Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350753
M. A. Muslim, A. Nurzahputra, B. Prasetiyo
Giving credit to prospective debtor is determined by the existence of credit scoring. The accuracy of credit scoring to classify the debtor data is very important. The method that can be applied is classification and one of the classification method is decision tree. One of the decision tree algorithm that can be used is C4.5 algorithm. In this paper, the problem that discussed is how to increase the accuracy of C4.5 algorithm to predict credit receipts. The increasing accuracy is conducted by applying the Split Feature Reduction Model and Bagging Ensemble. Split Feature Reduction Model is applied in the preprocessing process which split datasets to the amount of n. In this paper, datasets split into 4 splits. Split 1 consists of 16 features, Split 2 consists of 12 features, Split 3 consists of 8 features, and Split 4 consists of 4 features. Then, C4.5 algorithm is applied to every splits. The best accuracy result by applying split feature reduction model with C4.5 algorithm is in Split 3 amount 73.1%. Then, the best accuracy results obtained by applying the split feature reduction model and bagging ensemble with C4.5 algorithm is in Split 3 amount 75.1%. In comparison to the accuracy of C4.5 algorithm stand alone, the applying of split feature reduction model and bagging ensemble obtained increased accuracy by 4.6%.
{"title":"Improving accuracy of C4.5 algorithm using split feature reduction model and bagging ensemble for credit card risk prediction","authors":"M. A. Muslim, A. Nurzahputra, B. Prasetiyo","doi":"10.1109/ICOIACT.2018.8350753","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350753","url":null,"abstract":"Giving credit to prospective debtor is determined by the existence of credit scoring. The accuracy of credit scoring to classify the debtor data is very important. The method that can be applied is classification and one of the classification method is decision tree. One of the decision tree algorithm that can be used is C4.5 algorithm. In this paper, the problem that discussed is how to increase the accuracy of C4.5 algorithm to predict credit receipts. The increasing accuracy is conducted by applying the Split Feature Reduction Model and Bagging Ensemble. Split Feature Reduction Model is applied in the preprocessing process which split datasets to the amount of n. In this paper, datasets split into 4 splits. Split 1 consists of 16 features, Split 2 consists of 12 features, Split 3 consists of 8 features, and Split 4 consists of 4 features. Then, C4.5 algorithm is applied to every splits. The best accuracy result by applying split feature reduction model with C4.5 algorithm is in Split 3 amount 73.1%. Then, the best accuracy results obtained by applying the split feature reduction model and bagging ensemble with C4.5 algorithm is in Split 3 amount 75.1%. In comparison to the accuracy of C4.5 algorithm stand alone, the applying of split feature reduction model and bagging ensemble obtained increased accuracy by 4.6%.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"31 1","pages":"141-145"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81546473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350681
D. R. Pambudi, M. Rivai, A. Arifin
Organic solvent compounds are widely used as production raw materials in the field of chemical industry. Organic compounds are easily changed from liquid to gas conditions at room temperature. Organic solvent compounds are commonly found as gases or vapors, which are flammable, toxic, and explosive. The identification of the gas sensor is required in identifying and classifying some gases of volatile organic compounds, especially to monitor the condition of the organic solvent vapor pollutants in the environment. The latest development of gas sensor was designed based on the optical field by using Fabry-Perot interferometer which is applied to optical fiber to increase the sensitivity of gas sensor. The gas sensor was designed by coating chemical membranes on the tip of the optical fiber to increase the sensor selectivity. Three different types of chemical membranes are coated on the same three optical fibers placed in the sensor chamber. In this study, sensor output data are interpreted into digital form through analog-to-digital converter, while data processing and identification are performed by computer. The identification process of organic solvent is done by using artificial neural network algorithm. The results show that the sensor array could produce a different pattern for each of the gas vapor samples. The Neural network pattern recognition system can identify the type of vapor with 100% accuracy rate. Identification of organic solvent compound types, may be used to detect low-vapor gas vapor exposure applied in monitoring activities and analysis of organic solvent vapor.
