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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 144 Documents

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Search results for , issue "Vol 5: EECSI 2018" : 144 Documents clear

Analysis of Waveform of Partial Discharge in Air Insulation Measured by RC Detector Michael Stevano Sinurat; Umar Khayam
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

This study discusses the measurement of Partial Discharge (PD) in air insulation. Partial Discharge Measurement is very important to know the condition of electrical equipment. The cause of partial discharge is not only old equipment, but also from set-up errors and insulation problems. In this research partial discharge measurement was performed by using electrical methods. Electrical method use RC Detector. The modeling of partial discharge was done by using needle-plane electrode distant 1 cm in air insulation. Partial discharge measurement parameters include the measurement of Background Noise (BGN), Partial Discharge Inception Voltage (PDIV) and PD Waveform. The Partial Discharge measurement result show that Vpp of BGN ON is higher than Vpp of BGN OFF. The negative PDIV signal first appeared for the RC Detector at a voltage 3.55 KV and Positive PDIV at 4.01 KV. Negative and positive PD waveform for RC Detector at 5 KV, 5.5 KV, 6 KV, 6.5 KV and 7 KV respectively, it has been found that the fall time is greater than the rise time, and peak to peak voltage (Vpp) will be greater when the applied voltage is greater.

Determine supporting features for mobile application of NUSANTARA Dana I. Sensuse; Ika Arthalia Wulandari; Erzi Hidayat; Elin Cahyaningsih; Pristi Sukmasetya; Wina Permana Sari
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

This paper is a continuation of previous research focusing on the development of a model of knowledge management system for civil servant from three ministries in Indonesia (KEMENPAN&RB, BKN, and LAN). From previous study obtain a knowledge management model which is Government Human Capital Knowledge Management of Republic of Indonesia (NUSANTARA). Implementation of this model is conducted with web system, further development of this system still provides constraints from several sides in providing more optimal service against users requirements as well as limited accessibility and responsiveness. This paper aims to explore the supporting features that will be used to integrate pre- existing systems that build mobile knowledge management applications. Data were collected by interview from each related institution. The CommonKADS method is chosen as a technique to explore the problems and knowledge of each organization. SMAPA method is used to validate the result from the experts and end users. Results of this work are produced seven recommended supporting features there are vision and mission view, activity notification, group discussion, search repository, upload document and document activities log.

Automatic Estimation of Human Weight From Body Silhouette Using Multiple Linear Regression Hurriyatul Fitriyah; Gembong Edhi Setyaw
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Estimating weight based on 2D image is advantageous especially for contactless and rapid measurement. Several researches used additional thermal camera or Kinect camera, required subjects to do front and side pose and manually extract body measures. This research propose an algorithm to estimate body weight automatically using 2D visual image where subject only do front pose. This research studied 4 features of body measures which are: (F1) height, and width of (F2) shoulder, (F3) abdomen/waist plus arm, (F4) feet. Each feature was simply subtracted based on body proportion where normal body has 8 equal segments. Shoulder is in 2nd segment, abdomen/waist is in 4th segment and feet is in the last segment. Multiple Linear Regression is used to determine weight estimation formula of all combination of 4 features, 15 in total. The highest significance R2 (0.80) and RMSE 2.68 Kg is given when using all 4 features in the estimation formula.

Real Time SIBI Sign Language Recognition Based on K-Nearest Neighbor Fitrah Humaira; Supria Supria; Darlis Herumurti; Kukuh Widarsono
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Persons with disabilities also have the right to communicate with each other, both with normal people and people with other disabilities. People with disabilities will be difficult to communicate with other people. They use 'sign language' to communicate. That's why other normal people will be difficult to communicate with them. Because there are not many normal people that can understand the 'sign language'. System which can help to communicate with disabilities people are needed. In this paper, we proposed sign language recognition for Sistem Isyarat Bahasa Indonesia (SIBI) using leap motion based on K-Nearest Neighbor. Technology of leap motion controller will generate the existence of coordinate points on each bone in hand. As an input, we used the value of distance between the coordinates of each bone distal to the position of the palm, which were measured using Euclidean Distance. This feature of distance will be used for training and testing data on K-Nearest Neighbor method. The experiment result shows that the best accuracy is 0,78 and error 0,22 with proposed parameter of K = 5.

