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31,456 Article Results

Competency improvement through internship: An evaluation of corporate social responsibility program in vocational school

10.11591/ijere.v9i3.20571
Mgs. Ahmad Ramadhani , Ety Rahayu
The high unemployment rate in Indonesia derived from vocational school graduates could be alleviated through internship as a part of Corporate Social Responsibility program that deployed by company together with school to equip its students or graduates with set of competences, therefore they will be competent and able to compete in job market, especially in the era of disruptive technologies. This applied research of evaluation using qualitative approach aimed to evaluate the input and process of the corporate social responsibility program in vocational internship conducted by an oil and gas manufacturing company in Indonesia. The results of this revealed some inputs that were the source of program success and processes that determined the quality of the program. Aspects of input generally met the ideal criteria such as competent program staff, participant characteristic reflecting program objectives, flexible and synchronized curriculum, adequate facility, and available procedure. Aspects of the process complied with regulations and procedures as well. Both aspects resulted the achievement of outcome that exceeded expectation such as competence improvement, cost saving, awards and provide information to be replicated by other institutions.
Volume: 9
Issue: 3
Page: 625-634
Publish at: 2020-08-01

ELM and K-nn machine learning in classification of breath sounds signals

10.11591/ijece.v10i4.pp3528-3536
Z. Neili , M. Fezari , A. Redjati
The acquisition of Breath sounds (BS) signals from a human respiratory system with an electronic stethoscope, provide and offer prominent information which helps the doctors to diagnosis and classification of pulmonary diseases. Unfortunately, this BS signals with other biological signals have a non-stationary nature according to the variation of the lung volume, and this nature makes it difficult to analyze and classify between several diseases. In this study, we were focused on comparing the ability of the extreme learning machine (ELM) and k-nearest neighbour (K-nn) machine learning algorithms in the classification of adventitious and normal breath sounds. To do so, the empirical mode decomposition (EMD) was used in this work to analyze BS, this method is rarely used in the breath sounds analysis. After the EMD decomposition of the signals into Intrinsic Mode Functions (IMFs), the Hjorth descriptors (Activity) and Permutation Entropy (PE) features were extracted from each IMFs and combined for classification stage. The study has found that the combination of features (activity and PE) yielded an accuracy of 90.71%, 95% using ELM and K-nn respectively in binary classification (normal and abnormal breath sounds), and 83.57%, 86.42% in multiclass classification (five classes).
Volume: 10
Issue: 4
Page: 3528-3536
Publish at: 2020-08-01

Approximation of regression-based fault minimization for network traffic

10.12928/telkomnika.v18i4.13192
Chanintorn; Assumption University. Jittawiriyanukoon
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in Deep Learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
Volume: 18
Issue: 4
Page: 1802-1808
Publish at: 2020-08-01

Cloud computing survey on services, enhancements and challenges in the era of machine learning and data science

10.11591/ijict.v9i2.pp117-139
Wajid Hassan , Te-Shun Chou , Omar Tamer , John Pickard , Patrick Appiah-Kubi , Leslie Pagliari
Cloud computing has sweeping impact on the human productivity. Today it’s used for Computing, Storage, Predictions and Intelligent Decision Making, among others. Intelligent Decision Making using Machine Learning has pushed for the Cloud Services to be even more fast, robust and accurate. Security remains one of the major concerns which affect the cloud computing growth however there exist various research challenges in cloud computing adoption such as lack of well managed service level agreement (SLA), frequent disconnections, resource scarcity, interoperability, privacy, and reliability. Tremendous amount of work still needs to be done to explore the security challenges arising due to widespread usage of cloud deployment using Containers. We also discuss Impact of Cloud Computing and Cloud Standards. Hence in this research paper, a detailed survey of cloud computing, concepts, architectural principles, key services, and implementation, design and deployment challenges of cloud computing are discussed in detail and important future research directions in the era of Machine Learning and Data Science have been identified.
Volume: 9
Issue: 2
Page: 117-139
Publish at: 2020-08-01

