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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 : -

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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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Ontology-Based Sentence Extraction for Answering Why-Question A. A. I. N. Eka Karyawati; Edi Winarko; Azhari Azhari; Agus Harjoko
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Most studies on why-question answering system usually used the keyword-based approaches. They rarely involved domain ontology in capturing the semantic of the document contents, especially in detecting the presence of the causal relations. Consequently, the word mismatch problem usually occurs and the system often retrieves not relevant answers. For solving this problem, we propose an answer extraction method by involving the semantic similarity measure, with selective causality detection. The selective causality detection is applied because not all sentences belonging to an answer contain causality. Moreover, the motivation of the use of semantic similarity measure in scoring function is to get more moderate results about the presence of the semantic annotations in a sentence, instead of 0/1. The semantic similarity measure employed is based on the shortest path and the maximum depth of the ontology graph. The evaluation is conducted by comparing the proposed method against the comparable ontology-based methods, i.e., the sentence extraction with Monge-Elkan with 0/1 internal similarity function. The proposed method shows the improvements in term of MRR (16%, 0.79-0.68), P@1 (15%, 0.76-0.66), P@5 (14%, 0.8-0.7), and Recall (19%, 0.86-0.72).

Text Modeling in Adaptive Educational Chat Room Based on Madamira Tool Jehad A. H. Hammad; Mochamad Hariadi; Mauridhi Hery Purnomo
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

his paper discusses how to enhance the ability of text modeling in Arabic during chat sessions. Hanini and Jabari et al. modeled the text in chat sessions, but there is still a problem when using Arabic , because the Arabic language is very difficult to comprehend, has complex derivative and many ambiguities. This paper enhanced the previous study and added MADAMIRA tool to analyze the Arabic text. Monitoring and modeling has been completed through the text modeling process by evaluating the student expressions within the chat session using MADAMIRA tool and machine learning. MADAMIRA tool enables the modeling process to categorize Arabic text into different categories, which makes it easier to use the levels of the used expressions and discover the importance of the chat session between two peers. The process of the student modeling using MADAMIRA and Machine learning will update the student model which gathers information about the student achievements within the AVCM.

Design of Automatic Switching Bio-Impedance Analysis (BIA) for Body Fat Measurement Munawar A Riyadi; Achmad Ngaqib Muthouwali; Teguh Prakoso
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Bioelectrical impedance analysis (BIA) is one method of measuring body fat levels by distinguishing the fat mass and non-fat mass based on body composition assessment. This research designs a system to measure the body fat percentage by BIA method. The system is capable of measuring BIA with automatic switching between four different electrode schemes, i.e cross-sectional, hand-to-hand, hand-to-foot, and foot-to-foot. Two electrodes are to conduct current into the body, while other two electrodes are utilized to measure the voltage from the body. The alternating current is injected with frequency of 50 kHz. Automatic switch in the form of multiplexers and demultiplexers controls the sequence of BIA measurement methods. Microcontroller process the data and the result is displayed on LCD. A keypad is used to input related body parameters, i.e height, weight, age, and gender. The measurement tests shows that the BIA works as intended, while the comparison with commercial BIA reveals maximum relative error of 4.6 % and the highest standard deviation of 2.2%.

Precise Wide Baseline Stereo Image Matching for Compact Digital Cameras Martinus Edwin Tjahjadi; Fourry Handoko
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Numerous image matching methods for wide range of applications have been invented in the last decade. When high precision and reliability of the object space point coordinates is highly demanding, a stereo image matching method which can produce conjugate point of images and a standard deviation of the matched point is examined. In this approach, image gradients are used locally to seek a conjugate patch. The normalized cross correlation is first utilized to estimate an approximate location of the conjugate patch between two normalized images. Then the location of conjugate patch is further refined by using Gaussian-Newton least squares image matching. Both radiometric and geometric parameters of least squares models are used selectively in seeking the best possible accuracy. Iterative computation is conducted to incrementally refine the geometric location of the conjugate point. After a matched patch has been found, a variant-covariant matrix of the parameter is analyzed to inform the precision of the conjugate points both on images and object space. This method can compute high precision object space points and some examples demonstrate the insight of the approach.

Compressed Natural Gas (CNG) Technology for Fuel Power Plants Isworo Pujotomo; Retno Aita Diantari
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Gas has great potential to be converted into electrical energy. Indonesia has natural gas reserves up to 50 years in the future, but the optimization of the gas to be converted into electricity is low and unable to compete with coal. Gas is converted into electricity has low electrical efficiency (25%), and the raw materials are more expensive than coal. Steam from a lot of wasted gas turbine, thus the need for utilizing exhaust gas results from gas turbine units. Combined cycle technology (Gas and Steam Power Plant) be a solution to improve the efficiency of electricity. Among other Thermal Units, Steam Power Plant (Combined Cycle Power Plant) has a high electrical efficiency (45%). Weakness of the current Gas and Steam Power Plant peak burden still using fuel oil. Compressed Natural Gas (CNG) Technology may be used to accommodate the gas with little land use. CNG gas stored in the circumstances of great pressure up to 250 bar, in contrast to gas directly converted into electricity in a power plant only 27 bar pressure. Stored in CNG gas used as a fuel to replace loadbearing peak. Lawyer System on CNG conversion as well as the power plant is generally only used compressed gas with greater pressure and a bit of land.

