Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

Bulletin of Electrical Engineering and Informatics

EEI
Website

Published by Universitas Ahmad Dahlan

ISSN : - EISSN : - DOI : -

Core Subject : Engineering,

Electrical & Electronics Engineering

Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.

Arjuna Subject : -

Articles 2,901 Documents

68 69 70 71 72

Flying object tracking and classification of military versus nonmilitary aircraft Ehsan Akbari Sekehravani; Eduard Babulak; Mehdi Masoodi
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Tracking of moving objects in a sequence of images is one of the important and functional branches of machine vision technology. Detection and tracking of a flying object with unknown features are important issues in detecting and tracking objects. This paper consists of two basic parts. The first part involves tracking multiple flying objects. At first, flying objects are detected and tracked, using the particle filter algorithm. The second part is to classify tracked objects (military or nonmilitary), based on four criteria; Size (center of mass) of objects, object speed vector, the direction of motion of objects, and thermal imagery identifies the type of tracked flying objects. To demonstrate the efficiency and the strength of the algorithm and the above system, several scenarios in different videos have been investigated that include challenges such as the number of objects (aircraft), different paths, the diverse directions of motion, different speeds and various objects. One of the most important challenges is the speed of processing and the angle of imaging.

Implementing canny edge detection algorithm for noisy image Ehsan Akbari Sekehravani; Eduard Babulak; Mehdi Masoodi
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Edge detection is a significant stage in different image processing operations like pattern recognition, feature extraction, and computer vision. Although the Canny edge detection algorithm exhibits high precision is computationally more complex contrasted to other edge detection methods. Due to the traditional Canny algorithm uses the Gaussian filter, which gives the edge detail represents blurry also its effect in filtering salt-and-pepper noise is not good. In order to resolve this problem, we utilized the median filter to maintain the details of the image and eliminate the noise. This paper presents implementing and enhance the accuracy of Canny edge detection for noisy images. Results present that this proposed method can definitely overcome noise disorders, preserve the edge useful data, and likewise enhance the edge detection precision.

A real-time big data sentiment analysis for iraqi tweets using spark streaming Nashwan Dheyaa Zaki; Nada Yousif Hashim; Yasmin Makki Mohialden; Mostafa Abdulghafoor Mohammed; Tole Sutikno; Ahmed Hussein Ali
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

The scale of data streaming in social networks, such as Twitter, is increasing exponentially. Twitter is one of the most important and suitable big data sources for machine learning research in terms of analysis, prediction, extract knowledge, and opinions. People use Twitter platform daily to express their opinion which is a fundamental fact that influence their behaviors. In recent years, the flow of Iraqi dialect has been increased, especially on the Twitter platform. Sentiment analysis for different dialects and opinion mining has become a hot topic in data science researches. In this paper, we will attempt to develop a real-time analytic model for sentiment analysis and opinion mining to Iraqi tweets using spark streaming, also create a dataset for researcher in this field. The Twitter handle Bassam AlRawi is the case study here. The new method is more suitable in the current day machine learning applications and fast online prediction.

Autonomous system to control a mobile robot Ayman Abu Baker; Yazeed Yasin Ghadi
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents an ongoing effort to control a mobile robot in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this paper, the fuzzy controller is used to tackle the problem of mobile robot autonomous navigation in unstructured environment. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the fuzzified, adaptive inference engine and defuzzification engine. Also number of linguistic labels is optimized for the input of the mobile robot in order to reduce computational time for real-time applications. The proposed fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.

A comparative study of wavelet families for electromyography signal classification based on discrete wavelet transform Abdelouahad Achmamad; Atman Jbari
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Automatic detection of neuromuscular disorders performed using electromyography (EMG) has become an interesting domain for many researchers. In this paper, we present an approach to evaluate and classify the non-stationary EMG signals based on discrete wavelet transform (DWT). Most often researches did not consider the effect of DWT factors on the performance of EMG signals classification. This problem is still an interesting unsolved challenge. However, the selection of appropriate mother wavelet and related level decomposition is an essential issue that should be addressed in DWT-based EMG signals classification. The proposed method consists of decomposing a raw EMG signal into different sub-bands. Several statistical features were extracted from each sub-band and six wavelet families were investigated. The feature vector was used as inputs to support vector machine (SVM) classifier for the diagnosis of neuromuscular disorders. The obtained results achieve satisfactory performances with optimal DWT factors using 10-fold cross-validation. From the classification performances, it was found that sym14 is the most suitable mother wavelet at the 8th optimal wavelet level of decomposition. These simulation results demonstrated that the proposed method is very reliable for reducing cost computational time of automated neuromuscular disorders system and removing the redundancy information.

