedly to generate itemset candidates. This research examines the combination of pruning by using the trieapproach and multi-thread implementation in three algorithms to obtain frequent itemset. Trie is a data structure in the form of an ordered tree to store a set of strings where every node in the tree contains the same prefix. The use of a full combination trie (different from frequent pattern (FP) tree using links) allows the implementation of arrays and the hash calculation to achieve the addressing of itemset combination. In this research, the measure to get the address is called Hash-node calculation used to update support value. For these three alternatives, run time processing is analyzed based on the number of itemset combinations and transaction data at a certain minimum support value. The experimental results show that an algorithm thatexploits resource capabilities by applying multi-threadperforms almost seven times betterthanan algorithm implemented in single-thread in calculating hash-node. The fastest run time of the multi-thread approach is 43 minutes with 150-itemset combinations on 100,000 transaction data.
Design and implementation of a secured SDN system based on hybrid encrypted algorithms Samir Ghaly; Mahmood Zaki Abdullah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18721

Abstract

Software defined network suggests centralizing network knowledge in one network portion by separating the routing (control plane) mechanism from the transmission network packet operation (data plane). The control plane is composed of one, two or more controllers which are considered as software-defined networking (SDN) network brain where the real intelligence is incorporated. The process of separating the control unit from the data unit led to a problem related to poor security of data sent in the network, so solutions to these problems had to be found. In this paper, address this problem by implementing robust algorithms to encrypt information, based on advanced encryption standard (AES), Rivest–Shamir–Adleman (RSA), and hybrid encryption algorithms to guarantee data protection and authenticity. The results showed that the hybrid coding method is better in terms of security and improved time (faster than RSA alone) by applying several scenarios in the SDN network to a set of encrypted files.
Quantitative approach for reclassification of the spatial cluster of archipelagos in Maluku Province for the basis of forest development Patrich Papilaya; Endang Suhendang; I Nengah Surati Jaya; Teddy Rusolono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.17041

Abstract

In natural resource management, it is necessary to group regions based on the similarity of their spatial and non-spatial characteristics, to efficiency and effectiveness Therefore, this study describes the re-grouping of the twelve island clusters established by the provincial government of Maluku into more homogeneous classes. The re-grouping was carried out based on the biophysical conditions of the regions, therefore, it could be used as the basis for determining the forest management units. The results showed that the twelve designated island clusters could be simplified to eight more homogeneous island clusters with 86.4% accuracy and 82.2 validation. It also showed that there were thirteen significant changes in the grouping of clusters of the island, including the horticultural crop area (Bf) and horticultural crop production (E). Moreover, when the island cluster is reclassified into 5 classes, the grouping would be more accurate, with 94.9% accuracy and 92.4% validation. This study concludes that there are two dominant factors in the classification of the island cluster in Maluku province namely, biophysical and social.
Design and realization of motion detector system for house security Zainab G. Faisal; Maysam Sameer Hussein; Amany Mohammad Abood
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.v17i6.13142

Abstract

In this paper, the design and realization of motion detector system for house security based GSM network is presents. The development of microcontroller carried out intruder detection that supports tracking techniques to provide vital security with control and alert operation inside and outside the home. The pivot of security on the integration the motion detector and cameras into web applications has become more interested. The smart surveillance Pi camera obtain the input from the motion detector and controller which is send the video to the web server allowing the homeowner to access this video by use web applications. An intrusion alert send to the owner by mean of message via mobile and buzzers alarms located at suitable distance. This system is typify proficient video camera for remote sensing and tracking with live video for succeeding play again to offers efficient and easy implementation with omnipresent surveillance solution
Proposed different relay selection schemes for improving the performance of cooperative wireless networks Dheyaa Jasim Kadhim; Saba Qasim Jabbar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18327

Abstract

Relay selection is a new method currently used to develop and improve cooperative wireless networks. One of the main advantages of this new technology is that it can achieve cooperative diversity gain without installing multiple antennas in the transmitter or receiver. Relay selection algorithms can be used to select one node to become a relay node from a set of N candidate relays with optimization criteria as the outage probability or frame error rate. The selection process is preferable to operate in a distributed fashion and offers only reasonable costs in terms of manufacturing complexity and flexible handling over wireless cooperative networks. In this work, different relay selection schemes are proposed to enhance the cooperative wireless networks in terms of different approaches including: 1) Relay selection-based destination feedback scheme, 2) Relay selection based a ready-to-send/clear-to-send (RTS/CTS) messages scheme, 3) Relay selection-based identification messages (IDM) table scheme, and 4) Relay selection-based relay power consuming scheme. The experimental results via suggested case study show that the performance of overall cooperative network is enhanced in terms of increasing throughput, energy saving (efficiency maximization), blocking reduction and outage reduction (PER minimization).
An optimized power allocation algorithm for cognitive radio NOMA communication Madan H. T.; P. I. Basarkod
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.20366

