EMITTER International Journal of Engineering Technology
EMITTER International Journal of Engineering Technology is a BI-ANNUAL journal published by Politeknik Elektronika Negeri Surabaya (PENS). It aims to encourage initiatives, to share new ideas, and to publish high-quality articles in the field of engineering technology and available to everybody at no cost. It stimulates researchers to explore their ideas and enhance their innovations in the scientific publication on engineering technology.
EMITTER International Journal of Engineering Technology primarily focuses on analyzing, applying, implementing and improving existing and emerging technologies and is aimed to the application of engineering principles and the implementation of technological advances for the benefit of humanity.
Articles
14 Documents
Search results for
, issue
" Vol 2, No 2 (2014)"
:
14 Documents
clear
<![CDATA[Indonesian Automatic Speech Recognition For Command Speech Controller Multimedia Player ]]>
<![CDATA[Wardhany, Vivien Arief]]>;
<![CDATA[Sukaridhoto, Sritrusta]]>;
<![CDATA[Sudarsono, Amang]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[The purpose of multimedia devices development is controlling through voice. Nowdays voice that can be recognized only in English. To overcome the issue, then recognition using Indonesian language model and accousticc model and dictionary. Automatic Speech Recognizier is build using engine CMU Sphinx with modified english language to Indonesian Language database and XBMC used as the multimedia player. The experiment is using 10 volunteers testing items based on 7 commands. The volunteers is classifiedd by the genders, 5 Male & 5 female. 10 samples is taken in each command, continue with each volunteer perform 10 testing command. Each volunteer also have to try all 7 command that already provided. Based on percentage clarification table, the word âKananâ had the most recognize with percentage 83% while âpilihâ is the lowest one. The word which had the most wrong clarification is âkembaliâ with percentagee 67%, while the word âkananâ is the lowest one. From the result of Recognition Rate by male there are several command such as âKembaliâ, âUtamaâ, âAtas â and âBawahâ has the low Recognition Rate. Especially for âkembaliâ cannot be recognized as the command in the female voices but in male voice that command has 4% of RR this is because the command doesnât have similar word in english near to âkembaliâ so the system unrecognize the command. Also for the command âPilihâ using the female voice has 80% of RR but for the male voice has only 4% of RR. This problem is mostly because of the different voice characteristic between adult male and female which male has lower voice frequencies (from 85 to 180 Hz) than woman (165 to 255 Hz).The result of the experiment showed that each man had different number of recognition rate caused by the difference tone, pronunciation, and speed of speech. For further work needs to be done in order to improving the accouracy of the Indonesian Automatic Speech Recognition system.Keywords: Automatic Speech Recognizer, Indonesian Acoustic Model, CMU Sphinx, indonesian Language Model, Recognition Rate, XBMC.]]>
<![CDATA[Internet Connection Control based on Idle Time Using User Behavior Pattern Analysis ]]>
<![CDATA[Hardiansyah, Fadilah Fahrul]]>;
<![CDATA[Buliali, Joko Lianto]]>;
<![CDATA[Wibisono, Waskitho]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[The increase of smartphone ability is rapidly increasing the power consumption. Many methods have been proposed to reduce smartphone power consumption. Most of these methods use the internet connection control based on the availability of the battery power level regardless of when and where a waste of energy occurs. This paper proposes a new approach to control the internet connection based on idle time using user behavior pattern analysis. User behavior patterns are used to predict idle time duration. Internet connection control performed during idle time. During idle time internet connection periodically switched on and off by a certain time interval. This method effectively reduces a waste of energy. Control of the internet connection does not interfere the user because it is implemented on idle time.Keywords: Smartphone, User Behavior, Pattern Recognition, Idle Time, Internet Connection Control]]>
<![CDATA[Applicationof Computer Visionfor Polishing RobotinAutomotive Manufacturing Industries ]]>
<![CDATA[Besari, Adnan Rachmat Anom]]>;
<![CDATA[Zamri, Ruzaidi]]>;
<![CDATA[Palil, Md. Dan Md.]]>;
<![CDATA[Prabuwono, Anton Satria]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[Polishing is a highly skilled manufacturing process with a lot of constraints and interaction with environment. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout partâs surface. In order to reduce the polishing time and cope with the shortage of skilled workers, robotic polishing technology has been investigated. This paper studies about vision system to measure surface defects that have been characterized to some level of surface roughness. The surface defects data have learned using artificial neural networks to give a decision in order to move the actuator of arm robot. Force and rotation time have chosen as output parameters of artificial neural networks. Results shows that although there is a considerable change in both parameter values acquired from vision data compared to real data, it is still possible to obtain surface defects characterization using vision sensor to a certain limit of accuracy. The overall results of this research would encourage further developments in this area to achieve robust computer vision based surface measurement systems for industrial robotic, especially in polishing process.Keywords: polishing robot, vision sensor, surface defects, and artificial neural networks]]>
<![CDATA[Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms ]]>
<![CDATA[Dewantara, Bima Sena Bayu]]>;
<![CDATA[Miura, Jun]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trialâerror determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time.Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm]]>
<![CDATA[Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network ]]>
<![CDATA[Al Rasyid, M. Udin Harun]]>;
