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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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Different analytical frameworks and bigdata model for Internet of Things Ayushi Chahal; Preeti Gulia; Nasib Singh Gill
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp1159-1166

Abstract

Sensor devices used in internet of things (IoT) enabled environment produce large amount of data. This data plays a major role in bigdata landscape. In recent years, correlation, and implementation of bigdata and IoT is being extrapolated. Nowadays, predictive analytics is gaining attention of many researchers for big IoT data analytics. This paper summarizes different sort of IoT analytical platforms which consist in-built features for further use in machine learning, MATLAB, and data security. It emphasizes on different machine learning algorithms that plays important role in big IoT data analytics. Besides different analytical frameworks, this paper highlights the proposed model for bigdata in IoT domain and elaborates different forms of data analytical methods. Proposed model comprises different phases i.e., data storing, data cleaning, data analytics, and data visualization. These phases cover the basic characteristics of bigdata V’s model and most important phase is data analytics or big IoT analytics. This model is implemented using an IoT dataset and results are presented in graphical and tabular form using different machine learning techniques. This study enhances researchers’ knowledge about various IoT analytical platforms and usability of these platforms in their respective problem domains.
Energy management in connected and disconnected mode of a photovoltaic system with a battery storage using an artificial neural network technique Ezzitouni Jarmouni; Ahmed Mouhsen; Mohammed Lamhammedi; Zakarya Benizza
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp54-62

Abstract

In order to reduce the inconvenience resulting from the use of the traditional energy sources (oil, gas and coal), the integration of renewable energy sources is among the better solutions. With the integration of green energy sources, there are several strategies that can be adopted, including the combination of clean energy sources (solar, wind, and biomass) with each other, or the combination of renewable sources with conventional sources. In this article, we focus on a photovoltaic system allowing the storage of energy in a battery with a coupling to the electrical grid. In order to overcome the problems related to the random operation that accompanies the use of photovoltaic systems, we have developed a control technique based on the use of artificial neural network technology. The complete system was designed and simulated on MATLAB Simulink.
Community-based framework for influence maximization problem in social networks Mustafa K. Alasadi; Ghusoon Idan Arb
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1604-1609

Abstract

Given a social graph, the influence maximization problem (IMP) is the act of selecting a group of nodes that cause maximum influence if they are considered as seed nodes of a diffusion process. IMP is an active research area in social network analysis due to its practical need in applications like viral marketing, target advertisement, and recommendation system. In this work, we propose an efficient solution for IMP based on the social network structure. The community structure is a property of real-world graphs. In fact, communities are often overlapping because of the involvement of users in many groups (family, workplace, and friends). These users are represented by overlapped nodes in the social graphs and they play a special role in the information diffusion process. This fact prompts us to propose a solution framework consisting of three phases: firstly, the community structure is discovered, secondly, the candidate seeds are generated, then lastly the set of final seed nodes are selected. The aim is to maximize the influence with the community diversity of influenced users. The study was validated using synthetic as well as real social network datasets. The experimental results show improvement over baseline methods and some important conclusions were reported.
Geometric control of quadrotor UAVs using integral backstepping Ali Bouchaib; Rachid Taleb; Ahmed Massoum; Saad Mekhilef
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp53-61

Abstract

The traditional quadcopter control systems should deal with two common problems. Namely, the singularities related to the inverse kinematics and the ambiguity linked to the quaternion representation of the dynamic model. Moreover, the stability problem due to the system nonlinearity and high degree of coupling. This paper provides a solution to the two issues by employing a geometrical integral-backstepping control system. The integral terms were added to improve system ability to track desired trajectories. The high-level control laws are considered as a virtual control and transmitted to the low-level to track the high-level commands. The proposed control system along with the quadcopter dynamic model were expressed in the special Euclidean group SE(3). Finally, the control system robustness against mismatching parameters was studied while tracking various paths.
Secure and smart system for monitoring patients with critical cases Hanan Abed Alwally Abed Allah; Rawsam Abduladheem Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1800-1807

Abstract

Recently, heat-related diseases like COVID19, Chickenpox, Typhoid, and others are increasing significantly; therefore, the need for portable devices to measures the heat of the human body accurately, quickly, easily with low cost has become very necessary to preserve the life of patients. For this reason, a smart system has been developed to monitor the patient's heat, in addition to temperature and humidity of the critical environment such as surgical operating rooms, patients’ isolation rooms and pharmacies, because it can help propagate infectious agents like viruses and bacteria. The proposed system divided into four parts: transmitted part (arduino, heat sensor, and hygrometer sensor), alarm part consists of lights and alarm bell, emergency part (doctors and nurses), and the medical application has been used as the last part. The application can be used only by authorized persons and through the accounts which are granted to them, in order to protect the data from sabotage and maintain the privacy and confidentiality of it.
Text mining approaches for analyzing an Indonesian tafseer and translation of the holy Quran Ayu, Media Anugerah; Irawan, Edi; Mantoro, Teddy
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1469-1480

