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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 66 Documents
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Search results for , issue "Vol 23, No 3: September 2021" : 66 Documents clear
NARX-based water quality index model of Air Busuk River using chemical parameter measurements Muhammad Ierfan Hasnan; Azhar Jaffar; Norashikin M. Thamrin; Mohamad Farid Misnan; Ahmad Ihsan Mohd Yassin; Megat Syahirul Amin Megat Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1663-1673

Abstract

Water quality plays a major role in issues related to public health and marine life. Hence, monitoring river for contaminations is vital for ensuring safe and sustainable water resources. Conventional method for assessing water quality index is costly as it requires considerable amount of time and laboratory resources. Therefore, this study proposes a water quality index model based on artificial neural network. A six-year data for Air Busuk River is obtained from the Department of Environment. Dissolved oxygen, biological oxygen demand, and ammoniacal nitrogen has shown high correlation with water quality index. The water quality index model is then developed based on these parameters, employing the non-linear autoregressive with exogeneous input structure. Generally, the model which is based on three chemical parameters has shown satisfactory performance with overall regression of 0.8767 and passed the correlation function tests. The model offers a potentially efficient method for assessing water quality with cost-saving benefits for government agencies and monitoring authorities.
Automatic dependent bug reports assembly for bug tracking systems by threshold-based similarity B. Luaphol; J. Polpinij; M. Kaneampornpan
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1620-1633

Abstract

Bug reports contain essential information for fixing problems that occur in software. Many studies have proposed methods for automatic analysis of bug reports. One such task could affect the completion of software bug fixing, known as “bug dependency”. Although this problem was mentioned by many researches, most of them discussed about the related bugs but not really dealt with dependency issue in bug reports. One possible solution used for addressing this issue is to assemble all relevant/dependent bug reports together before analysis of the next processing stages. This study presents a method of assembling dependent bug reports. The main mechanism is called “threshold-based similarity analysis”, and the three similarity techniques of cosine similarity (CS) multi aspect TF (MATF), and BM25 are compared with feedback, precision and likelihood value. As the BM25 with the threshold as 0.5 gives the best results, it was used to compare with the state of the art method. The results show that our method increases precision and likelihood values by 12% and 12.4% respectively. Therefore, our results can be used to encourage developers to recognize all dependent bugs in the same problem domain.
Distribution of attempted leader with monsoon seasons and negative cloud-to-ground flashes in Melaka, Malaysia Nur Asyiqin Isa; Zikri Abadi Baharudin; Hidayat Zainuddin; Tole Sutikno; Maslan Zainon; Ahmad Aizan Zulkefle
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1324-1330

Abstract

Ninety (90) waveforms recognized as attempted leader were identified with both positive (84 events) and negative (6 events) initial polarity observed from four consecutive years of data (N=10,206). The positive attempted leader shows no correlation with the number of thunderstorms producing it during monsoon. Meanwhile, the negative attempted leader during monsoon and both polarity of attempted leader (positive and negative) during inter-monsoon shows positive correlation with the number of thunderstorms producing it. In this study, the yearly statistical distribution of negative cloud-to-ground (CG) lightning flashes which were classified as positive preliminary breakdown pulses (214 events) and negative preliminary breakdown pulses (4982 events) in accordance of their preliminary polarity were also presented. In addition, there is no relationship of attempted leader and the initial breakdown of negative ground flash since both mechanisms performed as a negative correlation.
Machine learning deployment for arms dynamics pattern recognition in Southeast Asia region Zul Indra; Azhari Setiawan; Yessi Jusman; Arisman Adnan
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1654-1662

Abstract

Finding the most significant determinant variable of arms dynamic is highly required due to strategic policies formulations and power mapping for academics and policy makers. Machine learning is still new or underdiscussed among the study of politics and international relations. Existing literature have much focus on using advanced quantitative methods by applying various types of regression analysis. This study analyzed the arms dynamic in Southeast Asia countries along with its some strategic partners such as United States, China, Russia, South Korea, and Japan by using ‘Decision Tree’ of machine learning algorithm. This study conducted a machine learning analysis on 55 variable items which is classified into 8 classes of variables videlicet defense budget, arms trade exports, arms trade imports, political posture, economic posture, security posture and defense priority, national capability, and direct contact,. The results suggest three findings: (1) state who perceives maritime as strategic drivers and forces will seek more power for its maritime defense posture which is translated to defense budget, (2) big size countries tend to be an arms exporter country, and (3) state’s energy dependence often leads to a higher volume of arms transfers between countries.
The effects of the cross-entropy stopping criterion and quadrature amplitude modulation on iterative turbo decoding performance Roslina Mohamad; Mohamad Yusuf Mat Nasir; Nuzli Mohamad Anas
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1557-1564

Abstract

One of the most often-used stopping criteria is the cross-entropy stopping criterion (CESC). The CESC can stop turbo decoder iterations early by calculating mutual information improvements while maintaining bit error rate (BER) performance. Most research on iterative turbo decoding stopping criteria has utilised low-modulation methods, such as binary phase-shift keying. However, a high-speed network requires high modulation to transfer data at high speeds. Hence, a high modulation technique needs to be integrated into the CESC to match its speed. Therefore, the present paper investigated and analysed the effects of the CESC and quadrature amplitude modulation (QAM) on iterative turbo decoding. Three thresholds were simulated and tested under four situations: different code rates, different QAM formats, different code generators, and different frame sizes. The results revealed that in most situations, the use of CESC is suitable only when the signal-to-noise ratio (SNR) is high. This is because the CESC significantly reduces the average iteration number (AIN) while maintaining the BER. The CESC can terminate early at a high SNR and save more than 40% AIN compared with the fixed stopping criterion. Meanwhile, at a low SNR, the CESC fails to terminate early, which results in maximum AIN.
Different soliton pulse order effects on the fiber communication systems performance evaluation Mahmoud M. A. Eid; Abd El-Naser A. Mohammed; Ahmed Nabih Zaki Rashed
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1485-1492