Batik pattern recognition using convolutional neural network Mohammad Arif Rasyidi; Taufiqotul Bariyah
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Batik is one of Indonesia's cultures that is well-known worldwide. Batik is a fabric that is painted using canting and liquid wax so that it forms patterns of high artistic value. In this study, we applied the convolutional neural network (CNN) to identify six batik patterns, namely Banji, Ceplok, Kawung, Mega Mendung, Parang, and Sekar Jagad. 994 images from the 6 categories were collected and then divided into training and test data with a ratio of 8:2. Image augmentation was also done to provide variations in training data as well as to prevent overfitting. Experimental results on the test data showed that CNN produced an excellent performance as indicated by accuracy of 94% and top-2 accuracy of 99% which was obtained using the DenseNet network architecture.

Diabetes prediction based on discrete and continuous mean amplitude of glycemic excursions using machine learning Lailis Syafaah; Setio Basuki; Fauzi Dwi Setiawan Sumadi; Amrul Faruq; Mauridhi Hery Purnomo
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2387

Chronic hyperglycemia and acute glucose fluctuations are the two main factors that trigger complications in diabetes mellitus (DM). Continuous and sustainable observation of these factors is significant to be done to reduce the potential of cardiovascular problems in the future by minimizing the occurrence of glycemic variability (GV). At present, observations on GV are based on the mean amplitude of glycemic excursion (MAGE), which is measured based on continuous blood glucose data from patients using particular devices. This study aims to calculate the value of MAGE based on discrete blood glucose observations from 43 volunteer patients to predict the diabetes status of patients. Experiments were carried out by calculating MAGE values from original discrete data and continuous data obtained using Spline Interpolation. This study utilizes the machine learning algorithm, especially k-Nearest Neighbor with dynamic time wrapping (DTW) to measure the distance between time series data. From the classification test, discrete data and continuous data from the interpolation results show precisely the same accuracy value that is equal to 92.85%. Furthermore, there are variations in the MAGE value for each patient where the diabetes class has the most significant difference, followed by the pre-diabetes class, and the typical class.

Fruit sorting robot based on color and size for an agricultural product packaging system Tresna Dewi; Pola Risma; Yurni Oktarina
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Indonesia's location in the equator gives an ideal condition for agriculture. However, agriculture suffers the issue of old farming due to a lack of youth interest working in this sector. This problem can be overcome by applying digital farming methods, in which one of them is by employing robots. Robotics technology is suitable for handling the harvested product, such as a sorting robot. This paper presents the application of a 4DOF fruit sorting robot based on color and size in a packaging system. The sorting is made possible by image processing where color is recognized by HSV analysis, and the diameter is known in the grayscale image and setting the thresholding. The fruit to be sorted is red and green tomatoes and red and green grapes. The experiments were conducted to show the effectiveness of the proposed method. The time requires for the robot to accomplish the task is 11.91s for red tomatoes, 11.76s for green tomatoes, 12.56s for red grapes, and 12.92s for green grapes. The time difference is due to the position of the boxes for the sorted fruit. The experimental results show that the arm robot manipulator is applicable for a sorting robot using the proposed method.

Advantages and recent advances of smart energy grid Mohammed Qasim Taha
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Smart grid is widely recognized technology used to improve the stability and losses of the electric power system. It is encouraging reliability, efficiency, and effective control of the supply of electrical energy. However, it is a hot topic for recent publications and still has a limited understanding among researchers. This review work is to provide insight and support to the beginner researchers since this topic needs a multidisciplinary background knowledge. The conventional electric transmission system and distribution networks struggle to provide resilient performance and reliable service and real-time data. Also, smart grid id a promising network maneuver to stabilize the system once any disturbances break out by using the distributed renewable energy generators, while the conventional networks lack for flexibility to integrate with renewable energy generators or microgrids. This comprehensive work is conducted to map previous controbution in a coherent manar, including the specifications, features, and fundamentals that are presented to benefit the interested readers interested in smart grid development.

