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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 9,174 Documents
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Monitoring of submersible pumps using ESP32 microcontroller and photovoltaic panels Zaidan Didi; Ikram El Azami
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1470-1477

Abstract

In this article, the Moroccan climate is currently undergoing several changes that have negatively affected agricultural activities, especially in the field of irrigation. That's why we relied on internet of things (IoT) technology to overcome these problems. In this article, we present the design and realization of an intelligent irrigation system via a solar submersible pump. We used the ESP32 microcontroller which reads the temperature and humidity values measured by the soil moisture sensor. The communication between the blocks is ensured by the radiofrequency module. We have implemented a Web server to monitor the measured quantities. The graphical representation of the data will be ensured using the ThingSpeak platform which makes it possible to store and collect the data coming from the sensors via the hypertext transfer protocol (HTTP). Our achievement was executed and tested without any problems detected, which shows that our smart irrigation study was very successful.
Hammer-shaped slotted antenna design and analysis for wireless applications Gajendran Srihari; Raman Ramamoorthy; Shanmuganantham Thangavelu; Nimmagadda Padmaja
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1488-1497

Abstract

The method for creating a two-element multiple-input and multiple-output (MIMO) ultra-wideband hammer antenna is presented in this paper. It has been suggested to investigate characteristics of this ultra-wideband antenna design. Split-ring resonators (SRR), made of metamaterial, have enhanced performance of antenna in terms of multiplexing effectiveness, S parameters, radiation characteristics, envelope correlation coefficient, and diversity gain. Reduced weight and size of this antenna technology make it easier to integrate into a 5G and linked object receiver. Because the outputs from the previous designer to the target entity did not satisfy the standards, we thoroughly researched design attributes and made parametric changes to the design to reach the precise outcomes.
Toward measuring the usability of decision support applications in fog computing environment Oras Abdulkhdhur Hussein; Ayad Hameed Mousa
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1689-1698

Abstract

Decision support systems are applications that provide meaningful information and help with decision support. To gain the benefits of these applications, they need to be used optimally. Thus, the optimal manner to utilize relies on several properties, such as usability. This research aims to investigate the decision support systems applications (DSS) in terms of usability evaluation and propose a usability instrument for DSS in a fog computing environment. Recently, complexity is a major problem with most software products. Hence, the way to ensure user satisfaction is by measuring its usability. The study is based on the research question: What dimensions and their elements that utilize to evaluate the usability of DSS applications. A systematic literature review (SLR) was conducted to understand and extract all the instrument’s dimensions and elements. To confirm the validity of the proposed instrument, Multi scientific methods were adapted such as face validity, a pilot study for testing the goodness of proposed instrument consistency, and factor analysis. Furthermore, Bartlett’s test was utilized to ensure the reliability of the developed instrument. Eventually, the validated instrument was used to evaluate DSS application in a fog computing environment. The findings show that the proposed instrument is workable in practice.
Low leakage decoder using dual-threshold technique for static random-access memory applications R. Krishna; Punithavathi Duraiswamy
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1420-1427

Abstract

Decoders are one of the significant peripheral components of static random-access memory (SRAM). As the CMOS technology moves towards nano scale regime, the leakage power starts dominating dynamic power. In this paper, we propose decoders using NAND logic in 32 nm CMOS technology. Leakage power is reduced by employing dual-threshold technique. Dual thresholding is a technique that uses transistors of two different threshold voltages. The technique is implemented in simulation by two methods; first method uses transistors with different threshold voltage and the second method uses substrate biasing to vary the threshold voltage. Row and column decoders are designed and simulated in H-Spice. The leakage power is calculated and compared for both the methods. The NAND gate implemented by Method-1 and Method-2 provides a maximum leakage power savings of 87.67% and 90.81% respectively. The maximum leakage power savings of 96.76% and 98.74% is reported for the row decoder implemented by Method-1 and Method-2 respectively. Similarly, Method-1 gives maximum leakage power savings of 97.09% and Method-2 gives a savings of 99.11% for column decoder. The difference in leakage power savings of Method-1 and Method-at same threshold voltage is 3.14%, 1.98%, and 2.02% for NAND gate, row decoder and column decoder respectively.
Cluster-based denoising autoencoders for rate prediction recommender systems Ammar Abdulsalam Al-Asadi; Mahdi Nsaif Jasim
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1805-1812

Abstract

Recommender system (RS) is a suitable tool for filtering out items and providing the most relevant and suitable items to each user, based on their individual preferences. Deep learning algorithms achieve great success in several fields including RS. The issue with deep learning-based RS models is that, they ignore the differences of users’ preferences, and they build a model based on all the users’ rates. This paper proposed an optimized clustering-based denoising autoencoder model (OCB-DAE) which trains multiple models instead of one, based on users’ preferences using k-means algorithm combined with a nature-inspired algorithm (NIA) such as artificial fish swarm algorithm to determine the optimal initial centroids to cluster the users based on their similar preferences, and each cluster trains its own denoising autoencoder (DAE) model. The results proved that combining NIA with k-means gives better clustering results comparing with using k-means alone. OCB-DAE was trained and tested with MovieLens 1M dataset where 80% of it is used for training and 20% for testing. Root mean squared error (RMSE) score was used to evaluate the performance of the proposed model which was 0.618. It outperformed the other models that use autoencoder and denoising autoencoder without clustering with 38.5% and 29.5% respectively.
Development and evaluation of a didactic tool with augmented reality for Quechua language learning in preschoolers Joselyn Zapata-Paulini; Saul Beltozar-Clemente; Fernando Sierra-Liñan; Michael Cabanillas-Carbonell
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1548-1557

