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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 65 Documents
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Search results for , issue "Vol 18, No 3: June 2020" : 65 Documents clear
Harmonic current classification using hybrid FAM-RBF neural network Shoun Ying Leow; Keem Siah Yap; Shen Yuong Wong
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1551-1558

Abstract

In this paper, the type of customers of electricity in Malaysia is classified into the type of electricity consumers based on the harmonic current data. A hybrid of Fuzzy Adaptive Resonance Theory with Mapping Algorithm (Fuzzy ARTMAP) and Radial Basis Function (RBF) neural network is developed (namely FAM-RBF), and it is used to classify the harmonic current into types of consumers. The result of the proposed neural network is discussed, and compared with other neural networks in this paper. The comparison result shows that the proposed FAM-RBF obtained the best performance result and is a truthful neural network to be used in this application.
Ant colony algorithm for text classification in multicore-multithread environment Ahmad Nazmi Fadzal; Mazidah Puteh; Nurazzah Abd Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1359-1366

Abstract

This paper presents about Ant Colony Algorithm (ACO) for Text Classification in Multicore-Multithread Environment in Artificial Intelligent domain. We had develop a software which assimilate concurrency concept to multiple artificial ants. Pheromone in ACO is the main concept used to solve the text classification problem. In regards to its role, pheromone value is changed depending on the solution finding that has been discovered at the pseudo random heuristic attempt in selecting path from text words. However, ACO can take up longer time to process larger training document. Based on the cooperative concept of ants living in colony, the ACO part is examined to work in multicore-multithread environment as to cater additional execution time benefit. In running multicore-multithread environment, the modification aims to make artificial ants actively communicate between multiple physical cores of processor. The execution time reduction is expected to show an improvement without compromising the original classification accuracy by the investment of trading on more processing power. The single and multicore-multithreaded version of ACO was compared statistically by conduction relevant test. It was found that the result shows a positive time reduction improvement.
A comparative analysis of classification techniques on predicting flood risk Nazri Mohd Nawi; Mokhairi Makhtar; Mohd Zaki Salikon; Zehan Afizah Afip
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1342-1350

Abstract

Flood is a temporary overflow of a dry area due to overflow of excess water, runoff surface waters or undermining of shoreline. In Malaysia itself in 2014, the country grieved with the catastrophic flood event in Kuala Krai, Kelantan, which caused of human lives, public assets and money lost. Due to uncertainties in flooding event, it is vital for Malaysia to have pre-warning system that assist related agencies in to categorize land areas that face high risk of flood so preventive actions can be planned in place. This paper conducts a comparative analysis of three classifications in classifying the risk of flood, whether high or low. The classification experiment conducts using three variants of Bayesian approaches, which are Bayesian Networks (BN), Naive Bayes (NB), and Tree Augmented Naive Bayes (TAN). The outcome of this research shows that Tree Augmented Naive Bayes (TAN) has the best algorithms as compared to others algorithms in classifying the risk of flood.
Automated detection of vehicles license plate using image processing techniques Farhana Ahmad Poad; Noor Shuraya Othman; Roshayati Yahya Atan; Jusrorizal Fadly Jusoh; Mumtaz Anwar Hussin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1408-1415

Abstract

The aim of this project is to design an Automated Detection of License Plate (ADLP) system based on image processing techniques. There are two techniques that are commonly used in detecting the target, which are the Optical Character Recognition (OCR) and the split and merge segmentation. Basically, the OCR technique performs the operation using individual character of the license plate with alphanumeri characteristic. While, the split and merge segmentation technique split the image of captured plate into a region of interest. These two techniques are utilized and implemented using MATLAB software and the performance of detection is tested on the image and a comparison is done between both techniques. The results show that both techniques can perform well for license plate with some error.
Quranic verse finder: a tool for speech preparation using quranic verses Maslina Abdul Aziz; Irfan Fikri Azni; Wan Faezah Abbas; Mohd Izuan Hafez; Nur Nafhatun Md Shariff
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1616-1623

Abstract

This paper presents a mobile application called the Quranic Verse Finder. The main idea of this study is to develop a mobile application to help preachers in preparing their speech text. Based on preliminary investigation, the minimum time for a preacher to prepare a speech for a given topic is 3 hours. This process is very time consuming since the speech needs to refer to different source of reference such as the Quran and Hadith. The existing Quran search on the website or mobile application are from unknown source of reference. Therefore, to solve the problems mentioned above, this application offers an efficient method to search and identify any Quran verses for reference. With this application, the user can identify the juz number, the name of the Surah, which number of verses in the Surah and the meaning of the verses of a specific verse. The Quranic Verse Finder is different from other existing Quran Search applications due to its bilanguage feature. This application provides Malay and English translation. It also has other special features such as Bookmark that allows specific Quran verse to be saved for later reference. Moreover, due to the current trends, the Quranic Verse Finder allows user to share it using popular social media sites such as Facebook and Twitter.
Automatic gray images colorization based on lab color space Nidhal K. El Abbadi; Eman Saleem Razaq
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1501-1509

Abstract

The colorization aim to transform a black and white image to a color image. This is a very hard  issue and usually requiring manual intervention by the user to produce high-quality images free of artifact. The public problem of inserting gradients color to a gray image has no accurate method. The proposed method is fully automatic method. We suggested to use reference color image to help transfer colors from reference image to gray image.  The reference image converted to  Lab color space, while the gray scale image normalized according to the lightness channel L. the gray image concatenate with both a, and b channels before converting to RGB image. The results were promised compared with other methods.
The development of simulation logic model that dealing with uncertainty for piping construction industry Zirawani Baharum; HairulNizam Mahdin; Fauziah Abdul Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1311-1318

