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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 67 Documents
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Search results for , issue "Vol 22, No 3: June 2021" : 67 Documents clear
An approach of adaptive notch filtering design for electrocardiogram noise cancellation Rahmad Hidayat; Ninik Sri Lestari; Herawati Herawati; Givy Devira Ramady; Sudarmanto Sudarmanto; Farhan Adani
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.pp1303-1311

Abstract

An electrocardiogram (ECG) is a means of measuring and monitoring important signals from heart activity. One of the major biomedical signal issues such as ECG is the issue of separating the desired signal from noise or interference. Different kinds of digital filters are used to distinguish the signal components from the unwanted frequency range to the ECG signal. To address the question of noise to the ECG signal, in this paper the digital notch filter IIR 47 Hz is designed and simulated to demonstrate the elimination of 47 Hz noise to obtain an accurate ECG signal. The full architecture of the structure and coefficient of the IIR notch filter was carried out using the FDA Tool. Then the model is finished with the help of Simulink and the MATLAB script was to filter out the 47 Hz noise from the signal of ECG. For this purpose, the normalized least mean square (NLMS) algorithm was used. The results indicate that before being filtered and after being filtered it clearly shows the elimination of 47 Hz noise in the signal of the ECG. These results also show the accuracy of the design technique and provide an easy model to filter out noise in the ECG signal.
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.
Tuned bidirectional encoder representations from transformers for fake news detection Amsal Pardamean; Hilman F. Pardede
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.pp1667-1671

Abstract

Online medias are currently the dominant source of Information due to not being limited by time and place, fast and wide distributions. However, inaccurate news, or often referred as fake news is a major problem in news dissemination for online medias. Inaccurate news is information that is not true, that is engineered to cover the real information and has no factual basis. Usually, inaccurate news is made in the form of news that has mass appeal and is presented in the guise of genuine and legitimate news nuances to deceive or change the reader's mind or opinion. Identification of inaccurate news from real news can be done with natural language processing (NLP) technologies. In this paper, we proposed bidirectional encoder representations from transformers (BERT) for inaccurate news identification. BERT is a language model based on deep learning technologies and it has found effective for many NLP tasks. In this study, we use transfer learning and fine-tuning to adapt BERT for inaccurate news identification. The experiments show that our method could achieve accuracy of 99.23%, recall 99.46%, precision 98.86%, and F-Score of 99.15%. It is largely better than traditional method for the same tasks.
Child tracking and hidden activities observation system through mobile app Mohammad Jahangir Alam; Tanjia Chowdhury; Sohrab Hossain; Shusmoy Chowdhury; Tanmoy Das
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.pp1659-1666

Abstract

The world is changing rapidly due to information technology, and all the people around the world are busy with their jobs, and business, adjusting to this race. Now, parents are giving more time at their business, office, and jobs, instead of passing the time at home, but they always get worried and scared about their children due to abuse of Information Technology and the country's law and order situation. So, parents are wanted to track and monitor their child's activities and location from anywhere to resolve their pressure. But is not possible for every parent to monitor their child physically due to many reasons. This paper presents a system that will help parents monitor their child activities from anywhere using a mobile phone to solve the problem. This android app uses global positioning system (GPS) and mobile services to find the child location and secretly stored all the call logs, hort message service (SMS) logs, contact lists, and accurate locations without knowing the children. Children assume that they are using Facebook, browsing the net or watching videos from youtube. It will not hamper any activities of the child. Parents can check all the activities of children using this app.
Studying faculty members’ readiness to use Shaqra University e-learning platform Raed Alotaibi; Abdulrahman Alghamdi
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.pp1556-1564

Abstract

In Saudi Arabia, most universities are seeking to implement e-learning to improve education access and processes. Although some universities have already implemented e-learning, most have not. Shaqra University is aiming to implement an e-learning system. Therefore, through the use of a questionnaire, this study examines faculty members’ readiness to use the e-learning platform and assesses their readiness based on gender differences and user experience. Factors considered were usage self-efficacy, self-confidence in dealing with e-learning, Attitude towards e-learning and educational needs towards e-learning. The results revealed that, based on all these factors, faculty members were ready to use the platform of e-learning. There were no differences between male and female participants in self-efficacy in using information and communications technology, self-confidence in e-learning and educational needs towards e-learning. The females’ mean score was significantly higher than the males’ mean score. Between faculty members with no experience and faculty members’ who were experienced in e-learning, user experience was significantly different for self-efficacy of using information and communications technology, self-confidence in e-learning and attitude towards e-learning. These results revealed that faculty members are ready to use a platform of e-learning and these results may help decision makers in Shaqra University to successfuly adopt an e-learning platform.
Segmentation of image based on k-means and modified subtractive clustering Simon Tongbram; Benjamin A. Shimray; Loitongbam Surajkumar Singh
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.pp1396-1403

Abstract

Image segmentation has widespread applications in medical science, for example, classification of different tissues, identification of tumors, estimation of tumor size, surgery planning, and atlas matching. Clustering is a widely implemented unsupervised technique used for image segmentation mainly because of its simplicity and fast computation. However, the quality and efficiency of clustering-based segmentation is highly depended on the initial value of the cluster centroid. In this paper, a new hybrid segmentation approach based on k-means clustering and modified subtractive clustering is proposed. K-means clustering is a very efficient and powerful algorithm but it requires initialization of cluster centroid. And, the consistency of the clustering outcomes of k-means algorithm depends on the initial selection of the cluster center. To overcome this drawback, a modified subtractive clustering algorithm based on distance relations between cluster centers and data points is proposed which finds a more accurate cluster centers compared to the conventional subtractive clustering. These cluster centroids obtained from the modified subtractive clustering are used in k-means algorithm for segmentation of the image. The proposed method is compared with other existing conventional segmentation methods by using several synthetic and real images and experimental finding validates the superiority of the proposed method.
Protecting Android based applications from malware affected through SMS messages J. Sasi Bhanu; J. K. R. Sastry; T. Chandrasekhara Reddy
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.pp1580-1589

Abstract

Users use Android-based applications for communicating through emailing, text messaging, and transmission of audio and video objects. The attackers manipulate the email, text, videos, or audio so that users' receipt of the messages causes malware through their handheld devices. A runtime routine is invoked, which causes damage to the local resources of the mobile phone. The manipulation of the messages is done using different signatures, making it difficult to recognize the same using a single approach. Multiple approaches are sometimes required to detect different signature-based incoming messages. Choosing a method that suits the signature of the incoming message is the key. Malware can also enter at the time of installing third-party apps, clicking on the links provided in the messages, installing and invoking the malware in the background. Many issues are involved in dealing with malware detecting, prevention, and curing. A comprehensive architecture is required to deal with every aspect of dealing malware. In this paper, a comprehensive architecture is presented that considers malware's issue, especially concerning malware affected through short message service (SMS) messages operated under the Android operating system. The disection of the SMS messages have been implemented and 99% accuracy has been achieved.

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