Incident and reflected two waves correlation with cancellous bone structure

10.12928/telkomnika.v18i4.14828
Muhamad Amin Abd; Universiti Teknologi Malaysia Wahab , Rubita; Universiti Teknologi Malaysia Sudirman , Mohd Azhar Abdul; Universiti Teknologi Malaysia Razak , Fauzan Khairi Che; Universiti Teknologi Malaysia Harun , Nurul Ashikin Abdul; Universiti Teknologi Malaysia Kadir , Nasrul Humaimi; Universiti Teknologi Malaysia Mahmood
The correlation in bone microstructure for ultrasound pulse echo technique is still less accurate compared to through transmission technique. Previous works demonstrated, reflected two modes wave has significant association with bone porosity. The paper aims is to conduct simulation using pulse echo technique to examine the relationship between fast and slow waves with porosity of 2-dimensional cancellous bone models by comparing the result to through transmission technique. The “incident” and “reflected” waves were separated using bandlimited deconvolution method by estimating time threshold of fast and slow waves' transfer function. The parameters of the waves were computed, plotted versus porosity for six different thicknesses and the correlation coefficients between them were compared. The incident and reflected fast wave attenuations show marginally significant correlation with porosity for both bone models orientations. Wave propagation for parallel orientation dominated by incident and reflected fast wave, meanwhile, perpendicular orientation dominated by incident slow wave. The thickness factor affected wave amplitude but less affected the attenuation. Because of propagation loss, reflected wave shows lower correlation to porosity compared to incident wave. Hence, analyzing fast and slow waves might improve the measurement accuracy of pulse echo technique compared to using single mode wave to estimate bone quality.
Volume: 18
Issue: 4
Page: 1968-1975
Publish at: 2020-08-01

Fair and trustworthy: Lock-free enhanced tendermint blockchain algorithm

10.12928/telkomnika.v18i4.15701
Basem; Jazan University Assiri , Wazir Zada; Jazan University Khan
Blockchain Technology is exclusively used to make online transactions secure by maintaining a distributed and decentralized ledger of records across multiple computers. Tendermint is a general-purpose blockchain engine that is composed of two parts; Tendermint Core and the blockchain application interface. The application interface makes Tendermint suitable for a wide range of applications. In this paper, we analyze and improve Practical Byzantine Fault Tolerant (PBFT), a consensus-based Tendermint blockchain algorithm. In order to avoid negative issues of locks, we first propose a lock-free algorithm for blockchain in which the proposal and voting phases are concurrent whereas the commit phase is sequential. This consideration in the algorithm allows parallelism. Secondly, a new methodology is used to decide the size of the voter set which is a subset of blockchain nodes, further investigating the block sensitivity and trustworthiness of nodes. Thirdly, to fairly select the voter set nodes, we employ the random walk algorithm. Fourthly, we imply the wait-freedom property by using a timeout due to which all blocks are eventually committed or aborted. In addition, we have discussed voting conflicts and consensuses issues that are used as a correctness property, and provide some supportive techniques.
Volume: 18
Issue: 4
Page: 2224-2234
Publish at: 2020-08-01

Digital control strategy for SPWM MPPT of PV system with three-phase NPC three-level converter

10.11591/ijeecs.v19.i2.pp572-585
Mahmoud Aref , Ismaiel Ahmed , Vladislav Oboskalov
This paper is aimed at investigating MPPT of PV system controlled by SPWM which is generated by comparing sinusoidal wave with variable frequency sawtooth wave. Perturb and observe (P&O) method is used for MPPT control of PV system. NPC three-phase three-level converter with LCL filter is designed to produce output voltage with minimum total harmonic distortion (THD) and high efficiency. The simple and fast method to get MPP of PV system with variable irradiation is digital control where the maximum power point is obtained from look-up table for the values of optimum voltage that achieve the maximum power for each irradiance value is used for digital control signal in microcontroller. The output voltage harmonic of multi-level three-phase inverter is controlled using SPWM control. THD of output voltage of multi-level three-phase inverter is 22% of stand-alone and grid-connected PV system. Small rate LCL filter is used to limit voltage harmonics within medium and low voltage limits (5%). THD output voltage of LCL filter is 4.9% and 3.51% of stand-alone and grid-connected PV system respectively. 
Volume: 19
Issue: 2
Page: 572-585
Publish at: 2020-08-01

Voltage sag compensation using direct converter based DVR by modulating the error signal

