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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 64 Documents
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Search results for , issue "Vol 17, No 1: February 2019" : 64 Documents clear
The influence of sampling frequency on tone recognition of musical instruments Linggo Sumarno; Kuntoro Adi
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.v17i1.11608

Abstract

Sampling frequency of musical instruments tone recognition generally follows the Shannon sampling theorem. This paper explores the influence of sampling frequency that does not follow the Shannon sampling theorem, in the tone recognition system using segment averaging for feature extraction and template matching for classification. The musical instruments we used were bellyra, flute, and pianica, where each of them represented a musical instrument that had one, a few, and many significant local peaks in the Discrete Fourier Transform (DFT) domain. Based on our experiments, until the sampling frequency is as low as 312 Hz, recognition rate performance of bellyra and flute tones were influenced a little since it reduced in the range of 5%. However, recognition rate performance of pianica tones was not influenced by that sampling frequency. Therefore, if that kind of reduced recognition rate could be accepted, the sampling frequency as low as 312 Hz could be used for tone recognition of musical instruments.
2.45 GHz rectenna with high gain for RF energy harvesting Maizatul Alice Meor Said; Zahriladha Zakaria; Mohd Nor Husain; Mohamad Harris Misran; Faza Syahirah Mohd Noor
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.v17i1.11592

Abstract

This paper presents a high gain rectenna at 2.45 GHz. Two layers low cost FR4 substrate has been used with air-gap technology for this fabricated rectenna. The proposed designs contain antenna and  open stub rectifying circuits with feedline. With the dimension of 100 x 100 x 5 mm3, this rectenna can perform high gain. The technique of air gap approach has been used for this proposed rectenna design so as to increase the antenna gain. Second and third harmonics has been eliminated by the introducing of triangular slot and ground plane to the developed design. The proposed rectenna successfully achieved the output voltages reaches 0.46 V when the input power is 0 dBm respectively when  the input power range is between -25 to 30 dBm. It is also can reach up to 6V when the maximum input power is applied. High gain, simple design, low profile and easy integration are the main advantages of this design of the rectenna when compared to past researchers.
Hybrid model for forecasting space-time data with calendar variation effects Suhartono Suhartono; I Made Gde Meranggi Dana; Santi Puteri Rahayu
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.v17i1.10096

Abstract

The aim of this research is to propose a new hybrid model, i.e. Generalized Space-Time Autoregressive with Exogenous Variable and Neural Network (GSTARX-NN) model for forecasting space-time data with calendar variation effect. GSTARX model represented as a linear component with exogenous variable particularly an effect of calendar variation, such as Eid Fitr. Whereas, NN was a model for handling a nonlinear component. There were two studies conducted in this research, i.e. simulation studies and applications on monthly inflow and outflow currency data in Bank Indonesia at East Java region. The simulation study showed that the hybrid GSTARX-NN model could capture well the data patterns, i.e. trend, seasonal, calendar variation, and both linear and nonlinear noise series. Moreover, based on RMSE at testing dataset, the results of application study on inflow and outflow data showed that the hybrid GSTARX-NN models tend to give more accurate forecast than VARX and GSTARX models. These results in line with the third M3 forecasting competition conclusion that stated hybrid or combining models, in average, yielded better forecast than individual models.
The use of mobile-assisted virtual reality in fear of darkness therapy Erick Paulus; Mira Suryani; Puspita Adhi Kusuma Wijayanti; Firdaus Perdana Yusuf; Aulia Iskandarsyah
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.v17i1.11614

Abstract

Fear of darkness is a common psychological problem that may extent to a specific phobia if it is not treated well. Several intervention techniques related to fear and phobia using actual exposure therapy have been studied for decades, however, there were some constraints emerged when the therapist provides a real environment to overcome the patient's reaction to his/her specific fear. Virtual reality (VR) technology is an innovative tool providing a more immersive, secure, personal, and controlled virtual environment. Therefore, we developed a novel framework for treating the fear of darkness named Mobile-assisted Virtual Reality (MAVR). The purpose of this study was to evaluate the use of MAVR to treat fear of darkness based on usability, time consumption and its ability to decrease fear. We used the GOMS model as an interaction guidance between human and computer which aimed to facilitate the process of re-learning in mindset change and individual’s behavioral toward situation of darkness and night. Therefore, a comprehensive evaluation was conducted to measure the efficacy of the MAVR. We developed the usability assessment checklist to assess the feasibility and acceptability of the MAVR, and fear of darkness thermometer to measure the degree of fear. The Wilcoxon Signed Rank Test showed that the fear of darkness was significantly decreased after participants received the MAVR therapy (z=-3.550, p-value<0.001). We found that the MAVR was very useful, easy to be used and acceptable for participants. In conclusion, this study highlights the efficacy of Mobile-assisted Virtual Reality in treating specific fear, and it seems that Virtual Reality technology has a promising benefit to be implemented for other fear or specific phobia and also used in other psychological treatment.
A verification of periodogram technique for harmonic source diagnostic analytic by using logistic regression M. Manap; M. H. Jopri; A. R. Abdullah; R. Karim; M. R. Yusoff; AH Azahar
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.v17i1.10390