Abstract

It is important to preserve our cultural identity through the preservation of our mother tongue, contributing to its dissemination. Augmented reality (AR) is a great ally of education that provides efficiency, and productivity and increases the interest of students in their academic activities. An AR application was developed for learning Quechua in preschool children, thus improving their learning, satisfaction, and preference compared to traditional teaching. Previously, learning styles were identified for better coverage of the application; the design thinking methodology was applied for the development of the application, then the respective tests were conducted where it was obtained that the children's performance improved by 28.3% more compared to traditional teaching, with an average satisfaction of 89% of the classrooms, and 81% of students' preference. It was concluded that the proposed application considerably favors the written and audiovisual learning of the Quechua language in preschool students.
Sentiment analysis of Twitter data regarding the agnipath scheme of the defense forces Vijaylakshmi Sajwan; Monisha Awasthi; Ankur Goel; Priyank Sharma
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1643-1650

Abstract

Due to the popularity of social media today, people frequently share such criticism on Facebook, Twitter, Instagram, and other platforms. Therefore needs to know how your input from users of social media is generated in order to ascertain the public reaction to the policy that has been enacted. However, because of the comments, it is challenging to tell how many people have responded positive or negative. The objective of sentiment analysis of tweets is to provide insight into people’s attitudes and perceptions regarding an event. This study illustrates the role of Twitter in the announcement of a new army vacancy through the “agnipath scheme” dubbed “agniveer”. The result of this study can be used by the defense forces and government for decision making or policies related to the agnipath scheme. The study studied 4,000 English-language Twitter posts from July 3, 2022 to July 9, 2022. Manual text analysis revealed seven basic groups of tweet sentiments. The tweets’ positive, negative, and neutral emotions were shown using orange data mining software, a powerful machine learning, data mining, and data visualization toolset. Result shows that agnipath scheme is mostly accepted by the people.
Knee-joint exoskeleton control system design using adaptive barrier function controller Amer B. Rakan; Mohammed Rashid Subhi; Ali H. Mhmood
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1440-1448

Abstract

Exoskeletons and wearable robots are mechatronic devices that are worn by an operator and fit closely to the body to improve daily activities. The adaptive sliding mode control (ASMC) based on the barrier function is proposed in this study to regulate the movement of the knee joint exoskeleton with friction. This controller is implemented without the requirement to know the system model uncertainty and disturbance bounded and does not require the use of the low pass for chattering elimination with keeping the controller’s performance. The suggested barrier method can be guaranteed the output variable’s convergence and keep it in a preset neighborhood of zero regardless of the disturbance’s upper bound, without overestimating the control gain. The simulation results show that the proposed performs well, the system angle following the target angular position with a modest pre-adjusted steady-state error. Furthermore, when compared to a typically strong and stable ASMC developed with the identical actuator; the obtained results reveal superior features. Concluded from the above this control method indicates the robustness of the proposed adaptive controller with barrier function against uncertainties and disturbances elimination.
Do clinical decision support systems for prescribing improve patient safety? a systematic literature review Sri Kusumadewi; Isnatin Miladiyah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1748-1761

Abstract

Clinical decision support systems (CDSS) are developed independently or connected to the electronic health record (EHR) or other computerized systems. The study begins with identification by searching the literature through the Google Scholar, PubMed and ScienceDirect databases. The search results obtained 5,595 articles. Forty-two articles were obtained, which were used further. Most of the research focus is on "CDSS development and evaluation". In terms of impacts, the most common is "reduce prescribing errors". One of the biggest problems reported was the presence of "alert fatigue," which was felt to be disturbing to doctors and pharmacists. CDSS must be supported by a method that is able to indicate the presence of drug-drug interactions (DDI). The use of alerts indicating the presence of a DDI should be interpreted using clinical judgment to determine the risks and benefits of a particular drug for a specific patient. The performance of CDSS is mostly reported to have been able to reduce prescribing errors, which in turn will improve patient safety. However, increased adherence to clinical protocols has not been widely reported. Complaints that are still quite a lot reported are the presence of "alert fatigue", which can interfere with effectiveness.
A novel hybrid feature extraction and ensemble C3D classification for anomaly detection in surveillance videos Vishnu Priya Thotakura; Purnachand Nalluri
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1572-1585

Abstract

Anomaly detection in several deep learning frameworks are recently presented on real-time video databases as a challenging task. However, these frameworks have high false positive rate (FPR) and error rate due to various backgrounds, motion appearance and semantic high-level and low-level features for anomaly detection through action classification. Also, extraction of features and classification are the major problems in traditional convolution neural network (CNN) on real-time video databases. The proposed work is a novel action classification framework which is designed and implemented on large video databases with high true positive rate (TPR) and error rate. In this framework, Kalman based incremental principal component analysis (IPCA) feature extraction method; C3D and non-linear support vector machine (SVM) classifier are used to improve the action prediction (anomaly detection) on the large real-time video databases. The proposed frame work shown new results of high computation performance than the traditional deep learning frameworks for action classification.

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