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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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Radial radio number of chess board graph and king’s graph Kulandaivel Maruthamuthu Paramasivam; Kins Yenoke; Baby Smitha Kanaka Muralidharan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.19493

Abstract

A radial radio labeling ℸ of a connected graph G = (V, E) with radius rad(G) is a mapping from V (G) to N ∪ {0} satisfying |ℸ(u) − ℸ(w)|+ d(u, w) ≥ 1 + rad(G), ∀ u, v ∈ V (G). The span of a radial radio labeling ℸ, denoted by rr(ℸ) is the greatest number in the range of ℸ. The minimum span taken over all radial radio labelings ℸ of G is called the radial radio nmber of G and it is denoted by rr(G). In this article, we have investigated the upper bounds for rr(G) of chess board graphs and king’s graph.
Implementation of K-means algorithm in data analysis Asyahri Hadi Nasyuha; Zulham Zulham; Ibnu Rusydi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.21986

Abstract

Some large companies have difficulty in providing products even though the products are still available in the warehouse. Based on these problems, a solution is needed in managing cosmetic products and can find the right strategy so that it can increase business in the field of sales and improve sales services by using algorithms in data mining that can overcome these problems, such as clustering techniques that use the K-means clustering algorithm as a way to measure proximity data between cosmetic products based on transactions that have occurred. The specialty of the analysis of the management of cosmetic products in this study is that it produces data on products that are not sold enough so that it can provide prevention so that the accumulation of these products does not occur. The use of K-means clustering also makes it easier to collect cosmetic sales transaction data, can solve problems in classifying cosmetic product sales transaction data and find out which products should be in cosmetics stock so as to increase sales profits
Characteristic's analysis of associative switching system Svetlana A Sadchikova; Mubarak Abdujapparova
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.17640

Abstract

This paper introduced new method and model of telecommunication switching system design which can be applied to wavelength-division multiplexing (WDM) optical networks, circuit-switching networks or virtual channel/path connections in an asynchronous transfer mode (ATM) networks. Modern data switching systems such as electronic private branch exchange (PBX), routers and switches include switching matrix which are constructed in the form of bipartite graphs. In such systems, the issues of requests’ processing are considered from the queuing theory point of view. Associative switching systems are fundamentally new structures, therefore it is necessary to develop adequate methods for their throughput determination. Article covered matters of throughput determination basics of an associative switching system and the obtained formulas used for state probability calculation of switching modules and system throughput.
Artificial intelligent techniques applied for detection COVID-19 based on chest medical imaging Nawres Aref Alwash; Hussain Kareem Khleaf
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.20881

Abstract

One of the ways to detect coronavirus disease of 2019 (COVID-19) is X-rays, computerized tomography (CT). This paper aims to detect COVID-19 from CT images without any user intervention. The proposed algorithm consists of 5 stages. These stages include; the first stage aims to collect data from hospitals and internet websites, the second stage is pre-processing stage to remove noise and convert it from red green blue (RGB) to grayscale and then improve image quality, the third is the segmentation stage which included threshold and region-growing segmentation methods. The fourth stage is used to extract important characteristics, and the last stage is classification CT images using feed forward back propagation network (FFBPN) and support vector machines (SVM) and compare the results between them and see if the person is infected or healthy. This study was implemented in MATLAB software. The results showed that the noise cancellation technology using anisotropic filtering gave the best results. Region-growing method was reliable to separate COVID-19 infected from healthy regions. The FFBPN has given the best results for detecting and classifying COVID-19. The results of the proposed methodology are rapid and accurate in detecting COVID-19. The output from classifier is displayed on the Rasbperry Pi that included weather if patient is infected or not and the severity of COVID-19 infection.
Investigation of temperature gradient between ambient air and soil to power up wireless sensor network device using a thermoelectric generator Khalil Azha Mohd Annuar; Ramizi Mohamed; Yushaizad Yusof
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.22463

Abstract

This paper proposes a study of an energy harvesting system for powering wireless sensor network (WSN) devices. The thermal energy harvesting system used is based on the thermal energy source between ambient air at the soil surface with five depth levels. Measurement was taken for 46 days in a garden area located in Melaka, Malaysia. A feasibility study of soil temperature measurement to obtain a temperature gradient can be used for harvesting by using thermoelectric generators (TEG) modules. Then, the efficiency of TEG with several different configurations based on temperature gradient data has been tested in the laboratory. The results revealed that the depth of soil 6 cm between sensors 1 and 3 will gave the best representation of level average temperature different around 1 ℃. Based on the temperature gradient data, the combination of three TEG SP1848 in a series connection with DC-DC step-up circuit DC1664 will produce an optimum voltage output of about 3 V. This output voltage is enough to operate low power IoT device derived from thermal energy.
Performance evaluation of ad-hoc on-demand distance vector protocol in highway environment in VANET with MATLAB Osama A. Qasim; Mohammed Sami Noori; Mohand Lokman Ahmad Al Dabag
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.20876