Abstract

A harmonic source diagnostic analytic is vital to identify the root causes and type of harmonic source in power system. This paper introduces a verification of periodogram technique to diagnose harmonic sources by using logistic regression classifier. A periodogram gives a correct and accurate classification of harmonic signals. Signature recognition pattern is used to distinguish the harmonic sources accurately by obtaining the distribution of harmonic and interharmonic components and the harmonic contribution changes. This is achieved by using the significant signature recognition of harmonic producing load obtained from the harmonic contribution changes. To verify the performance of the propose method, a logistic regression classifier will analyse the result and give the accuracy and positive rate percentage of the propose method. The adequacy of the proposed methodology is tested and verified on distribution system for several rectifier and inverter-based loads.
Classification of neovascularization using convolutional neural network model Wahyudi Setiawan; Moh. Imam Utoyo; Riries Rulaningtyas
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.v17i1.11604

Abstract

Neovascularization is a new vessel in the retina beside the artery-venous. Neovascularization can appear on the optic disk and the entire surface of the retina. The retina categorized in Proliferative Diabetic Retinopathy (PDR) if it has neovascularization. PDR is a severe Diabetic Retinopathy (DR). An image classification system between normal and neovascularization is here presented. The classification using Convolutional Neural Network (CNN) model and classification method such as Support Vector Machine, k-Nearest Neighbor, Naïve Bayes classifier, Discriminant Analysis, and Decision Tree. By far, there are no data patches of neovascularization for the process of classification. Data consist of normal, New Vessel on the Disc (NVD) and New Vessel Elsewhere (NVE). Images are taken from 2 databases, MESSIDOR and Retina Image Bank. The patches are made from a manual crop on the image that has been marked by experts as neovascularization. The dataset consists of 100 data patches. The test results using three scenarios obtained a classification accuracy of 90%-100% with linear loss cross validation 0%-26.67%. The test performs using a single Graphical Processing Unit (GPU).
Transistor mismatch effect on common-mode gain of cross-coupled amplifie Zainul Abidin; Eka Maulana; Ramadhani Kurniawan Subroto; Wijono Wijono
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.v17i1.11587

Abstract

In this paper, the analytical approach of MOS transistor mismatch effect on common-mode gain of cross-coupled amplifier is presented. Transconductance (MOS transistor parameter) mismatch effect on common-mode gain of cross-coupled amplifier was analyzed. This study was started with mathematical derivation for representing the mismatch effect of transconductance between 2 differential pairs of crosscoupled amplifier due to common-mode voltage. The derivation result was simulated based on Monte Carlo simulation with random transconductance mismatch rate from 0.05% until 1%. The common-mode gain increases 36.9 dB and average common-mode gain is -81.1 dB. The transconductance mismatch rate increases followed by increase in common-mode gain. The results can be used by circuit designers to design analog circuits, especially operational amplifier used for biosignals processing to minimize the common-mode gain of their circuits. This research presents aid to circuit designers to improve their circuits performance.
Ontology design based on data family planning field officer using OWL and RDF Rolly Maulana Awangga; Setiawan Assegaff; Syafrial Fachri Pane; Muhammad Firman Kahfi
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.v17i1.9237

Abstract

Population density in Indonesia is ranked fourth in the world. The impact of a large population will affect the level of welfare of the community to decrease, and the number of unemployment is increasing so that the state makes Family Planning Program (PLKB) to control the rate of population growth. Problems in the PLKB program are on knowledge management and mapping from data contraception, counseling and planning so that this research using Ontology method will aim to do mapping with knowledge management and Ontology design shows represented data to relate and describes the resources contained in family planning data. This research approach the representation of ontology that is validated through model transformation from family planning data to ontology design using OWL and RDF which are useful for data processing and representing data to be utilized by field officers in educating the public and eradicating negative issues about family planning programs
Big 5 ASEAN capital markets forecasting using WEMA method Seng Hansun; Marcel Bonar Kristanda; P. M. Winarno
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.v17i1.11625

Abstract

ASEAN through ASEAN Economics Community (AEC) 2020 treaty has proposed financial integration via capital markets integration in order to aim comprehensive ASEAN economic integration. Therefore, the need to have a proper prediction of ASEAN capital market becomes a major issue. In this study, we took big 5 ASEAN capital markets, i.e. Straits Times Index (STI), Kuala Lumpur Stock Exchange (KLSE), Stock Exchange of Thailand (SET), Jakarta Stock Exchange (JKSE), and Philippine Stock Exchange (PSE) to be forecasted using WEMA method. Weighted Exponential Moving Average (WEMA) is a new hybrid moving average method which combines the weighting factor calculation in Weighted Moving Average (WMA) with the procedure of Exponential Moving Average (EMA). WEMA has successfully been implemented and used to forecaste discrete time series data, but never being used to forecast ASEAN capital markets. In this study, we took further action by implementing the WEMA method with brute force approach for scaling factor tuning on big 5 ASEAN capital markets. From the experimental results, we found that WEMA has successfully forecasted all those exchanges. By looking at the forecast error measurement, it gives the best performance on PSE and worst performance on SET dataset among all datasets being considered in this study.
A colour-based building recognition using support vector machine Mas Rina Mustaffa; Loh Weng Yee; Lili Nurliyana Abdullah; Nurul Amelina Nasharuddin
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.v17i1.11609

Abstract

Many applications apply the concept of image recognition to help human in recognising objects simply by just using digital images. A content-based building recognition system could solve the problem of using just text as search input. In this paper, a building recognition system using colour histogram is proposed for recognising buildings in Ipoh city, Perak, Malaysia. The colour features of each building image will be extracted. A feature vector combining the mean, standard deviation, variance, skewness and kurtosis of gray level will be formed to represent each building image. These feature values are later used to train the system using supervised learning algorithm, which is Support Vector Machine (SVM). Lastly, the accuracy of the recognition system is evaluated using 10-fold cross validation. The evaluation results show that the building recognition system is well trained and able to effectively recognise the building images with low misclassification rate.

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