Abstract

The Indonesian tafseer and translation of Holy Quran is an important source of information and knowledge for Indonesian muslims, since not many Indonesian muslims understand Arabic language in the Quran.  However, the tafseer is full of the commentaries and explanation of each surah (chapter) and/or ayah (verse), which form a large document and not so easy to be accessed. Thus, the challenge is how to refer to both tafseer and translation in faster and accurate ways as one needs to always refer to them back and forth. Hence, this study proposes several text mining approaches, i.e.  most frequent words, K-means clustering, and association rules, to analyze an Indonesian tafseer and translation of Quran and provide insights of hidden knowledge and relationships based on statistical information derived from it.   These insights could be useful for muslims in general and for people that doing research in related areas.  This study shows interesting results from combined analysis of the approaches used which can help people accessing information in tafseer more efficiently.  As well, interesting relationships have been drawn from terms in the tafseer which could provide further and deeper knowledge on messages in the Quran.
Optimized routing algorithm for maximizing transmission rate in D2D network Marwa K. Farhan; Muayad S. Croock
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp575-582

Abstract

Wireless devices have been equiping extensive services over recent years. Since most of these devices are randomly distributed, a fundamental trade-off to be addressed is the transmission rate, latency, and packet loss of the ad hoc route selection in device to device (D2D) networks. Therefore, this paper introduces a notion of weighted transmission rate and total delay, as well as the probability of packet loss. By designing optimal transmission algorithms, this proposed algorithm aims to select the best path for device-to-device communication that maximizes the transmission rate while maintaining minimum delay and packet loss. Using the Lagrange optimization method, the lagrangian optimization of rate, delay, and the probability of packet loss algorithm (LORDP) is modeled. For practical designation, we consider the fading effect of the wireless channels scenario. The proposed optimal algorithm is modeled to compute the optimal cost objective function and represents the best possible solution for the corresponding path. Moreover, a simulation for the optimized algorithm is presented based on optimal cost objective function. Simulation results establish the efficiency of the proposed LORDP algorithm.
A new function of stereo matching algorithm based on hybrid convolutional neural network Mohd Saad Hamid; Nurulfajar Abd Manap; Rostam Affendi Hamzah; Ahmad Fauzan Kadmin; Shamsul Fakhar Abd Gani; Adi Irwan Herman
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp223-231

Abstract

This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. The main purpose of the stereo matching algorithm is to produce a disparity map. This map is essential for many applications, including three-dimensional (3D) reconstruction. The raw disparity map computed by a convolutional neural network (CNN) is still prone to errors in the low texture region. The algorithm is set to improve the matching cost computation stage with hybrid CNN-based combined with truncated directional intensity computation. The difference in truncated directional intensity value is employed to decrease radiometric errors. The proposed method’s raw matching cost went through the cost aggregation step using the bilateral filter (BF) to improve accuracy. The winner-take-all (WTA) optimization uses the aggregated cost volume to produce an initial disparity map. Finally, a series of refinement processes enhance the initial disparity map for a more accurate final disparity map. This paper verified the performance of the algorithm using the Middlebury online stereo benchmarking system. The proposed algorithm achieves the objective of generating a more accurate and smooth disparity map with different depths at low texture regions through better matching cost quality.
A review of IoT-based smart waste level monitoring system for smart cities A. A. I. Shah; S. S. M. Fauzi; R. A. J. M. Gining; T. R. Razak; M. N. F. Jamaluddin; R. Maskat
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp450-456

Abstract

Smart cities are covering the population that are seeking the best lifestyle and fulfilling their needs. Through smart cities, necessary modern facilities using ICT emerging technologies such as the internet of things (IoT) had been installed to ensure the sustainability of the city. In the perspective of waste management, several different IoT-based solutions also had been proposed as an alternative to monitor and to ensure the health of communities. This paper reviews existing IoT-based solutions in smart cites’ waste level management system to bring together the state-of-the-art. We performed reviews on 16 research articles from the past 5 years in the literature to provide a comprehensive review of different works on IoT-based solutions related to the smart waste level monitoring system, possible solutions and technologies used. The results obtained shows that existing solutions were similar in the platform used to integrate with the IoT technologies but had some differences in term of the used of sensors and communication technologies. The study also shows that many of the prior studies used Arduino Uno. Results from this study will assist the researcher, focusing on expanding further the used of different technologies or improved the existing system.
Fire incidents visualization and pattern recognition using machine learning algorithms Jonardo R. Asor; Jefferson L. Lerios; Sherwin B. Sapin; Jocelyn O. Padallan; Chester Alexis C. Buama
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1427-1435

Abstract

A fire incident is a devastating event that can be avoided with enough knowledge on how and when it may occur. For the past years, fire incidents have become a big problem for the Philippines, since it affects the socio-economic growth of the country. Machine learning algorithm is a well-known technique to predict and analyze data. It can also be used to recognize pattern and develop models for artificial intelligence. Pattern recognition through machine learning algorithm is already established and have proven itself accurate in different fields such as education, crime, health and many others including fire incidents. This paper aims to develop a model for recognizing patterns of fire incidents in the province of Laguna, Philippines implementing a machine learning algorithm. With the foregoing project, it is found out that a recurrent neural network shows an astonishing result in terms of pattern recognition. Further, it is also found that Calamba City is the most vulnerable area in case of fire occurrence in the Province of Laguna.

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