Proceeding of the Electrical Engineering Computer Science and Informatics
Not a member yet
649 research outputs found
Sort by
Clustering human perception of environment impact using Rough Set Theory
Get PDFRough set is a set theory which is have been applied in the many areas. One of them is in data mining. The utilization of feature selection and clustering methods, that are a part of data mining application, could contribute for decision support. This paper investigates the application of rough set theory to select attribute and cluster environment impact. The Maximum Dependency Attribute (MDA) and fuzzy partition based on indiscernible relation are used to select the most important impact and cluster the object using the selected attributes, respectively. The data are collected from the field survey at identifying the environmental impact experienced by several communities in Yogyakarta, Indonesia. The results show that the water quality is the important attribute on physical and chemical aspects. Furthermore, on economic aspect, the highest attributes are immigration and employee absorption. Moreover, the number of cluster recommended is 9 based on the silhouette coefficient which is rising 0.9. This paper can be used to make recommendation to improve the quality of social environment
Analysis of EMG based Arm Movement Sequence using Mean and Median Frequency
Get PDFThis paper present the studies of analysis arm movement sequence which dedicated for upper limb rehabilitation after stroke. The recovery of the arm could be optimized if the rehabilitation therapy is in a right manner. Upper limb weakness after stroke is prevalent in post-stroke rehabilitation, many factors that can deficit muscle strength there are neural, muscle structure and function change after stroke. Rehabilitation process needs to start as soon as after a stroke attack, repetitive and conceptualized. On the other hand monitoring of muscle activity also need in the rehabilitation process to evaluate muscle strength, motor function and progress in the rehabilitation process. The objective of this research is to analysis arm movement sequence using the feature frequency domain. In this study deltoid, biceps and flexor carpum ulnaris (FCU) muscles will be monitored by surface electromyography (sEMG). Five healthy subjects male and female become participants in data recording. Mean frequency (MNF) and median frequency (MDF) domain are two signals processing technique used for arm movement sequence analyzing. The analysis result showed that MNF is better than MDF where MNF produced higher frequency than MDF from each segment. From the data analysis, this movement sequence design more focuses on deltoid and FCU muscles treatment. This movement sequence has five condition movements. First undemanding, second difficult, third moderate, fourth moderate and the last cool-down movements. The best movement sequence minimum has four condition movements warming up - moderate - difficult - cool-down
Demand Forecasting Considering Actual Peak Load Periods Using Artificial Neural Network
Get PDFPresently, 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%
Single-Tone Doppler Radar System for Human Respiratory Monitoring
Get PDFHuman respiration activities can be identified from the chest wall movement. In developing a non-contacting sensor for human respiration, the chest wall movement can be detected as a Doppler shift. Therefore, the Doppler radar is potential to be implemented for the non-contacting sensor previously mention. In this paper, the Single-Tone Doppler radar which operates at 10 GHz has been studied and proposed for detecting human respiration. The simulation experimental is performed for investigating the capability of the proposed method in detecting the human respiration parameter such as respiration rate and respiration amplitude. The results show that the proposed method is capable to extract the human respiration parameter
Comparison of LFC Optimization on Micro-hydro using PID, CES, and SMES based Firefly Algorithm
Get PDFMicro-hydro gets potential energy from water flow that has a certain height difference. Potential energy is strongly influenced by high water fall. Potential energy through pipes, incoming turbines converted into kinetic energy. The kinetic energy of the turbine coupled with the generator is converted into electrical energy. Some components used for micro-hydro power generation, among others; intake, settling basin, headrace, penstock, turbine, draft tube, generator, and control panel. Water flows through the pipe into the turbine house so it can rotate the turbine blades. Turbine rotation is used to rotate a generator at the micro hydro generator. The most common problem with micro-hydro generating systems is inconsistent generator rotation caused by changes in connected loads. Load changes can cause system frequency fluctuations and may cause damage to electrical equipment. Artificial Intelligence (AI) is used to obtain the right constants to obtain the best optimization. In this study compare the control method, namely; Proportional Integral Derivatives (PID), Capacitive Energy Storage (CES), and Superconducting Magnetic Energy Storage (SMES). This study also compared the method of artificial intelligence between Particle Swarm Optimization (PSO) method has been studied with the method of Firefly Algorithm (FA). Overall this study compares 11 methods, namely methods; uncontrolled, PID-PSO method, PID-FA method, CES-PSO method, CES-FA method, SMES-PSO method, SMES-FA method, PID-CES-PSO method, PID-CES-FA method, PID-SMES - PSO, and PID-SMES-FA method. The results of the simulation showed that from the 11 methods studied, it was found that the PID-CES-FA method has the smallest undershot value, ie -7.774e-03 pu, the smallest overshoot value, which is 4.482e-05 pu, and the fastest completion time is 7.11 s. These results indicate that the smallest frequency fluctuations are found in the PID-CES-FA controller. Thus it is stated that the PID-CES-FA method is the best method used in the previous method. This research will use other methods to get the best controller
