Proceeding of the Electrical Engineering Computer Science and Informatics
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.
Articles
649 Documents
<![CDATA[FVEC feature and Machine Learning Approach for Indonesian Opinion Mining on YouTube Comments ]]>
<![CDATA[Aina Musdholifah]]>;
<![CDATA[Ekki Rinaldi]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (646.057 KB)
|
DOI: 10.11591/eecsi.v5.1726
<![CDATA[Mining opinions from Indonesian comments from YouTube videos are required to extract interesting patterns and valuable information from consumer feedback. Opinions can consist of a combination of sentiments and topics from comments. The features considered in the mining of opinion become one of the important keys to getting a quality opinion. This paper proposes to utilize FVEC and TF-IDF features to represent the comments. In addition, two popular machine learning approaches in the field of opinion mining, i.e., SVM and CNN, are explored separately to extract opinions in Indonesian comments of YouTube videos. The experimental results show that the use of FVEC features on SVM and CNN achieves a very significant effect on the quality of opinions obtained, in term of accuracy.]]>
<![CDATA[Clustering human perception of environment impact using Rough Set Theory ]]>
<![CDATA[Ani Apriani]]>;
<![CDATA[Iwan Riyadi Yanto]]>;
<![CDATA[Septiana Fathurrohmah]]>;
<![CDATA[Sri Haryatmi]]>;
<![CDATA[D Danardono]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (268.63 KB)
|
DOI: 10.11591/eecsi.v5.1727
<![CDATA[Rough 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.]]>
<![CDATA[E-Government Service Evaluation of Batu City Health Dept.using e-Govqual Approach and IPA Analysis ]]>
<![CDATA[Evi Wahyuni EDW]]>;
<![CDATA[Dharma Pradana]]>;
<![CDATA[Yasina Karina]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (276.524 KB)
|
DOI: 10.11591/eecsi.v5.1728
<![CDATA[E-Government is an application of government information system technology to support public service system and dissemination of information from government to society that used in every element of government. Batu City Health Office website (http://dinkes.batukota.go.id) is part of Batu City Government e-Government system that was built to support publication of government information to the public. According to observations, there was a decline in visitors from the number 150 visitors in October 2017 to 50 visitors in November 2017. While in December 2017 stable at the number 50 visitors. Based on the anomaly incident, there needs to be an evaluation of e-Government in Batu City Health Office by doing the assessment of website service quality from the user side. This evaluation uses e-Govqual and Heuristic Evaluation methods. Assessment of e-govqual attributes on performance values and interests in the IPA quadrant resulted in the conclusion that there are 24 attributes in A and C quadrants in the IPA quadrant that need to improve attribute quality. Suggestions based on quadrant A and C in the form of recommendation improvement in the form of recommendation mockup based on 10 principles of heuristic evaluation]]>
<![CDATA[Implementation of Obfuscation Technique on PHP Source Code ]]>
<![CDATA[Maskur Maskur]]>;
<![CDATA[Zamah Sari]]>;
<![CDATA[Ahmad Miftakh]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (449.924 KB)
|
DOI: 10.11591/eecsi.v5.1729
<![CDATA[Source code on web based applications can be altered easily. This occurred because the source code is not compiled into an executable file. Hence, it can be read and copied easily, or be changed without permission from the author. Obfuscation is a technique that commonly used to secure the source code in any websites based application. Obfuscation is a technique to randomize the source code that make the code harder to read but still runnable, but this make the running time increased and the application will run slower then it supposed to. This increased time caused by reverse obfuscation proses to bring back the source code into originally form before interpreted by web server. This studi intended to create an obfuscation technique that keeping the application run time performance as not obfuscated called Wanna Crypt. The methods to create this applications are (1) system design using UML, (2) implementation of the system, which is done by coding or writing scripts using PHP, HTML, JavaScript, CSS to build Wanna Crypt based website, (3) Blackbox and Whitebox testing to compare the execution time. From the tests, it can be concluded that web applications using Wanna Crypt provide a longer response time than web applications without using obfuscation.]]>
<![CDATA[Classification of Motor Imagery and Synchronization of Post-Stroke Patient EEG Signal ]]>
<![CDATA[Arifah Ummul Fadiyah]]>;
<![CDATA[Esmeralda C. Djamal]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eecsi.v6.1935
<![CDATA[Stroke attacks often cause disability, so the need for rehabilitation to restore patient's motor skills. Electroencephalogram (EEG) is an instrument that can capture electrical activity in the brain. Some post-stroke patients have brain electrical dysfunction so that EEG signal can achieve such as amplitude decrease, and wave differences from symmetric channels. However, EEG signal analysis is not easy because it has high complexity and small amplitude. However, information from EEG signals is beneficial, including for stroke identification. This study proposes the identification of EEG signals from post-stroke patients using wavelet extraction and Backpropagation Levernberg-Marquardt. EEG signals are recorded, extracted imagery motor variables, and synchronization of symmetric channels. The results of the study provide that the accuracy for identifying post-stroke EEG signals is 100% for training data and 79.69 % for new data. Research also shows that the use of learning rates affects accuracy. The smaller the learning rate provided accuracy is better. However, it had consequences for computing time so that the optimal learning rate is 0.0001.]]>
<![CDATA[Early Detection Application of Bipolar Disorders Using Backpropagation Algorithm ]]>
<![CDATA[Desti Fitriati]]>;
<![CDATA[Febri Maspiyanti]]>;
<![CDATA[Fairuz Astari Devianty]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eecsi.v6.1936