Abstract

The primary objective of cognitive radio network is to effectively utilize the unused spectrum bands. In cognitive radio networks, spectrum sharing between primary and secondary users is accomplished using either underlay or interweave cognitive radio approach. Non orthogonal multiple access (NOMA) is the proven technology in the present wireless developments, which allows the coexistence of multiple users in the same orthogonal block. The new paradigm cognitive radio NOMA (CR-NOMA) is one of the potential solutions to fulfill the demands of future wireless communication. This paper emphasizes on practical implementation of NOMA in cognitive radio networks to enhance the spectral efficiency. The goal is to increase the throughput of the secondary users satisfying the quality of service (QOS) requirements of primary users. To achieve this, we have presented the optimized power allocation strategy for underlay downlink scenario to support the simultaneous transmission of primary and secondary users. Furthermore, we have proposed QOS based power allocation scheme for CR-NOMA interweave model to support the coexistence of multiple secondary networks. Also, the changes adopted in implementing superposition coding (SC) and successive interference cancellation (SIC) for CR-NOMA are highlighted. Finally, simulation results validate the mathematical expressions that are derived for power allocation coefficient and outage probability.
Cervical cancer classification using convolutional neural network-support vector machine Jane Eva Aurelia; Zuherman Rustam; Ilsya Wirasati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20406

Abstract

Cervical cancer is the second most common cancer in women worldwide, and occurs when there are presences of abnormal cells in the cervix, which continue to grow uncontrollably. In the early stages, cervical cancer indications are not perceptible; however, it is easily detected with different forms of machine learning methods, such as the convolutional neural network (CNN). This is a popular method with a wide range of applications and known for its high accuracy value. Moreover, there is a support vector machine (SVM) with several kernel functions that is commonly used in the classification of diseases, and also known for its high accuracy value. Therefore, the combination of CNN–SVM with several linear kernels functions as classifier for the categorization of cervical cancer.
Application of big data for distribution and consumption of power Olagunju Mukaila; Adeniyi Abidemi Emmanuel; Ogundokun Roseline Oluwaseun; Ojo Olufemi Samuel; Kolawole Paul Oluwatoba
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.16285

Abstract

The exponentially growing and tremendous collection of data stored in the power sector, combined with the need for data analysis, has produced an urgent need for powerful tools to extract hidden data as to effectively distribute the power for proper consumption for the household. This research work was embarked on to show the business value of big data analytics in Energy and utilities with a focus on how analytics can help solve problems of inefficiency and wastages in electricity generation, production and distribution and how raw energy datasets can be converted into insights that can be used by energy policy makers to make major business decisions. To explicitly show how raw data can be turned into insights, the study deploys the use of the Hadoop on Hortonworks’ open-source apache-Hive licensed data warehousing framework run on a windows operating system to turn raw datasets (in excel formats converted to .csv format) gotten from the prepaid meters of 196,000 consumers (households and businesses) in 11 business units of Ikeja Electricity Distribution Company (IKEDC, Nigeria) to analyze the distribution and consumption of power.
Lung cancer classification based on CT scan image by applying FCM segmentation and neural network technique Ahmad Zoebad Foeady; Siti Ria Riqmawatin; Dian Candra Rini Novitasari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18874

Abstract

The number of people with lung cancer has reached approximately 2.09 million people worldwide. Out of 9.06 million cases of death, 1.76 million people die due to lung cancer. Lung cancer can be automatically identified using a computer-aided diagnosis system (CAD) such as image processing. The steps taken for early detection are pre-processing feature extraction, and classification. Pre-processing is carried out in several stages, namely grayscale images, noise removal, and contrast limited adaptive histogram equalization. This image feature extracted using GLCM and classified using 2 method of neural network which is feed forward neural network (FFNN) dan feed backward neural network (FBNN). This research aims to obtain the best neural network model to classify lung cancer a. Based on training time and accuracy, the best method of FFNN is kernel extreme learning machine (KELM), with a training time of 12 seconds and an accuracy of 93.45%, while the best method of FBNN is Backpropagation with a training time of 18 minutes 04 seconds and an accuracy of 97.5%.
Comparative study of standalone classifier and ensemble classifier Tri Okta Priasni; Teddy Oswari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.19508

Abstract

Ensemble learning is one of machine learning method that can solve performance measurement problem. Standalone classifiers often show a poor performance result, thus why combining them with ensemble methods can improve their performance scores. Ensemble learning has several methods, in this study, three methods of ensemble learning are compared with standalone classifiers of support vector machine, Naïve Bayes, and decision tree. bagging, AdaBoost, and voting are the ensemble methods that are combined then compared to standalone classifiers. From 1670 dataset of twitter mentions about tourist’s attraction, ensemble methods did not show a specific improvement in accuracy and precision measurement since it generated the same result as decision tree as standalone classifier. Bagging method showed a significant development in recall, f-measure, and area under curve (AUC) measurement. For overall performance, decision tree as standalone classifier and decision tree with AdaBoost method have the highest score for accuracy and precision measurements, meanwhile support vector machine with bagging method has the highest score for recall, f-measure, and AUC.

Page 242 of 262 | Total Record : 2614

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