Abstract

Vehicular ad-hoc network (VANET), the development of this network in recent years has become one of the most important areas of research. The primary goal of using the VANET network is to reduce the number of deaths and enhance road safety. VANET network faces some problems when routing packets between vehicles, due to the high-speed movement of vehicles. Therefore, researchers have begun to develop routing protocols in the VANET network to overcome these problems when routing packets between vehicles. In this study, the effect of changing the number of vehicles on the performance of ad-hoc on-demand distance vector (AODV) protocol will be studied in the highway environment and in the case of vehicle movement at variable speeds between (40-120 km/h) and the simulation time is 200 sec. The ad-hoc ondemand distance vector protocol performance was evaluated by three performance measures (end-to-end delay, dropped packets, overhead and packet delivery ratio).
Leukocytes identification using augmentation and transfer learning based convolution neural network Mohammed Sabah Jarjees; Sinan Salim Mohammed Sheet; Bassam Tahseen Ahmed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.23163

Abstract

Most haematological diseases can be diagnosed using the morphological analysis of the microscopic blood image. The basic routine of the morphological analysis can be performed using the microscopic device which requires the skills and experiences of the haematologists. An inexperienced haematologist can lead to critical human errors. Therefore, this paper aims to propose an automated classification system used to classify different types of leukocytes based on the convolution neural network (CNN) algorithm. CNN has achieved robust performance in various fields especially in medical applications. A dataset of microscopic blood cells images of the conforming tags (basophil, eosinophil, erythroblast, lymphocyte, monocyte, neutrophil, and platelet) was used to train and test the proposed algorithm. The augmentation and deep transfer approaches were used to improve and enhance the performance of the CNN algorithm. The overall accuracy of the proposed classifier was 98% with Visual Geometry Group-19 (VGG-19). The obtained accuracy was higher than the state-of-art algorithms. To conclude that using the augmentation and deep transfer approaches with VGG-19 can obtain better classification results.
Comparative analysis of various machine learning algorithms for ransomware detection Ban Mohammed Khammas
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.18812

Abstract

Recently, the ransomware attack posed a serious threat that targets a wide range of organizations and individuals for financial gain. So, there is a real need to initiate more innovative methods that are capable of proactively detect and prevent this type of attack. Multiple approaches were innovated to detect attacks using different techniques. One of these techniques is machine learning techniques which provide reasonable results, in most attack detection systems. In the current article, different machine learning techniques are tested to analyze its ability in a detection ransomware attack. The top 1000 features extracted from raw byte with the use of gain ratio as a feature selection method. Three different classifiers (decision tree (J48), random forest, radial basis function (RBF) network) available in Waikato Environment for Knowledge Analysis (WEKA) based machine learning tool are evaluated to achieve significant detection accuracy of ransomware. The result shows that random forest gave the best detection accuracy almost around 98%.
Study of positioning estimation with user position affected by outlier: a case study of moving-horizon estimation filter Moath Awawdeh; Tarig Faisal Ibrahim; Anees Bashir; Flower M. Queen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.21657

Abstract

Many applications which require accurate location point positioning systems utilize global position system for pseudosciences. One of the main challenges faced by the system occurs due to the inherent errors that are a resultant of outliers. This considerably reduces the accuracy of the observations of global position system device. In this paper, we briefly introduce the problem of position estimation when the pseudo range measurements have an outlier. Moving horizon estimation algorithm has been adapted for the simulation result compared with the extended Kalman filter model, which is still imperfect for the case of outlier. The point at which a pseudo range becomes an outlier is considered at a fixed time instance. A simulation example is presented using an existing model with a moving horizon estimator and an extended Kalman filter. The moving horizon filter turns to be more robust than Kalman filtering with presence of outlier under certain choice of tunning parameter
Improved maximum distance on-demand routing algorithm routing protocol for vehicular ad hoc network network in an urban environment Dania Mohammed; Muhamad Bin Mansor; Goh Chin Hock
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.19283

Abstract

Vehicular ad hoc network (VANET) is a modern technology that has received great attention in the modern era due to daily road accidents. In VANET network it is difficult to design effective routing protocols due to the speed of movement of nodes and the rapid change in network architecture, and the purpose of routing protocols in the VANET network is to route data between vehicles (V2V), and between vehicles to infrastructure (V2I). Recently researchers have been interested in designing effective routing protocols for the VANET network because not all existing protocols are suitable for all traffic scenarios. Therefore, the focus of this paper will be on the maximum distance on-demand routing algorithm (MDORA) protocol and work on improving the protocol algorithm so that it is compatible with the urban environment. After that, the improved performance of the MDORA-without direction (MDORA-WD) protocol will be compared with the ad-hoc on-demand distance vector (AODV) protocol in terms of communication overhead, packet delivery ratio (PDR) and end to end (E2E) delay. The protocols will be simulated by MATLAB.

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