{"title":"Detection of organic solvent compounds using optical fiber interferometer array and neural network pattern recognition","authors":"D. R. Pambudi, M. Rivai, A. Arifin","doi":"10.1109/ICOIACT.2018.8350681","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350681","url":null,"abstract":"Organic solvent compounds are widely used as production raw materials in the field of chemical industry. Organic compounds are easily changed from liquid to gas conditions at room temperature. Organic solvent compounds are commonly found as gases or vapors, which are flammable, toxic, and explosive. The identification of the gas sensor is required in identifying and classifying some gases of volatile organic compounds, especially to monitor the condition of the organic solvent vapor pollutants in the environment. The latest development of gas sensor was designed based on the optical field by using Fabry-Perot interferometer which is applied to optical fiber to increase the sensitivity of gas sensor. The gas sensor was designed by coating chemical membranes on the tip of the optical fiber to increase the sensor selectivity. Three different types of chemical membranes are coated on the same three optical fibers placed in the sensor chamber. In this study, sensor output data are interpreted into digital form through analog-to-digital converter, while data processing and identification are performed by computer. The identification process of organic solvent is done by using artificial neural network algorithm. The results show that the sensor array could produce a different pattern for each of the gas vapor samples. The Neural network pattern recognition system can identify the type of vapor with 100% accuracy rate. Identification of organic solvent compound types, may be used to detect low-vapor gas vapor exposure applied in monitoring activities and analysis of organic solvent vapor.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"30 1","pages":"477-482"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84378741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350710
M. Jupri, R. Sarno
Tax revenue has a very important role to fund the State's finances. In order for the optimal tax revenue, the tax authorities must perform tax supervision to the taxpayers optimally. By using the self-assessment taxation system that is taxpayers calculation, pay and report their own tax obligations added with the data of other parties will create a very large data. Therefore, the tax authorities are required to immediately know the taxpayer non-compliance for further audit. This research uses the classification algorithm C4.5, SVM (Support Vector Machine), KNN (K-Nearest Neighbor), Naive Bayes and MLP (Multilayer Perceptron) to classify the level of taxpayer compliance with four goals that are corporate taxpayers comply formally and materially required, corporate taxpayers comply formally required, corporate taxpayers comply materially required and corporate taxpayers not comply formally and materially required. The classification results of each algorithm are compared and the best algorithm chosen based on criteria F-Score, Accuracy and Time taken to build the model by using fuzzy TOPSIS method. The final result shows that C4.5 algorithm is the best algorithm to classify taxpayer compliance level compared to other algorithms.
{"title":"Taxpayer compliance classification using C4.5, SVM, KNN, Naive Bayes and MLP","authors":"M. Jupri, R. Sarno","doi":"10.1109/ICOIACT.2018.8350710","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350710","url":null,"abstract":"Tax revenue has a very important role to fund the State's finances. In order for the optimal tax revenue, the tax authorities must perform tax supervision to the taxpayers optimally. By using the self-assessment taxation system that is taxpayers calculation, pay and report their own tax obligations added with the data of other parties will create a very large data. Therefore, the tax authorities are required to immediately know the taxpayer non-compliance for further audit. This research uses the classification algorithm C4.5, SVM (Support Vector Machine), KNN (K-Nearest Neighbor), Naive Bayes and MLP (Multilayer Perceptron) to classify the level of taxpayer compliance with four goals that are corporate taxpayers comply formally and materially required, corporate taxpayers comply formally required, corporate taxpayers comply materially required and corporate taxpayers not comply formally and materially required. The classification results of each algorithm are compared and the best algorithm chosen based on criteria F-Score, Accuracy and Time taken to build the model by using fuzzy TOPSIS method. The final result shows that C4.5 algorithm is the best algorithm to classify taxpayer compliance level compared to other algorithms.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"8 1","pages":"297-303"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81133614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350793
Yudit Arum Mekarsari, D. Setiadi, C. A. Sari, E. H. Rachmawanto, Muljono
The main problem in using various watermarking methods to secure digital images is how to optimize the trade-off between robustness watermarked image against the effect of distortion and imperceptibility on watermark insertion. This research proposes a watermark insertion method to protect copyright in true color (RGB) images by combining Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) algorithms. DWT process will be done as much as 2 levels then selected subband LL2 to inserted watermark by Singular Value Decomposition (SVD) method. Measuring tool in this research using MSE, PSNR, SSI M for imperceptibility and NC quality measurement for robustness measurement. The results show that the proposed scheme can optimize the trade-off between imperceptibility and robustness. Some attacks are used such as Gaussian noise, salt & pepper noise, crop, blur and rotate for watermarked image resilience. The PSNR and SSIM values produced from this method are fairly stable values above 40 dB for PSNR and above 0.99 for SSIM. While the average value of NC resulting from this method is 1.