<![CDATA[Mental health is an important aspect in realizing overall health and important to be considered as physical health. Mental disorders are classified as difficult to diagnose due to the similarity of symptoms that can occur. In addition, information about mental disorders is inadequate so that it can be difficult for experts to provide a diagnosis of the disorders experienced by patients. The difficulty of experts in diagnosing is usually caused by the similarity of symptoms in mental disorders, such as in schizophrenia and bipolar disorder. Based on these problems, this research would like to conduct an early detection study of bipolar disorder by using screening questionnaire data from 300 respondents and serve as a knowledge base to be processed using the backpropagation algorithm. Based on all the results of testing the backpropagation algorithm that has been done to find out the results obtained accuracy and the highest results of training, the highest results obtained with the total test data correct or suitable is 249 and the wrong data is 1 of 250 test data. If it is calculated by a formula, the resulting accuracy rate is 99.6%. And it can be concluded broadly that the greatest influence of the accuracy of the backpropagation algorithm is based on momentum. Because in testing momentum the highest accuracy can be produced compared to the results of other analyzes.]]>
<![CDATA[The Kinematics and Dynamics Motion Analysis of a Spherical Robot ]]>
<![CDATA[Tresna Dewi]]>;
<![CDATA[Pola Risma]]>;
<![CDATA[Yurni Oktarina]]>;
<![CDATA[Lin Prasetyani]]>;
<![CDATA[Zarqa Mulya]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eecsi.v6.1937
<![CDATA[Mobile robot application has reach more aspect of life in industry and domestic. One of the mobile robot types is a spherical robot whose components are shielded inside a rigid cell. The spherical robot is an interesting type of robot that combined the concept of a mobile robot and inverted pendulum for inner mechanism. This combination adds to more complex controllerdesignthantheothertypeofmobilerobots.Asidefrom these challenges, the application of a spherical robot is extensive, from being a simple toy, to become an industrial surveillance robot. This paper discusses the mathematical analysis of the kinematics and dynamics motion analysis of a spherical robot. The analysis combines mobile robot and pendulum modeling as the robot motion generated by a pendulum mechanism. This paper is expected to give a complete discussion of the kinematics and dynamics motion analysis of a spherical robot.]]>
<![CDATA[The Improved Artificial Neural Network Based on Cosine Similarity in Facial Emotion Recognition ]]>
<![CDATA[Kartika Candra Kirana]]>;
<![CDATA[Slamet Wibawanto]]>;
<![CDATA[Nur Hidayah]]>;
<![CDATA[Gigih Prasetyo Cahyono]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eecsi.v6.1938
<![CDATA[In this study, we present the improved artificial neural network based on cosine similarity in facial emotion recognition. We apply a shifting window that employs neural network for two concurrent processes consisting of face detection and emotional recognition. In order to prevent the slow and futile computations, non-face areas need to be filtered from neurons on each network layer, thus we propose the improved artificial neural network based on cosine similarity. Cosine similarity is employed to bypass the process of non-face areas in neural network. The accuracy of the proposed method reaches 0.84, while the accuracy of the original neural network method reaches 0.74. It can be concluded that our methods work accurately.proposed method is superior to the state-of-the-art algorithms.]]>
<![CDATA[Emotion and Attention of Neuromarketing Using Wavelet and Recurrent Neural Networks ]]>
<![CDATA[Muhammad Fauzan Ar Rasyid]]>;
<![CDATA[Esmeralda C. Djamal]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eecsi.v6.1939
<![CDATA[One method concerning evaluating video ads is neuromarketing. This information comes from the viewer's mind, thus minimizing subjectivity. Besides, neuromarketing can overcome the difficulties of respondents who sometimes do not know the response to the video ads they watch. Neuromarketing is based on neuropsychology, which is sourced from the human brain through electrical activity signals recorded by Electroencephalogram. Usually, Neuropsychology consists of emotions, attention, and concentration. This research proposed the Wavelet method and Recurrent Neural Networks to measure the emotional and attention variable of neuropsychology in real-time every two seconds while watching video ads. The results showed that Wavelet and Recurrent Neural Networks could provide training data accuracy of 100% and 89.73% for new data. The experiment also gave that the RMSprop optimization model for the weight correction contributed to higher correctness of 1.34% than the Adam model. Meanwhile, using Wavelet for extraction can increase accuracy by 4%.]]>
<![CDATA[An SoC-Based System for Real-time Contactless Measurement of Human Vital Signs and Soft Biometrics ]]>
<![CDATA[Aminuddin Rizal]]>;
<![CDATA[Kuan-Ting Chiang]]>;
<![CDATA[Jia-Wei Lin]]>;
<![CDATA[Yuan-Hsiang Lin]]>
<![CDATA[ Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019 ]]>
Publisher : <![CDATA[IAES Indonesia Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/eecsi.v6.1940
<![CDATA[Computer vision (CV) plays big role in our current society's life style. The advancement of CV technology brings the capability to sense human vital sign and soft biometric parameters in contactless way. In this work, we design and implement the contactless human vital sign parameters measurement including pulse rate (PR) and respiration rate (RR) and also for assessment of human soft biometric parameters i.e. age, gender, skin color type, and body height. Our designed system is based on system on chip (SoC) device which run both FPGA and hard processor while provides real-time operation and small form factor. Experimental results shows our device performance has mean absolute error (MAE) 2.85 and 1.46 bpm for PR and RR respectively compared to clinical apparatus. While, for soft biometric parameters measurement we got unsatisfied results on age and gender estimation with accuracy of 58% and 74% respectively. However, for skin color type and body height measurement we reach high accuracy with 98 % and 2.28 cm respectively on both parameters.]]>