Application of Ultra-Wideband Double Layer Printed Antenna for Partial Discharge Detection Yuda Muhammad Hamdani; Umar Khayam
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Partial discharge (PD) is a local electrification phenomenon that partially connects insulation between the conductors and occurs either on the surface of the conductor or inside the insulation (void). During the PD there are several phenomena that accompany the occurrence of PD, such as impulse currents, heat radiation, electromagnetic waves, mechanical waves and chemical processes. This phenomenon is detected and measured to know the existence of PD. One of the PD measurements is ultra high frequency (UHF) method, by measuring the waves generated by PD using antenna. One of antenna having good characteristics is UWB double layer printed antenna. In this paper the application of ultra-wideband double layer printed antenna for partial discharge detection is reported. The application of antenna on PD measurement, shows that the antenna is able to detect PD. The characteristics of PD: PDIV, PDEV, PD waveform are measured using this antenna. Ultra-wideband (UWB) double layer printed antenna is an antenna developed from a square microstrip antenna with symmetrical T-shaped tethering. The proposed antenna is implemented on Epoxy FR-4 substrate with permittivity of 4.3, thickness of 1.6mm, and 72.8mm x 60.0mm in size. The VNA testing of the antenna shows that the antenna bandwidth is from 50MHz to 2.30GHz. The measured results of PD wave are PDIV, PD waveform and PDEV.

Variance and Symmetrical-based Approach for Optimal Alignment of 3D Model Luh Putu Ayu Prapitasari; Parth Rawal; Rolf-Rainer Grigat
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer's world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object's point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.

Reliability Analysis of Randu Garut 3 Distribution System Using Section Technique Method Jimmy Trio Putra; Raka Bagus
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

In a distribution system, reliability index is significant to calculate system performance in continuosly distribute the electricity power to consuments. Fedeer analysed by researcher is the main electricity distributor in Tambak Aji industrial area, a developing industrial area. This research is needed to be conducted to ensure the frequent blackout is known and minimalized along with increasement of load number in the feeder. Using section technique method which divides feeder section based on sectionalizer number and detailed calculation in each load point, device failure rate, the length of conductor, and disturbance repairement duration. It was obtained Randu Garut 3 feeder reliability index of SAIFI of 1.759 faults/year, SAIDI of 4.547 hours/year as CAIDI of 2.585 hours/year.

The Recognition Of Semaphore Letter Code Using Haar Wavelet And Euclidean Function Leonardus Sandy Ade Putra; Linggo Sumarno; Vincentius Abdi Gunawan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Semaphore are one way of communicating over long distances using the semaphore flags. In Indonesia semaphore is used in scout activities as a method to send information in the form of a sentence containing the message. Sending the semaphore letter code tends to be difficult. Based on the need to semaphore learning, this research proposes an algorithm with image processing as a way to correct the movement of the semaphore letter code based on the image obtained by using the webcam. Digital image processing, Wavelet feature extraction, and Euclidean distance function are applied in this study to determine the best recognition rate of variation decimation and distance variation to sending semaphore letter code using the webcam. This study resulted in the best recognition rate of 95.4% in the 1 st decimation, recognition rate reached 94.6% in decimation 2, and recognition rate reached 94.2% in decimation 3. The result of the introduction of the semaphore letter code is on the introduction of movement as far as 3 to 5 meters

Knowledge Management Maturity Assessment in Air Drilling Associates using G-KMMM Dana I. Sensuse; Richard Vinc; Ricky Nauvaldy Ruliputra; Siti Hadjar; Jonathan Sofian Lusa; Pudy Prima
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Since the early 1990s, companies in the oil & gas industry have realized that their business operations are knowledge-based, where company performance can be derived from faster identification, an assessment of an opportunity, and the speed of an exploitation. The oil & gas industry is one of the leading industries in the application and development of knowledge management; this is caused by changes in market and technology from 1990s to the beginning of the 21st century. Utilizing knowledge management is a must to be able to compete with other oil and gas industry companies. Currently, Air Drilling Associates (ADA) as one of the companies in oil & gas industry already has implemented knowledge management system, but its benefits are far from the expectation. In order to position their efforts and initialize knowledge management, companies need framework to use as a template. The objective of this paper is to measure the knowledge management maturity of Air Drilling Associates and other suggestion related to knowledge management for improvement.

Artificial Neural Network Parameter Tuning Framework For Heart Disease Classification Mohamad Haider Abu Yazid; Haikal Satria; Shukor Talib; Novi Azman
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Heart Disease are among the leading cause of death worldwide. The application of artificial neural network as decision support tool for heart disease detection. However, artificial neural network required multitude of parameter setting in order to find the optimum parameter setting that produce the best performance. This paper proposed the parameter tuning framework for artificial neural network. Statlog heart disease dataset and Cleveland heart disease dataset is used to evaluate the performance of the proposed framework. The results show that the proposed framework able to produce high classification accuracy where the overall classification accuracy for Cleveland dataset is 90.9% and 90% for Statlog dataset.

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