{"title":"Non-blind RGB image watermarking technique using 2-level discrete wavelet transform and singular value decomposition","authors":"Yudit Arum Mekarsari, D. Setiadi, C. A. Sari, E. H. Rachmawanto, Muljono","doi":"10.1109/ICOIACT.2018.8350793","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350793","url":null,"abstract":"The main problem in using various watermarking methods to secure digital images is how to optimize the trade-off between robustness watermarked image against the effect of distortion and imperceptibility on watermark insertion. This research proposes a watermark insertion method to protect copyright in true color (RGB) images by combining Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) algorithms. DWT process will be done as much as 2 levels then selected subband LL2 to inserted watermark by Singular Value Decomposition (SVD) method. Measuring tool in this research using MSE, PSNR, SSI M for imperceptibility and NC quality measurement for robustness measurement. The results show that the proposed scheme can optimize the trade-off between imperceptibility and robustness. Some attacks are used such as Gaussian noise, salt & pepper noise, crop, blur and rotate for watermarked image resilience. The PSNR and SSIM values produced from this method are fairly stable values above 40 dB for PSNR and above 0.99 for SSIM. While the average value of NC resulting from this method is 1.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"122 1","pages":"623-627"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89874010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350805
Mihuandayani, Herda D. Ramandita, A. Setyanto, I. B. Sumafta
Tracking customer preferences is an important aspect of business success. Having information on hand about most favorite food is a key success for everyone who takes apart in the culinary business. Exact sales data on certain food is hardly available to the public. Restaurant owner tends to keep their data for their own business strategy. Therefore, generating a food trend in a certain community is hardly possible using food sales data. This paper discussed extracting food general trend from social media, with the case study on Twitter data with a certain regional area of interest. Social media provides a tremendous amount of data including people choice of food when they visit the certain place. However, the available data is unstructured in human language. The challenge is twofold: to grasp the meaning and extract the relevant information to the food trends. We proposed a bag of words technique to gather relevant information in the Indonesian language for feature extracting purpose. While K-mean Clustering and Simple Additive Weighting (SAW) algorithm are proposed to draw up the food rank. In order to measure the accuracy, we compare our result with the sales data of some restaurants in Yogyakarta. We test the algorithm using 4 weeks of data, the result is compared against the available data and an accuracy of 72.75 % is achieved.
{"title":"Food trend based on social media for big data analysis using K-mean clustering and SAW: A case study on yogyakarta culinary industry","authors":"Mihuandayani, Herda D. Ramandita, A. Setyanto, I. B. Sumafta","doi":"10.1109/ICOIACT.2018.8350805","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350805","url":null,"abstract":"Tracking customer preferences is an important aspect of business success. Having information on hand about most favorite food is a key success for everyone who takes apart in the culinary business. Exact sales data on certain food is hardly available to the public. Restaurant owner tends to keep their data for their own business strategy. Therefore, generating a food trend in a certain community is hardly possible using food sales data. This paper discussed extracting food general trend from social media, with the case study on Twitter data with a certain regional area of interest. Social media provides a tremendous amount of data including people choice of food when they visit the certain place. However, the available data is unstructured in human language. The challenge is twofold: to grasp the meaning and extract the relevant information to the food trends. We proposed a bag of words technique to gather relevant information in the Indonesian language for feature extracting purpose. While K-mean Clustering and Simple Additive Weighting (SAW) algorithm are proposed to draw up the food rank. In order to measure the accuracy, we compare our result with the sales data of some restaurants in Yogyakarta. We test the algorithm using 4 weeks of data, the result is compared against the available data and an accuracy of 72.75 % is achieved.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"10 1","pages":"549-554"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90287218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350811
Adewasti, R. Febriani, Sholihin, Eka Susanti, Emilia Hesti
In Indonesia, the earthquake disaster is a disaster that often happens and cause a lot of damage and casualties, so researchers will try to design a Robot control system to monitor the Earthquake Disaster Location Using Xbee Pro Based Arduino. Initial robot formation, how to design a tool in the form of robot is one that must be considered for the tool produced in this case a robot can be useful for the community and can help the work of the SAR team in terms of monitoring the location of earthquakes. Researchers only limit the subject matter only to the set of receivers and monitoring devices. In order to monitor the state of the earthquake disaster site, this robot is equipped with a camera as a monitoring tool. This tool uses Arduino as Microcontroller, Xbee Pro as communication medium between remote and robot, Driver Motor as DC motor drive, DC Motor as a robot drive, Servo Motor as camera drive, Wireless Camera and Mobile as monitoring device. As a result the robot is able to walk and receive commands up to a distance of more than 20 meters while in the room, and stay connected to the phone to monitor the location of the earthquake.