Abstract

Basically, multi processes and activities involve in the piping construction (PC) projects needs to be followed before the project is handed over to the customer or client, called multi-project construction environment (MPCE). In PC, the MPCEs exist where more than one project is managed simultaneously within an organization become as a common phenomenon faced by managers that highly possible to face with uncertainty issues, lead to project completion late delivery (PCLD). Dealing with uncertainty in MPCE is a common, though managing uncertainty in PC become more complicated rather that others industry. Therefore, the objective of this paper is to develop the simulation logic model to deal with the uncertainty for PC projects that focused on environmental issues (EI). This result will be proceed for uncertainty model development in the next phase of this research. The simulation logic model development began with qualitative data collection towards the case study, to get all the activities throughout the water supply company. Then, the business model is developed with 14 activities before integrated with the uncertainty factors in EI. The integration of business model and uncertainty factors generated the simulation logic model as main contribution. Once the uncertainty model completely developed, it will provide a medium for PC that confront with MPCE to monitor the uncertainties and prepared to encounter any matters in future. Therefore, it is important to pursue in providing the PC company to all inclusive-model, and helping them in managing and tackling the uncertainty, especially for EI.
Faulty sensor detection using multi-variate sensors in internet of things (IoTs) Khaldoon Ammar Omar; Ahmed Dhahir Malik; Ansar Jamil; Hasan Muwafeq Gheni
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1391-1399

Abstract

IoT devices are lightweight and have limited computational capabilities often exposed to harsh environments, which can cause failure on the IoT devices [1, 2].  The failure on the IoT devices is also caused due to limited battery life, hardware failure or human mistakes. Sensor faults can be categorized under one type of hardware failure, such as sensor burn, reduced sensor sensitivity and malfunctioned sensors.  Any faulty on the IoT devices can cause a problem on the overall operation of the IoT system. Traditional ways in the management of IoT devices is a maintenance officer require to check each device every day  [1, 3]. Any faulty devices found needs to be fixed or replaced. This traditional method is not practical and very challenging especially in the management of a large scale deployment of IoT consist of hundreds or thousands devices. Because of this, we proposed a faulty sensor detection and identification mechanism using multivariate sensors. Two methods of decision making are introduced in detecting faulty sensors, which are logical and correlation method that implemented in smart parking system and smart agriculture system accordingly. The logical method compares state of all sensors (ultrasound, IR and hall-effect) in the smart parking system either a parking lot is occupied or available, and then determine the condition of the sensors. The drawback of this method is not able to detect faulty sensor properly for a constant fault, which the sensor reading remains the same value. The correlation method calculates the correlation between all sensors (soil moisture, soil temperature and soil water) in the smart agriculture system. This method uses a moving window technique to calculate the correlation for all sensor over time. Any incomparable and uncorrelated sensor readings means a presence of faulty sensors. Based on the experiment results, the findings shows that the proposed faulty sensor detection mechanism is working properly in detecting faulty sensor in a timely manner.
A business model canvas for crowdfunding platform: case study of crowdfunding platforms in Malaysia Muhammad Hakim Bin Nadir; Syaripah Ruzaini Syed Aris; Norjansalika Janom; Fauziah Ahmad; Noor Habibah Arshad; Nor Shahniza Kamal Bashah
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1287-1294

Abstract

Crowdfunding allows entrepreneurs raise fund to help subsidizing their project. In other country, crowdfunding platform has become famous. In the contrary, it is yet to be trend in Malaysia. Financing using internet still irrelevant among Malaysian citizen. Without a proper guideline and strong crowdfunding platform based in Malaysia as a benchmark, it is hard to convince entrepreneurs and funders to consider crowdfunding as an option to fund a project. This research thus proposed business model canvas which can be applied by the crowdfunding platform organizations to manage their business and operation more efficiently. Case study method has been employed with two techniques of data collection: interview and document review. Two crowdfunding platforms based in Malaysia participated in the case study. The findings show that both crowdfunding platforms have fundamental business model elements that made of a solid foundation as a crowdfunding platform. These results offer insight into crowdfunding environment and how it links to another necessary part of business for it to function as a successful business. Nine building blocks fits well in the crowdfunding platform business model elements namely partner network, core competency, key resources, value proposition, customer relationship, distribution channel, customer segments, cost structure and revenue stream. Interestingly, the findings revealed another imperative element that should be part of the canvas: risk management.
OperativeCriticalPointBug algorithm-local path planning of mobile robot avoiding obstacles Subir Kumar Das; Ajoy Kumar Dutta; Subir Kumar Debnath
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1646-1656

Abstract

For Autonomous Mobile Robot one of the biggest and interesting issues is path planning. An autonomous mobile robot should be able determine its own path to reach destination. This paper offers a new algorithm for mobile robot to plan a path in local environments with stationary as well as moving obstacles. For movable robots’ path planning OperativeCriticalPointBug (OCPB) algorithm, is a new Bug algorithm. This algorithm is carried out by the robot throughout the movement from source to goal, hence allowing the robot to rectify its way if a new obstacle comes into the route or any existing obstacle changes its route. According as, not only the robot tries to avoid clash with other obstacle but also tries a series of run time adjustment in its way to produce roughly a best possible path. During journey the robot is believed to be capable to act in an unknown location by acquiring information perceived locally. Using this algorithm the robot can avoid obstacle by considering its own as well as the obstacle’s dimension. The obstacle may be static or dynamic. The algorithm belongs to bug family.

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