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Proceeding of the Electrical Engineering Computer Science and Informatics

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Published by Institute of Advanced Engineering and Science

ISSN : 2407439X EISSN : - DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, students, engineers and practitioners together to participate and present their latest research finding, developments and applications related to the various aspects of electrical, electronics, power electronics, instrumentation, control, computer & telecommunication engineering, signal processing, soft computing, computer science and informatics.

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Articles 649 Documents

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A Conceptual Framework of Cloud-Based Mobile-Retail Application for Textile Cyberpreneurs Nik Zulkarnaen Khidzir; Wan Safra Diyana Wan Abdul Ghani; Khairul Azhar Mat Daud
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Cloud-based m-retail application is commonly used by internet retailers and cyberpreneurs for conducting online business operations. The emergence of third-party e-commerce platforms along with incentives from Malaysian government has easily enabled the utilization of mobile marketplace app among both Malaysian sellers and customers. As m-retail has just started to gain attention in Malaysia, more works must be done to overcome the academic research limitations in terms of technological and non-technological perspectives. Meanwhile, textile and apparel products are among the most popular to be sold via the internet in addition to the growing number of related businesses. The uses of latest technology such as cloud-based mobile-retail application may help business owners to sustain for business survival. In designing a mobile applications for specific users, a thorough investigation must be performed. A conceptual framework of the apps might be helpful in providing a general overview of required elements for developing a successful mobile-retail applications. Extensive literature reviews, qualitative analysis, interviews and questionnaires have been conducted in designing and validating the proposed framework. The analysis results shows mean values from the survey are > 3.5 for the core element variables in this research. Thus, the statistical analysis validation results indicates the importance of the element as the fundamental component for the proposed framework. Therefore, this paper intends to propose a conceptual framework of cloud-based mobile-retail application specifically to be used by textile cyberpreneurs which might be helpful for related key players.

Demand Forecasting Considering Actual Peak Load Periods Using Artificial Neural Network Octavia D.P. Yuan; A. N. Afandi; Hari Putranto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Presently, electrical energy consumption continues to increase from year to year. Therefore, a short-term load forecasting is required that electricity providers can deliver continuous electrical energy to electricity consumers. By considering the estimation of the electrical load, the scheduling plan for operation and allocation of reserves can be managed well by the supply side. This study is focused on a forecasting of electrical loads using Artificial Neural Network (ANN) method considering a backpropagation algorithm model. The advantage of this method is to forecast the electrical load in accordance with patterns of past loads that have been taught. The data used for the learning is Actual Peak Load Period (APLP) data on the 150 kV system during 2017. Results show that the best network architecture is structured for the APLP Day and Night. Moreover, the momentum setting and understanding rate are 0.85 and 0.1 for the APLP Day. In contrast, 0.9 and 0.15 belong to the APLP Night. Based on the best network architecture, the APLP day testing process generates Mean Squared Error (MSE) around 0.04 and Mean Absolute Percentage Error (MAPE) around 4.66%, while the APLP Night generates MSE in 0.16 and MAPE in 16.83%.

Implementation of MEMS Accelerometer for Velocity-based Seismic Sensor Amalia Cemara Nur'aidha; Sukir Maryanto; Didik R. Santoso
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Micro Electro Mechanical System (MEMS) accelerometer is commonly used as acceleration-based vibration sensor. The MEMS accelerometer is small device, simple in the implementation design, and relatively inexpensive. But in some fields of application, due to low frequency operation and also small magnitude of the measured signal, for example in seismology, velocity-based vibration sensor is usually more desirable than acceleration-based sensor. In this research, a velocity-based vibration sensor has been developed using MEMS Accelerometer device e.g. MMA7361L. The acceleration-based vibration signal from the MMA7361L is converted into a velocity-based vibration signal by using an integrator circuit module. This module is assembled by using a band-pass filter and an integral-amplifier. The laboratory test shows that the developed sensor system could detect both low and high-frequency vibration signals in velocity-based with good result. The sensor system has a frequency range of 0.02Hz to 148Hz. It is wider frequency than the geophone (seismic sensor), thus the velocity-based MEMS sensor system has capability for geophone replacement.

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance Mohd Fua'ad Rahmat; Siti Marhainis Othman; Sahazati Md Rozali; Zulfatman Has
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

This paper presents a modified sliding mode controller (MSMC) for tracking purpose of electro-hydraulic actuator system with mismatched disturbance. The main contribution of this study is in attempting to find the optimal tuning of sliding surface parameters in the MSMC using a hybrid algorithm of particle swarm optimization (PSO) and gravitational search algorithms (GSA), in order to produce the best system performance and reduce the chattering effects. In this regard, Sum square error (SSE) has been used as the objective function of the hybrid algorithm. The performance was evaluated based on the tracking error identified between reference input and the system output. In addition, the efficiency of the designed controller was verified within a simulation environment under various values of external disturbances. Upon drawing a comparison of PSOGSA with PSO and GSA alone, it was learnt that the proposed controller MSMC, which had been integrated with PSOGSA was capable of performing more efficiently in trajectory control and was able to reduce the chattering effects of MSMC significantly compared to MSMC-PSO and MSMC-GSA, respectively when the highest external disturbance, 10500N being injected into the system's actuator.