10.11591/ijeecs.v19.i2.pp608-616
S. Abdul Rahman , Estifanos Dagnew
The aim of this paper is to present a modulation technique to achieve highest voltage sag compensation using direct converter based dynamic voltage restorer (DVR). The DVR topology proposed in this paper, has a direct converter and a series transformer. The direct converter is fabricated using only two bi-directional switches. The DVR is designed to compensate the sag in a phase by taking power from the same phase. The direct converter is connected between the series transformer and the line in which sag compensation is to be achieved. Conventionally, the PWM pulses for the direct converters are produced by comparing the error signal with the carrier signal. The error signal is obtained by comparing the amplitude of voltage in the line with the amplitude of the reference voltage. If the amplitude of the carrier signal is kept constant and the actual amplitude of error signal is used for PWM generation, it is possible to achieve only 22% of voltage sag compensation. But if the error signal amplitude is modulated according to the amplitude of existing voltage sag in the line, 52% of the voltage sag can be compensated with the THD less than 5%. Simulation results are presented for validating the analysis. 
Volume: 19
Issue: 2
Page: 608-616
Publish at: 2020-08-01

Medium term load demand forecast of Kano zone using neural network algorithms

10.12928/telkomnika.v18i4.14032
Huzaimu Lawal; Bayero University Kano Imam , Muhammad Sani; Kano University of Science and Technology Gaya , G. S. M.; Bayero University Kano Galadanci
Electricity load forecasting refers to projection of future load requirements of an area or region or country through appropriate use of historical load data. One of several challenges faced by the Nigerian power distribution sectors is the overloaded power distribution network which leads to poor voltage distribution and frequent power outages. Accurate load demand forecasting is a key in addressing this challenge. This paper presents a comparison of generalized regression neural network (GRNN), feed-forward neural network (FFNN) and radial basis function neural network for medium term load demand estimation. Experimental data from Kano electricity distribution company (KEDCO) were used in validating the models. The simulation results indicated that the neural network models yielded promising results having achieved a mean absolute percentage error (MAPE) of less than 10% in all the considered scenarios. The generalization capability of FFNN is slightly better than that of RBFNN and GRNN model. The models could serve as a valuable and promising tool for the forecasting of the load demand.
Volume: 18
Issue: 4
Page: 2112-2117
Publish at: 2020-08-01

Optimal cost allocation algorithm of transmission losses to bilateral contracts

10.12928/telkomnika.v18i4.14226
Conny K.; Politeknik Negeri Bandung Wachjoe , Hermagasantos; Politeknik Negeri Bandung Zein , Fitria; Politeknik Negeri Bandung Yulistiani
One of the trends in electricity reform is the involvement of bilateral contracts that will participate in electricity business development. Bilateral agreements require fair transmission loss costs compared with the integrated power system. This paper proposes a new algorithm in determining the optimal allocation of transmission loss costs for bilateral contracts based on the direct method in economic load dispatch. The calculation for an optimal power flow applies fast decoupled methods. At the same time, the determination of a fair allocation of transmission losses uses the decomposition method. The simulation results of the optimal allocation of power flow provide comparable results with previous studies. This method produces a fair allocation of optimal transmission loss costs for both integrated and bilateral parties. The proportion allocation of the transmission lines loss incurred by the integrated system and bilateral contracts reflects a fair allocation of R. 852.589 and R. 805.193, respectively.
Volume: 18
Issue: 4
Page: 2132-2139
Publish at: 2020-08-01

Voronoi diagram with fuzzy number and sensor data in an indoor navigation for emergency situation

10.12928/telkomnika.v18i4.14905
Nanna; Universiti Teknikal Malaysia Melaka Suryana , Fandy Setyo; Universiti Teknikal Malaysia Melaka Utomo , Mohd Fairuz Iskandar; Universiti Teknikal Malaysia Melaka Othman , Mohd Nazrin; Universiti Teknikal Malaysia Melaka Muhammad
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.
Volume: 18
Issue: 4
Page: 1990-1997
Publish at: 2020-08-01

The TAWOCK conceptual model at content knowledge for professional teaching in vocational education

