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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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Analysis of named-entity effect on text classification of traffic accident data using machine learning Putra, Anugrah Dwiatmaja; Girsang, Abba Suganda
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.pp1672-1678

Abstract

With the rising number of accidents in Indonesia, it is still necessary to evaluate and analyze accident data. The categorization of traffic accident data has been developed using word embedding, however additional work is needed to achieve better results. Several informative named entities are frequently sufficient to differentiate whether or not information on a traffic accident exists. Named-entities are informational characteristics that can offer details about a text. The influence of named-entities on thematic text categorization is examined in this paper. The information was collected using a Twitter social media crawl. Preprocessing is done at the beginning of the process to modify and delete useful text as well as label specified entities. On Support Vector Machine (SVM), scheme comparisons were performed for (i) Word Embedding, (ii) the number of occurrences of Named Entities, and (iii) the combination of the two is known as a Hybrid. The Hybrid scheme produced an improvement in classification accuracy of 90.27 percent when compared to Word Embedding scheme and occurrences of named entities scheme, according to tests conducted using 1.885 data consisting of 788 accident data and 1.067 non-accident data.
Flight parameters improvement for an unmanned aerial vehicle using a lookup table based fuzzy PID controller Abderrahmen Benbouali; Fayçal Chabni; Rachid Taleb; Noureddine Mansour
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.pp171-178

Abstract

In this paper, a control scheme based on lookup table fuzzy proportionalintegral-derivate (PID) controller for the quadrotor unmanned aerial vehicle (UAV) movement control is proposed. This type of control provides enhanced quadrotor movement control beyond what can be achieved with conventional controllers and has a less computational burden on the processor. The proposed control scheme uses three lookup table based fuzzy logic controllers to control the different movement ranges of a quadrotor (i.e. roll, pitch, and yaw) to achieve stability. The mathematical model of a quadrotor, used to design the proposed controller, is derived based on the Lagrange approach. The processor in the loop (PIL) technique was used to test and validate the proposed control scheme. MATLAB/Simulink environment was used as a platform for the quadrotor model, whereas a low cost and high-performance STM32F407 microcontroller was used to implement the controllers. Data transfer between the hardware and software is via serial communication converter. The control system designed based on simulation is tested and validated using “processor in the loop” techniques.
Fixed point theorem between cone metric space and quasi-cone metric space Abdullah Al-Yaari; Hamzah Sakidin; Yousif Alyousifi; Qasem Al-Tashi
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.pp540-549

Abstract

This study involves new notions of continuity of mapping between quasi-cone metrics spaces (QCMSs), cone metric spaces (CMSs), and vice versa. The relation between all notions of continuity were thoroughly studied and supported with the help of examples. In addition, these new continuities were compared with various types of continuities of mapping between two QCMSs. The continuity types are ????????-continuous, ????????-continuous, ????????-continuous, and ????????-continuous. The results demonstrated that the new notions of continuity could be generalized to the continuity of mapping between two QCMSs. It also showed a fixed point for this continuity map between a complete Hausdorff CMS and QCMS. Overall, this study supports recent research results.
Classification of Quranic topics based on imbalanced classification Bassam Sulaiman Arkok; Akram Mohammed Zeki
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp678-687

Abstract

Imbalanced classification techniques have been applied widely in the field of data mining. It is used to classify the imbalanced classes that are not equal in the number of samples. The problem of imbalanced classes is that the classification performance tends to the class with more samples while the class with few samples will obtain poor performance. This problem can be occurred in the Qur’anic classification due to the different number of verses. Many studies classified Qur’anic verses, which depended on the traditional classification. However, no study classified Qur’anic topics based on the techniques of imbalanced classification. Therefore, this paper aims to apply the methods of imbalanced classification as synthetic minority over-sampling technique (SMOTE), random over sample (ROS), and random under sample (RUS) methods to classify the Qur’anic topics that are imbalanced. Many metrics were used in this research to evaluate the experimental results. These metrics are sensitivity/recall, specificity, overall accuracy, F-Measure, G-mean, and matthews correlation coefficient (MCC). The results showed that the Quranic classification performance improved when imbalanced classification techniques were applied
Efficient TCAM design based on dual port SRAM on FPGA Triet Nguyen; Kiet Ngo; Nguyen Trinh; Bao Bui; Linh Tran; Hoang Trang
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.pp104-112

Abstract

Ternary content addressable memory (TCAM) is a memory that allows high speed searching for data. Not only it is acknowledged as associative memory/storage but also TCAM can compare input searching content (key) against a collection of accumulated data and return the matching address which compatible with this input search data. SRAM-based TCAM utilizes and allocates blocks RAM to perform application of TCAM on FPGA hardware. This paper presents a design of 480×104 bit SRAM-based TCAM on altera cyclone IV FPGA. Our design achieved lookup rate over 150 millions input search data and update speed at 75 million rules per second. The architecture is configurable, allowing various performance trade-offs to be exploited for different ruleset characteristics.
Real time face recognition of video surveillance system using haar cascade classifier Adlan Hakim Ahmad; Sharifah Saon; Abd Kadir Mahamad; Cahyo Darujati; Sri Wiwoho Mudjanarko; Supeno Mardi Susiki Nugroho; Mochamad Hariadi
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.pp1389-1399