{"title":"Xbee pro module application in to organize and monitoring earthquake disaster location with the robot control system","authors":"Adewasti, R. Febriani, Sholihin, Eka Susanti, Emilia Hesti","doi":"10.1109/ICOIACT.2018.8350811","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350811","url":null,"abstract":"In Indonesia, the earthquake disaster is a disaster that often happens and cause a lot of damage and casualties, so researchers will try to design a Robot control system to monitor the Earthquake Disaster Location Using Xbee Pro Based Arduino. Initial robot formation, how to design a tool in the form of robot is one that must be considered for the tool produced in this case a robot can be useful for the community and can help the work of the SAR team in terms of monitoring the location of earthquakes. Researchers only limit the subject matter only to the set of receivers and monitoring devices. In order to monitor the state of the earthquake disaster site, this robot is equipped with a camera as a monitoring tool. This tool uses Arduino as Microcontroller, Xbee Pro as communication medium between remote and robot, Driver Motor as DC motor drive, DC Motor as a robot drive, Servo Motor as camera drive, Wireless Camera and Mobile as monitoring device. As a result the robot is able to walk and receive commands up to a distance of more than 20 meters while in the room, and stay connected to the phone to monitor the location of the earthquake.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"5 1","pages":"651-655"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79662426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350743
Mihuandayani, Ema Utami, E. T. Luthfi
The tax gives an important role for the contributions of the economy and development of a country. The improvements to the taxation service system continuously done in order to increase the State Budget. One of consideration to know the performance of taxation particularly in Indonesia is to know the public opinion as for the object service. Text mining can be used to know public opinion about the tax system. The rapid growth of data in social media initiates this research to use the data source as big data analysis. The dataset used is derived from Facebook and Twitter as a source of data in processing tax comments. The results of opinions in the form of public sentiment in part of service, website system, and news can be used as consideration to improve the quality of tax services. In this research, text mining is done through the phases of text processing, feature selection and classification with Support Vector Machine (SVM). To reduce the problem of the number of attributes on the dataset in classifying text, Feature Selection used the Information Gain to select the relevant terms to the tax topic. Testing is used to measure the performance level of SVM with Feature Selection from two data sources. Performance measured using the parameters of precision, recall, and F-measure.