10.11591/ijere.v9i3.20561
Zainal Arifin , Muhammad Nurtanto , Warju Warju , Rabiman Rabiman , Nur Kholifah
Now days, the integration of technology in the concept of learning is the trend in global education. The conceptual framework model is a general reference, and the only concept is Technology, Pedagogy, and Content Knowledge (TPACK). However, vocational education has knowledge of specific content, so adjusting conceptual models in professional learning is important to learn and offer. The purpose of this study is to evaluate the concept of TPACK into the concept of vocational education to improve the professionalism of vocational teachers in content knowledge. The author discusses the knowledge structure of vocational fields that are built based on work, content, technology, and the suitability of the learning approach. Based on the results of the article found a new construction in building knowledge in the field of vocational education with special expertise characteristics and shifting pedagogical concepts towards andragogy in learning concept. The results of the analysis recommend the TPACK concept transformed into the Technology, Andragogy, Work, and Content Knowledge (TAWOCK) concept in vocational learning.
Volume: 9
Issue: 3
Page: 697-703
Publish at: 2020-08-01

Design and modeling of solenoid inductor integrated with FeNiCo in high frequency

10.12928/telkomnika.v18i4.12139
Abdelhadi; Ahmed Zabana University Centre Namoune , Rachid; Hassiba Benbouali University Taleb , Noureddine; Hassiba Benbouali University Mansour
In this work, the design and modeling of the solenoid inductor are discussed. The layout of integrated inductors with magnetic cores and their geometrical parameters are developed. The quality factor Q and inductance value L are extracted from the S-parameters and plotted versus frequency. The effect of solenoid inductor geometry on inductance and quality factor are studied via simulation using MATLAB. The solenoid inductor geometry parameters considered are the number of turns, length of the magnetic core, the width of a magnetic core, the gap between turns, the thickness of the magnetic core, the thickness of the coil and oxide thickness of solenoid inductor. The performance of the proposed solenoid inductor integrated with FeNiCo is compared with other solenoid inductors.
Volume: 18
Issue: 4
Page: 1746-1753
Publish at: 2020-08-01

Early detection of breast cancer using mammography images and software engineering process

10.12928/telkomnika.v18i4.14718
Muayad Sadik; University of Technology-Iraq Croock , Saja Dhyaa; University of Technology-Iraq Khuder , Ayad Esho; University of Technology-Iraq Korial , Sahar Salman; University of Technology-Iraq Mahmood
The breast cancer has affected a wide region of women as a particular case. Therefore, different researchers have focused on the early detection of this disease to overcome it in efficient way. In this paper, an early breast cancer detection system has been proposed based on mammography images. The proposed system adopts deep-learning technique to increase the accuracy of detection. The convolutional neural network (CNN) model is considered for preparing the datasets of training and test. It is important to note that the software engineering process model has been adopted in constructing the proposed algorithm. This is to increase the reliably, flexibility and extendibility of the system. The user interfaces of the system are designed as a website used at country side general purpose (GP) health centers for early detection to the disease under lacking in specialist medical staff. The obtained results show the efficiency of the proposed system in terms of accuracy up to more than 90% and decrease the efforts of medical staff as well as helping the patients. As a conclusion, the proposed system can help patients by early detecting the breast cancer at far places from hospital and referring them to nearest specialist center.
Volume: 18
Issue: 4
Page: 1784-1794
Publish at: 2020-08-01

A progressive domain expansion method for solving optimal control problem

10.12928/telkomnika.v18i4.15047
Olalekan; Kwara State University Ogunbiyi , Oludare Y.; Federal University of Petroleum Resources Ogundepo , Madugu I.; Kano State University of Science and Technology Wudi Sani , Cornelius; Achievers University Thomas , Benjamin J.; University of Ilorin Olufeagba
Electricity generation at the hydropower stations in Nigeria has been below the expected value. While the hydro stations have a capacity to generate up to 2,380 MW, the daily average energy generated in 2017 was estimated at around 846 MW. A factor responsible for this is the lack of a proper control system to manage the transfer of resources between the cascaded Kainji-Jebba Hydropower stations operating in tandem. This paper addressed the optimal regulation of the operating head of the Jebba hydropower reservoir in the presence of system constraints, flow requirement and environmental factors that are weather-related. The resulting two-point boundary value problem was solved using the progressive expansion of domain technique as against the shooting or multiple shooting techniques. The results provide the optimal inflow required to keep the operating head of the Jebba reservoir at a nominal level, hence ensuring that the maximum number of turbo-alternator units are operated.
Volume: 18
Issue: 4
Page: 2062-2069
Publish at: 2020-08-01
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