Abstract

This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.
Algorithm fuzzy scheduling for realtime jobs on multiprocessor systems Holagundi, Nirmala; Ashwathsetty, Girijamma Hollalkere; Basthikodi, Mustafa
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.pp1308-1319

Abstract

The computing in Real-time is rapidly focusing much developments in technologies so that the real-time jobs are to be scheduled and executed on computing systems in particular time frame. The scheduling and load balancing techniques in distributed systems face numerous challenges because of lack of centralized strategy to dispatch the jobs in multiprocessors systems. In this work, we propose an Algorithm Fuzzy Scheduling (AFS) for real-time jobs that includes of Arrival time, Deadline and Computation time as the scheduling parameters of input. The approach AFS is analyzed and compared with Existing Fuzzy Algorithm (EFA) model for evaluation of performances from the outcome of the simulation. The jobs are scheduled on multiprocessor at higher system load by making use of fuzzy mechanisms in the algorithms. The experimental results prove that the proposed AFS achieves a better performance comparatively to EFA at various system load factors with respect to mean turnaroundtime, mean response time and count of missed deadlines. This is the initial phase of the algorithm, that will be enhanced to consider a greater number of parameters to be associated with jobs for better decision making and to investigate the scope for algorithm level parallelism.
Optimising monthly tilt angles of solar panels using particle swarm optimisation algorithm Namruta S. Kanianthara; Swee Peng Ang; Ashraf Fathi Khalil Sulayman; Zainidi bin Hj. Abd. Hamid
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.pp75-89

Abstract

This paper presents an intelligent computational method using the PSO (particle swarm optimisation) algorithm to determine the optimum tilt angle of solar panels in PV systems. The objective of the paper is to assess the performance of this method against conventional methods of determining the optimum tilt angle. The method presented here can be used to determine the optimum tilt angle at any location around the world. In this paper, it was applied to Brunei Darussalam, and succeeded in computing monthly optimum tilt angles, ranging from 34.7ᵒ in December to -26.7ᵒ in September. Results showed that changing the tilt angle every month, as determined by the PSO algorithm, increased annual yield by: (i) 5.94%, compared to keeping it fixed at 0ᵒ, (ii) 8.65%, compared to Lunde’s method and (iii) 17.31%, compared to Duffie and Beckman’s method. Benchmark test functions were used to compare and evaluate the performance of the PSO algorithm with the artificial bee colony (ABC) algorithm, another metaheuristic algorithm. The tests revealed that the PSO algorithm outperformed the ABC algorithm, exhibiting lower root mean square error and standard deviation, better convergence to the global minimum, more accurate location of the global minimum, and faster execution times.
Analysis of active islanding detection techniques for grid-connected inverters systems Ikken, Naima; Tariba, Nour-Eddine; Bouknadel, Abdelhadi; Haddou, Ahmed; Omari, Hafsa El; Omari, Hamid El
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.pp1287-1296

Abstract

An island is a section of the electrical grid that contains producing assets and loads that are separated from the main grid and powered by these generators, such as solar systems, with voltage and frequency maintained at nominal levels. It's worth noting that the concept of islanding is linked to time. When the inverter detects an isolated grid activity for a particular period of time, the inverter is compelled to decouple from the general grid, according to the criteria that dictate the working principle of a photovoltaic (PV) systemThis paper presents research and comparisons of the main islanding detection techniques for single-phase systems based on various structures, as well as a comparison of the improvement of the traditional islanding detection method using three different methods (active frequency drift (AFD), slip mode phase shift (SMS) and Sandia frequency shift (SFS)). Under normal and abnormal operating conditions, a comparison of these three examined improvements was made. Additionally, physical security information management (PSIM) software simulation results are generated to test the performance and effectiveness of the effective technique plan.
Data communication for drone-enabled internet of things Yousra Abdul Alsahib S. Aldeen; Haider Mohammed Abdulhadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp1216-1222

Abstract

Internet of things (IoT) is one of the prominent emerged technology of interconnected devices for people convenient and smart services. Recent advancement in this area caused various new challenges especially deployment of infrastructure. In order to fulfill the network requirements, the dynamic and dedicated drone networks have designed as a cost effective and flexible solution. The technologies of IoT and drone are emerged to collect, forward the data for further process. Data communication among drones and IoT infrastructure is new area of research where various different existing protocol are used. However, still this area need attention due to mobility of drones, obstacles and interferences in these networks. This paper proposes a Drone enabled Data Communication for Internet of Things (DDC-IoT) as a data communication solution for IoT networks, data collection centers and drones. The proposed data commination solution is tested in simulation to analyze its performance especially for real time critical applications in terms of data throughput and data delay.

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