Social Media and User Performance in Knowledge Sharing
Get PDFThe aimed of this study is to investigate the impact of social media utilization on the student's performances for knowledge sharing in teaching and learning progress. A research model on the basis of the Task-Technology Fit Theory and three hypotheses theory was developed for this study. Model and hypotheses then tested and validated using data obtained from a survey of respondents. The survey was conducted on students at a university in Indonesia. Of the 103 questionnaires filled out by members of the university, 75 questionnaires declared valid and used for further analysis. Data were analyzed using Partial Least Square (PLS) PLS Smart software utilizes V2. This study reveals that student performance in sharing knowledge with social media impact by technology characteristic and social media utilization
Implementation Strategy of Knowledge Management System: A Case of Air Drilling Associates
Get PDFJust as companies in the oil and gas industry, Air Drilling Associates (ADA) also feel the urgency to utilize Knowledge Management to facilitate resilience in a dynamic and competitive business environment. By the end of 2016 ADA introduces the ADA Knowledge Base, a Knowledge Management System, for employee to be utilized as a platform for sharing experiences and learning. However, up to one year since its introduction, the employee participation rate against ADA Knowledge Base is still low. A strategy is required for the implementation of a Knowledge Management System that is part of support for Knowledge Management. This study conducted by using Soft System Methodology approach and Knowledge Management theory. Respondents upper management, middle management and staff form the organization has been interviewed. The result defined three steps and sixteen activities for the company to implement the Knowledge Management System
The Utilization of Ontology to Support The Results of Association Rule Apriori
Get PDFAssociation rule is one of the data mining techniques to find associative combinations of items. There are several algorithms including Apriori, FP - Growth, and CT-Pro. One of the advantages of the Apriori algorithm is that it produces many rules. To improve its result, one of the methods is by using the semantic web technology. In this work, we propose how the hierarchical type of ontology can be utilized by the Apriori algorithm to improve the results. The Apriori with ontology implements the IR which is a parameter to determine the degree of association between combinations of items in a dataset. The series of experiments show that the proposed idea can improve the results compare to the default Apriori algorith
Improvement of Information Technology Infrastructure in Higher Education using IT Balanced Scorecard
Get PDFToday the use of Information Technology (IT) in business is a must since IT is useful to obtain competitive advantage. It can be achieved by alignment of IT and business, which is performed by developing a good IT infrastructure. Higher educational organization is one of business which requires competitive advantage to compete with their competitors. However, there are some problems encountered. These include the lack of a systemic approach to IT implementation, the lack of awareness to use IT, the lack of commitment and the leader's interest to implement IT, the weakness of technical support for IT implementation, poorly targeted staff development, lack of ownership and insufficient funds. Furthermore, an evaluation is need to determine the condition of IT infrastructure problems to deal with issues faced by a higher education organization. Balanced Scorecard is potential framework for analyzing IT infrastructure since it is one of the well-known performance measurements which embrace the important aspect in business. To do performance evaluation in the IT of higher education organization, Balance Scorecard perspective needs to be customized since IT division is more likely to serve internal rather than external parties commonly. The results of this study are expected to give an illustration of the state of IT infrastructure governance of higher education according to four perspectives in IT Balanced Scorecard. Based on this illustration, it can be identified critical recommendation to IT Infrastructure governance in higher education
Performance Analysis of Color Cascading Framework on Two Different Classifiers in Malaria Detection
Get PDFMalaria, as a dangerous disease globally, can be reduced its number of victims by finding a method of infection detection that is fast and reliable. Computer-based detection methods make it easier to identify the presence of plasmodium in blood smear images. This kind of methods is suitable for use in locations far from the availability of health experts. This study explores the use of two methods of machine learning on Cascading Color Framework, ie Backpropagation Neural Network and Support Vector Machine. Both methods were used as classifier in detecting malaria infection. From the experimental results it was found that Cascading Color Framework improved the classifier performance for both in Support Vector Machine and Backpropagation Neural Network