<![CDATA[Aji, Eka Saputra]]>;
<![CDATA[Nadhori, Isbat Uzzin]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (9680.169 KB)
<![CDATA[Wireless sensor network (WSN) uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as powerâefficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with nonâadaptive scheme. From the simulation results, our proposed idea has goodâquality data transmission and more efficient in energy consumption, but it has higher delay than that of nonâadaptive scheme.Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.]]>
<![CDATA[PID Controller Design of Nonlinear System using a New Modified Particle Swarm Optimization with Time-Varying Constriction Coefficient ]]>
<![CDATA[., Alrijadjis]]>;
<![CDATA[Mu, Shenglin]]>;
<![CDATA[Nakashima, Shota]]>;
<![CDATA[Tanaka, Kanya]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[The proportional integral derivative (PID) controllers have been widely used in most process control systems for a long time. However, it is a very important problem how to choose PID parameters, because these parameters give a great influence on the control performance. Especially, it is difficult to tune these parameters for nonlinear systems. In this paper, a new modified particle swarm optimization (PSO) is presented to search for optimal PID parameters for such system. The proposed algorithm is to modify constriction coefficient which is nonlinearly decreased time-varying for improving the final accuracy and the convergence speed of PSO. To validate the control performance of the proposed method, a typical nonlinear system control, a continuous stirred tank reactor (CSTR) process, is illustrated. The results testify that a new modified PSO algorithm can perform well in the nonlinear PID control system design in term of lesser overshoot, rise-time, settling-time, IAE and ISE.Keywords: PID controller, Particle Swarm Optimization (PSO),constriction factor, nonlinear system.]]>
<![CDATA[Dimensionality Reduction Algorithms on H ]]>
<![CDATA[Syarif, Iwan]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (10447.419 KB)
<![CDATA[Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespecially when the number of possible different combinations of variables is so high. In this research, we evaluate the performance of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as feature selection algorithms when applied to high dimensional datasets.Our experiments show that in terms of dimensionality reduction, PSO is much better than GA. PSO has successfully reduced the number of attributes of 8 datasets to 13.47% on average while GA is only 31.36% on average. In terms of classification performance, GA is slightly better than PSO. GAâ reduced datasets have better performance than their original ones on 5 of 8 datasets while PSO is only 3 of 8 datasets.Keywords: feature selection, dimensionality reduction, Genetic Algorithm (GA), Particle Swarm Optmization (PSO).]]>
<![CDATA[Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network ]]>
<![CDATA[Al Rasyid, M. Udin Harun]]>;
<![CDATA[Aji, Eka Saputra]]>;
<![CDATA[Nadhori, Isbat Uzzin]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (9680.169 KB)
|
DOI: 10.24003/emitter.v2i2.23
<![CDATA[Wireless sensor network (WSN) uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as powerâefficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with nonâadaptive scheme. From the simulation results, our proposed idea has goodâquality data transmission and more efficient in energy consumption, but it has higher delay than that of nonâadaptive scheme.Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.]]>
<![CDATA[PID Controller Design of Nonlinear System using a New Modified Particle Swarm Optimization with Time-Varying Constriction Coefficient ]]>
<![CDATA[., Alrijadjis]]>;
<![CDATA[Mu, Shenglin]]>;
<![CDATA[Nakashima, Shota]]>;
<![CDATA[Tanaka, Kanya]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (133.449 KB)
|
DOI: 10.24003/emitter.v2i2.28
<![CDATA[The proportional integral derivative (PID) controllers have been widely used in most process control systems for a long time. However, it is a very important problem how to choose PID parameters, because these parameters give a great influence on the control performance. Especially, it is difficult to tune these parameters for nonlinear systems. In this paper, a new modified particle swarm optimization (PSO) is presented to search for optimal PID parameters for such system. The proposed algorithm is to modify constriction coefficient which is nonlinearly decreased time-varying for improving the final accuracy and the convergence speed of PSO. To validate the control performance of the proposed method, a typical nonlinear system control, a continuous stirred tank reactor (CSTR) process, is illustrated. The results testify that a new modified PSO algorithm can perform well in the nonlinear PID control system design in term of lesser overshoot, rise-time, settling-time, IAE and ISE.Keywords: PID controller, Particle Swarm Optimization (PSO),constriction factor, nonlinear system.]]>
<![CDATA[Dimensionality Reduction Algorithms on High Dimensional Datasets ]]>
<![CDATA[Syarif, Iwan]]>
<![CDATA[ EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014) ]]>
Publisher : <![CDATA[Politeknik Elektronika Negeri Surabaya (PENS) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (10447.419 KB)
|
DOI: 10.24003/emitter.v2i2.24
<![CDATA[Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespecially when the number of possible different combinations of variables is so high. In this research, we evaluate the performance of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as feature selection algorithms when applied to high dimensional datasets.Our experiments show that in terms of dimensionality reduction, PSO is much better than GA. PSO has successfully reduced the number of attributes of 8 datasets to 13.47% on average while GA is only 31.36% on average. In terms of classification performance, GA is slightly better than PSO. GAâ reduced datasets have better performance than their original ones on 5 of 8 datasets while PSO is only 3 of 8 datasets.Keywords: feature selection, dimensionality reduction, Genetic Algorithm (GA), Particle Swarm Optmization (PSO).]]>