Abstract

The study outlined the soliton pulse order effects on the performance efficiency of the optical transceiver systems. The power after fiber is reported for various Soliton pulse order. Max optical signal power (SP) and min optical noise power (NP) are clarified versus time after optical fiber for various soliton pulse order. As well as the max electrical power amplitude against time period is demonstrated after electrical filter for various soliton pulse order. It is reported that the optical transceiver performance efficiency can be upgraded with the first soliton order pulse. The soliton technique is used for high speed communication transmission systems. Soliton technique is used to compensate the dispersion and balanced with nonlinear effects. The soliton order effects is then discussed to choose the suitable soliton order for high speed system performance efficiency. The soliton techniques can be used also for extended ultra high transmion distance with high data rates.
Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation Siti Fatimah Sulaiman; M. F. Rahmat; Ahmad Athif Faudzi; Khairuddin Osman; N. H. Sunar
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1385-1397

Abstract

The issues of inaccurate positioning control have made an industrial use of pneumatic actuator remains restricted to certain applications only. Non-compliance with system limits and properly control the operating system may also degrade the performance of pneumatic positioning systems. This study proposed a new approach to enhance pneumatic positioning system while considering the constraints of system. Firstly, a mathematical model that represented the pneumatic system was determined by system identification approach. Secondly, model predictive controller (MPC) was developed as a primary controller to control the pneumatic positioning system, which took into account the constraints of the system. Next, to enhance the performance of the overall system, nonlinear gain function was incorporated within the MPC algorithm. Finally, the performances were compared with other control methods such as constrained MPC (CMPC), proportional-integral (PI), and predictive functional control with observer (PFC-O). The validation based on real-time experimental results for 100 mm positioning control revealed that the incorporation of nonlinear gain within the MPC algorithm improved 21.03% and 2.69% of the speed response given by CMPC and PFC-O, and reduced 100% of the overshoot given by CMPC and PI controller; thus, providing fast and accurate pneumatic positioning control system.
Implementation of arduino pro mini and ESP32 cam for temperature monitoring on automatic thermogun IoT-based P. W. Rusimamto; Endryansyah Endryansyah; L. Anifah; R. Harimurti; Y. Anistyasari
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1366-1375

Abstract

The purpose of this research is to monitor the temperature by applying arduino pro mini and ESP32 cam using IoT technology which is connected to a web interface. Arduino is used as the main brain of the system where arduino will read data from the MLX90614-ACF temperature sensor. Sensor data will continue to be sent to the server by arduino via the ESP32 cam module. This tool can also take pictures and send images automatically at the same time when measuring temperature. The captured image will automatically be sent to the PC/laptop monitor screen via the website. The website is used to display and monitor the results of temperature measurement data and display the image results from the ESP32 cam. The process of taking photos and measuring body temperature is done automatically. Users can also view data from sensors and photo data sent by arduino and ESP32 cam via the provided web interface. From the test results, this system has been running well where all sensor data is sent and can be displayed on the website. Images and measurement data results are sent to the monitor screen via the website interface with a measurement accuracy of 99.6%.
Assessment of online education problems during the COVID-19 pandemic in Russia Ilshat Garafiev; Gulshat Garafieva; Angelika Idiatullina; Elena Spirchagova
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1689-1698

Abstract

The work studied the assessment of online education problems during the COVID-19 pandemic by the first year master’s students. It was hypothesized that there are two types of problems. The first type is the problems associated with the difficulties of online communication between the participants of the educational process. The second type is the problems associated with the technical difficulties of participating in online education. The results of factor analysis show that masters clearly distinguish between the content-related (online communication) and formal (technical problems) sides of the organization of online education. It was found that those masters’ students who do not work now or do not have work experience in the specialty for which they are studying generally perceive the presence of technical problems and Internet disruptions as difficulties in implementing online education more significantly.
Multilinear principal component analysis for iris biometric system Chetana Kamlaskar; Aditya Abhyankar
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1458-1469

Abstract

Iris biometric modality possesses inherent characteristics which make the iris recognition system highly reliable and noninvasive. Nowadays, research in this area is challenging compact template size and fast verification algorithms. Special efforts have been employed to minimize the size of the extracted features without degrading the performance of the iris recognition system. In response, we propose an improved feature fusion approach based on multilinear subspace learning to analyze Iris recognition. This approach consists of four stages. In the first stage, the eye image is segmented to extract the iris region. In the second step, wavelet packet decomposition is conducted to extract features of the iris image, since good time and frequency resolutions can be provided simultaneously by the wavelet packet decomposition. In the next step, all decomposed nodes or packets are arranged as a 3rd order tensor rather than a long vector, in which feature fusion is directly implemented with multilinear principal component analysis (MPCA). This approach provides a more compact or useful low-dimensional representation directly from the original tensorial representation. Finally, a discriminative tensor feature selection mechanism and classification strategy are applied to iris recognition problem. The obtained results indicate the usefulness of MPCA to select discriminative features and fuse them effectively. The experimental results reveal that the proposed tensor-based MPCA approach achieved a competitive matching performance on the SDUMLA-HMT Iris database with an adequate acceptable rate.

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