Aspect-Based Sentiment Analysis Approach with CNN Budi M. Mulyo; Dwi H. Widyantoro
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Lots of research has been done on the domain of Sentiment Analysis, for example, research that conducted by Bing Liu's (2012) [1]. Other research conducted in a SemEval competition, the domain of sentiment analysis research has been developed further up to the aspect or commonly called Aspect Based Sentiment Analysis (ABSA) [2]. The domain problem of Aspect Based Sentiment Analysis (ABSA) from SemEval is quite diverse, all of those problems arise mostly from the real data provided. Some existing problems include Implicit, Multi-label, Out Of Vocabulary (OOV), Expression extraction, and the detection of aspects and polarities. This research only focuses on classification aspect and classification of sentiment. This study uses an existing method of Convolution Neural Network (CNN) method, which was introduced again by Alex K. The study by Alex K reduces the error rate by 15%, compared in the previous year the decrease was only 5%. This research would like to propose CNN methods that have been optimized, and use Threshold (CNN-T) to select the best data in training data. This method can produce more than one aspect using one data test. The average result of this experiment using CNN-T got better F-Measure compared to CNN and 3 classic Machine Learning method, i.e. SVM, Naive Bayes, and KNN. The overall F1 score of CNN-T is 0.71, which is greater than the other comparable methods.

Implementation of Winnowing Algorithm for Document Plagiarism Detection Nurissaidah Ulinnuha; Muhammad Thohir; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar; Ahmad Zaenal Arifin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Plagiarism prevention efforts are being evolved in various sector. Designing and developing plagiarism checker applications is the purpose of this paper. Specifically by knowing the percentage of similarity between the original document and the test document. Winnowing algorithm is used because it can detect plagiarism in documents up to sub-section of the document. In this paper using three validators consisting of computational mathematicians, software engineering experts, and users to test the feasibility of the application. Experiment using several scenarios, the result of the equation using winnowing algorithm is 90.12%.

Development of Embedded System for Centralized Insomnia System Novi Azman; Mohd Khanapi Abd Ghani; Muhammad Haikal Satria; Muhammad Zillullah Mukaram
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Insomnia is a common health problem in medical field as well as in psychiatry. The measurement of those factors could be collected by using polysomnography as one of the current standards. However, due to the routine of clinical assessment, the polysomnography is impractical and limited to be used in certain place. The rapid progress of electronic sensors to support IoT in health telemonitoring should provide the real time diagnosis of patient at home too. In this research, the development of centralized insomnia system for recording and analysis of patient with chronic-insomnia data is proposed. The system is composed from multi body sensors that connected to main IOT server. The test has been done for 5 patients and the result has been successfully retrieved in real time.

A New Algorithm for Designing the Parameter of Damped-Type Double Tuned Filter Haposan Yoga Pradika Napitupulu; Chairul Gagarin Irianto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Due to harmonics problems generated by converter devices. Currently, passive filter has been widely used in suppressing harmonics distortion. Passive filter which mostly used is double tuned filter. However, double tuned filter doesn't have a damping resistor which can prevent network elements from exposing to harsh condition such as when the system reactance and the filter impedance are conjugated, this condition can cause severe overvoltage harmonics on the filter and other power system components. There is a new configuration of double tuned filter that has damping resistor, called damped-type double tuned filter. Aiming at the question of parameter of damped-type double tuned filter, a new algorithm for designing the parameter of damped-type double tuned filter is proposed based on the relationship between impedance of two single tuned filter and one double tuned filter, and also based on the resonance at tuned frequency one and tuned frequency two are close to zero. Simulation result from MATLAB shows that the impedance of damped-type double tuned filter designed with this algorithm is appropriate. In addition, the simulation result from PSIM shows that damped-type double tuned filter designed with this algorithm works well.

ML-Optimized Beam-based Radio Coverage Processing in IEEE 802.11 WLAN Networks Mehdi Guessous; Lahbib Zenkouar
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Dynamic Radio Resource Management (RRM) is a major building block of Wireless LAN Controllers (WLC) function in WLAN networks. In a dense and frequently changing WLANs, it maximizes Wireless Devices (WD) opportunity to transmit and guarantees conformance to the design Service Level Agreement (SLA). To achieve this performance, a WLC processes and applies a network-wide optimized radio plan based on data from access points (AP) and upper-layer application services. This coverage processing requires a "realistic" modelization approach of the radio environment and a quick adaptation to frequent changes. In this paper, we build on our Beam-based approach to radio coverage modelization. We propose a new Machine Learning Regression (MLR)-based optimization and compare it to our NURBS-based solution performance, as an alternative. We show that both solutions have very comparable processing times. Nevertheless, our MLR-based solution represents a more significant prediction accuracy enhancement than its alternative.

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm Achmad Fitro; Suryono Suryono; Retno Kusumaningrum
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can't store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system.

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