Neural Network on Mortality Prediction for the Patient Admitted with ADHF (Acute Decompensated Heart Failure) M. Haider Abu Yazid; Shukor Talib; Muhammad Haikal Satria; Azmee Abd Ghazi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Patient admitted with acute decompensated heart failure (ADHF) facing with high risk of mortality where 30 day mortality rates are reaching 10%. Identifying patient with high and low risk of mortality could improve clinical outcomes and hospital resources allocation. This paper proposed the use of artificial neural network to predict mortality for the patient admitted with ADHF. Results show that artificial neural network can predict mortality for ADHF patient with good prediction accuracy of 94.73% accuracy for training dataset and 91.65% for test dataset.

Robust and Imperceptible Image Watermarking by DC Coefficients Using Singular Value Decomposition Christy Atika Sari; Eko Hari Rachmawanto; De Rosal Ignatius Moses Setiadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Main problem frequently encountered in all schemes transform domain watermarking technique is the robustness and imperceptibility. Due to achieved optimal result most algorithms of image watermarking using combination two or more transformation domain. This paper proposed Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) to embed binary watermark to color Image. Before the message embedded in the color images, we converting RGB to YCbCr color space. Luminance component will be split into sub- block and it has been transformed by DCT to produce DC and AC coefficients. DC coefficients selected as embedding place because it is perceptually usefulness and robust against various attacks. DC coefficients will be collected from every sub-block to create a reference image. Then apply SVD on reference image and embed message in singular values. Various attacks have been implemented and tested due to achieve robustness using Normalized Cross Correlation (NCC) and imperceptibility tested using Peak Signal to Noise Ratio (PSNR). High values of the measurement results show the feasibility of the proposed method. A highest PSNR value resulted 42.3009 dB, whereas a highest NCC values 0.9993 after JPEG Compression.

Evaluation Study of Waste Materials for Renewable Energy through 3R Model in Bogor City Didik Notosudjono; Dede Suhendi; Engkos Engkos; Bagus Dwi Ramadhon
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Waste is one the critical issues in Indonesia which can pose a badly influence both to human’s health and nature preservation if it is not properly managed for productive use. Hence, the increasing production in municipal waste is directly proportional to the increasing number of population, in which raises the waste production in big cities in Indonesia, such as in Bogor. In Bogor, a waste processing facility (TPS) using biogas for renewable energy has been developed. The volume of wastes in Bogor at the year of 2016 has reached 2.734,03 m³ per day. There are 12 locations for waste processing facility with the TPS 3R (Reduce, Re-use and Recycle) model but there are only 3 locations that uses biogas for Renewable Energy. 3 of these biogas-based waste processing facilities can be found in the region of Taruna, Ceremai, and Dharmais. The wastes' capacity of each regions (Taruna, Ceremai, and Dharmais) consecutively is 3.300 kg,2.400 kg, and 2.520 kg with the number of organic materials that are being processed into biogas for renewable energy is 85 kg, 85 kg, and 55 kg.

Measurement of Maximum Value of Dental Radiograph to Predict the Bone Mineral Density Sri Lestari; Mohammad Diqi; Rini Widyaningrum
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Post-menopausal woman has a high risk to have osteoporosis. The condition of osteoporosis is characterized by the bone mineral density. The gold standard of BMD examination is using DEXA scan, but it has a problem in high cost and limited availability. So the study about the alternative to overcome the problem is necessary. The objective of this study is to measure the maximum value of periapical radiograph and determine its ability to be a predictor for bone mineral density of lumbar spine and hip.Image processing method was applied to 37 data subject that involved periapical radiograph and DEXA scan. The grayscale image was converted into binary image to observe the connectivity of the pixels. Measurement of maximum value for each radiograph has been done and continued by linier regression method between the maximum value with the BMD of lumbar spine and hip.The result of this study showed that the maximum value has a weak correlation with the BMD of lumbar spine and hip. The maximum value also cannot be the predictor for BMD of lumbar spine and hip as the significant of F is larger than 0,05 in the linier regression test.

Region of Interest Detection for Pregnancy Image Processing M. Khairudin; Joko Laras B T; Dessy Irmawati
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

This study discussed on a comparison of three cropping techniques for region of interest (ROI) detection of ultrasonography (USG) image. Ultrasound images are used to provide information about fetal development in the womb. The image generated by the two-dimensional ultrasound has not been able to provide complete information. Therefore, in order get the form of fetus on ultrasound image can be clearly identified with the necessary process of image analysis that can detect the boundaries of objects ROI, so that it can differentiate between one object with another object on the ultrasound image. Comparison results between the ROI detection with cropping methods namely rectanguler, circle and ellipse shapes are expected obtaining the best technique. It can be used in the ultrasound image segmentation process to obtain the best shape of the object of USG image. Based on the available data it can be concluded that the best ROI detection with cropping methods is produced by ellipse shape. The results show that ellipse shape of ROI Detection has the best accuracy compared to other cropping shapes. Based on the results, rectanguler and circle have the similar value. Therefore, MSE of ellipse is lower than rectanguler and circle shapes.

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