{"title":"Increase dehazing process using fast guided filter on the dark channel prior","authors":"R. Mutaqin, Fresy Nugroho, Nugraha Gumilar","doi":"10.1109/ICEEIE.2017.8328766","DOIUrl":"https://doi.org/10.1109/ICEEIE.2017.8328766","url":null,"abstract":"An image that contains degradation due a fog, so that the reduction of contrast and colors are faded. In this study, we have designed a system which can remove noise, fog effects or it can be called by Dehazing. Therefore, a method has been proposed for the removal of fog from the filter results by considering the guiding image content. It will be implemented on Dark Channel Prior Method which is the method using dark pixel, the software that can be used is Matlab. The output obtained is an image that has been separated by the effect of fog in a better quality.","PeriodicalId":304532,"journal":{"name":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134234659","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}
{"title":"Modelling of contractor selection using fuzzy-TOPSIS","authors":"Ibayasid Bintoro, R. Malani, Rihartanto","doi":"10.1109/ICEEIE.2017.8328778","DOIUrl":"https://doi.org/10.1109/ICEEIE.2017.8328778","url":null,"abstract":"The choice of construction contractors are very frequently conducted while tendering. There are more and more procedures in which the decision criteria of selecting a tender. To conduct a good selection, it is particularly central to correctly evaluate the contractor's abilities. The assessment is more qualitative and subjective, so subjective judgment based on experience is crucial. Making a decision implies that there are another choices to be considered and in a such case we would not only to recognize as many of these alternatives as possible but to select the one that top fits with our objectives and etc. So far several techniques have been offered to resolve Multi-Criteria Decision Making (MCDM) problems. An important point is how to apply the MCDM technique that has the capability to provide measures of constancy of preference. This study presents Technique of Order Preference by Similarity of Ideal Solution (TOPSIS) as a proposed method to deal with decision making in contractor selection. Triangular Fuzzy Number (TFN) is applied to handle linguistic environment which is used by human beings to make decisions.","PeriodicalId":304532,"journal":{"name":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130068809","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}
B. Siregar, E. Nababan, Alexander Yap, U. Andayani, Fahmi
{"title":"Forecasting of raw material needed for plastic products based in income data using ARIMA method","authors":"B. Siregar, E. Nababan, Alexander Yap, U. Andayani, Fahmi","doi":"10.1109/ICEEIE.2017.8328777","DOIUrl":"https://doi.org/10.1109/ICEEIE.2017.8328777","url":null,"abstract":"Forecasting is a process of predicting something future by doing calculations from previous data. In this case the authors will forecast the sale of plastic production by using ARIMA Box-Jenkins method for 2015 forecasting. The data used is the sales data of plastic factory production in Bandung from 2012 to 2014. This research will use ARIMA procedure in SAS that allows for identification, Estimation and forecasting of Time Series models. The measurement of the accuracy of forecasting results is done with the MAPE (Mean Absolute Percentage Error) value. Forecasting results conducted for 2015 using ARIMA (3.0, 2) on plastic product sales data for 2012 to 2014 resulted in a prediction accuracy rate of 74% for PP Trilene and 68% for PP Tintapro products.","PeriodicalId":304532,"journal":{"name":"2017 5th International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127024043","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}