{"title":"Text mining based on tax comments as big data analysis using SVM and feature selection","authors":"Mihuandayani, Ema Utami, E. T. Luthfi","doi":"10.1109/ICOIACT.2018.8350743","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350743","url":null,"abstract":"The tax gives an important role for the contributions of the economy and development of a country. The improvements to the taxation service system continuously done in order to increase the State Budget. One of consideration to know the performance of taxation particularly in Indonesia is to know the public opinion as for the object service. Text mining can be used to know public opinion about the tax system. The rapid growth of data in social media initiates this research to use the data source as big data analysis. The dataset used is derived from Facebook and Twitter as a source of data in processing tax comments. The results of opinions in the form of public sentiment in part of service, website system, and news can be used as consideration to improve the quality of tax services. In this research, text mining is done through the phases of text processing, feature selection and classification with Support Vector Machine (SVM). To reduce the problem of the number of attributes on the dataset in classifying text, Feature Selection used the Information Gain to select the relevant terms to the tax topic. Testing is used to measure the performance level of SVM with Feature Selection from two data sources. Performance measured using the parameters of precision, recall, and F-measure.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"25 1","pages":"537-542"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77607817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350714
Faiq Ahmad Khan, Shibli Nisar
Feedback control system is one of the most significant and challenging area in this modern era. Almost in every technical program it is being taught. Different research work has been done on the analysis of feedback control systems. But all the previous research work is on analysis of system based on stability, initial and final value theorem, state space representation or based on root locus and bode plot individually. In this paper the complete analysis of feedback control systems has been carried out that includes transfer functions, poles and zeros, stability of a system, initial and final values, state space representations, different responses of a system, time response of first and second order systems, Routh-Hurwitz criterion, root locus and Bode plot together using MATLAB.
{"title":"Design and analysis of feedback control system","authors":"Faiq Ahmad Khan, Shibli Nisar","doi":"10.1109/ICOIACT.2018.8350714","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350714","url":null,"abstract":"Feedback control system is one of the most significant and challenging area in this modern era. Almost in every technical program it is being taught. Different research work has been done on the analysis of feedback control systems. But all the previous research work is on analysis of system based on stability, initial and final value theorem, state space representation or based on root locus and bode plot individually. In this paper the complete analysis of feedback control systems has been carried out that includes transfer functions, poles and zeros, stability of a system, initial and final values, state space representations, different responses of a system, time response of first and second order systems, Routh-Hurwitz criterion, root locus and Bode plot together using MATLAB.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"10 1","pages":"16-24"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74270477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350732
Zhi-jun Wu, Xuan Liu, Akhmad Dahlan
The mysterious disappearance of MH370 flight is incredible in current air traffic management (ATM) with the rapid development of modern communication technology. In this paper, the vulnerabilities of communication technology and safety management on airplane tracking are explored through several existing methods and means. Then the proposals, for airborne communication, navigation, and surveillance system and safety management from internal and external factors, are put forward respectively to improve the ability of emergency response and disaster recovery for flight.
{"title":"Risk and countermeasure analysis of network-based global airplane tracking system","authors":"Zhi-jun Wu, Xuan Liu, Akhmad Dahlan","doi":"10.1109/ICOIACT.2018.8350732","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350732","url":null,"abstract":"The mysterious disappearance of MH370 flight is incredible in current air traffic management (ATM) with the rapid development of modern communication technology. In this paper, the vulnerabilities of communication technology and safety management on airplane tracking are explored through several existing methods and means. Then the proposals, for airborne communication, navigation, and surveillance system and safety management from internal and external factors, are put forward respectively to improve the ability of emergency response and disaster recovery for flight.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"2 1","pages":"292-296"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90454766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350791
M. Ikhwan, Mardlijah, C. Imron
Solar tracker in photo voltaic (PV) conversion technology becomes one of the most important factors in harvesting renewable energy. The development of this technology improved the efficiency of PV. This paper aimed to control PV position which is perpendicular to the direction of solar radiation. The solar altitude and azimuth angle were approached with pitch and yaw angle of solar tracker motor using model predictive control in Simulink package in Matlab. Results showed that the error value between solar tracker motor angle and solar angle is not significant.
{"title":"Model predictive control on dual axis solar tracker using Matlab/Simulink simulation","authors":"M. Ikhwan, Mardlijah, C. Imron","doi":"10.1109/ICOIACT.2018.8350791","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350791","url":null,"abstract":"Solar tracker in photo voltaic (PV) conversion technology becomes one of the most important factors in harvesting renewable energy. The development of this technology improved the efficiency of PV. This paper aimed to control PV position which is perpendicular to the direction of solar radiation. The solar altitude and azimuth angle were approached with pitch and yaw angle of solar tracker motor using model predictive control in Simulink package in Matlab. Results showed that the error value between solar tracker motor angle and solar angle is not significant.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"24 1","pages":"784-788"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84980291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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