Road surface classification based on LBP and GLCM features using kNN classifier Arthur Ahmad Fauzi; Fitri Utaminingrum; Fatwa Ramdani
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Autonomous Ground Vehicle (UGV) technology has shown a fast development this past year and proven to be useful. The use of UGV technology is restricted on a particular road condition. Classification of the road is an essential process in UGV, especially to control the autonomous vehicle. For example, the speed could be adjusted by referring to the road type, these process require a fast computational time. This research focuses on finding the most discriminant feature while keeping the number of features into a minimum to obtain fast computational time and accurate classification result. One can experiences difficulties because the condition of the road varies, this research proposes a combination of Gray Level Co-occurrence Matrix (GLCM) a statistical method to extract feature and Local Binary Pattern (LBP) feature to improve the robustness of the features. The kNN classifier is used to do the classification with the accuracy of 98% and 12 picture processed per second.

Page 70 of 291 | Total Record : 2901

68 69 70 71 72

Filter by Year

2012 2025

Filter By Issues

All Issue Vol 14, No 6: December 2025 Vol 14, No 5: October 2025 Vol 14, No 4: August 2025 Vol 14, No 3: June 2025 Vol 14, No 2: April 2025 Vol 14, No 1: February 2025 Vol 13, No 6: December 2024 Vol 13, No 5: October 2024 Vol 13, No 4: August 2024 Vol 13, No 3: June 2024 Vol 13, No 2: April 2024 Vol 13, No 1: February 2024 Vol 12, No 6: December 2023 Vol 12, No 5: October 2023 Vol 12, No 4: August 2023 Vol 12, No 3: June 2023 Vol 12, No 2: April 2023 Vol 12, No 1: February 2023 Vol 11, No 6: December 2022 Vol 11, No 5: October 2022 Vol 11, No 4: August 2022 Vol 11, No 3: June 2022 Vol 11, No 2: April 2022 Vol 11, No 1: February 2022 Vol 10, No 6: December 2021 Vol 10, No 5: October 2021 Vol 10, No 4: August 2021 Vol 10, No 3: June 2021 Vol 10, No 2: April 2021 Vol 10, No 1: February 2021 Vol 9, No 6: December 2020 Vol 9, No 5: October 2020 Vol 9, No 4: August 2020 Vol 9, No 3: June 2020 Vol 9, No 2: April 2020 Vol 9, No 1: February 2020 Vol 8, No 4: December 2019 Vol 8, No 3: September 2019 Vol 8, No 2: June 2019 Vol 8, No 1: March 2019 Vol 7, No 4: December 2018 Vol 7, No 3: September 2018 Vol 7, No 2: June 2018 Vol 7, No 1: March 2018 Vol 6, No 4: December 2017 Vol 6, No 3: September 2017 Vol 6, No 2: June 2017 Vol 6, No 1: March 2017 Vol 5, No 4: December 2016 Vol 5, No 3: September 2016 Vol 5, No 2: June 2016 Vol 5, No 1: March 2016 Vol 4, No 4: December 2015 Vol 4, No 3: September 2015 Vol 4, No 2: June 2015 Vol 4, No 1: March 2015 Vol 3, No 4: December 2014 Vol 3, No 3: September 2014 Vol 3, No 2: June 2014 Vol 3, No 1: March 2014 Vol 2, No 4: December 2013 Vol 2, No 3: September 2013 Vol 2, No 2: June 2013 Vol 2, No 1: March 2013 Vol 1, No 4: December 2012 Vol 1, No 3: September 2012 Vol 1, No 2: June 2012 Vol 1, No 1: March 2012 List of Accepted Papers (with minor revisions) More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name -

Contact Email -

Phone -

Journal Mail Official -

Editorial Address -

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA