Pub Date : 2018-11-01DOI: 10.1109/eiconcit.2018.8878530
{"title":"EIConCIT 2018 Organizer and Sponsors","authors":"","doi":"10.1109/eiconcit.2018.8878530","DOIUrl":"https://doi.org/10.1109/eiconcit.2018.8878530","url":null,"abstract":"","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114549719","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 : 2018-11-01DOI: 10.1109/EIConCIT.2018.8878525
Muhammad Rizky Eka Arlin, M. Niswar, Adnan Adnan, Doudou Fall, S. Kashihara
With the popularity and the high demand of Internet of Things (IoT), company and university are striving to deliver innovations every day. LoRa is one of the trending technologies in the IoT field, and it can build Low-Power Wide Area Network (LPWAN). However, the network performance of LoRa strongly depends on an environment where LoRa is installed. Therefore, before deploying a network with LoRa, we need to evaluate network performance. At present, researchers or developers evaluate it manually. In this paper, we provide a design of a measurement tool for evaluating network performance with LoRa to support for deploying a LoRA network. We also show experimental results by using our measurement tool, and we then discussed installing the LoRa network in our crab park environment.
{"title":"LouPe: LoRa Performance Measurement Tool","authors":"Muhammad Rizky Eka Arlin, M. Niswar, Adnan Adnan, Doudou Fall, S. Kashihara","doi":"10.1109/EIConCIT.2018.8878525","DOIUrl":"https://doi.org/10.1109/EIConCIT.2018.8878525","url":null,"abstract":"With the popularity and the high demand of Internet of Things (IoT), company and university are striving to deliver innovations every day. LoRa is one of the trending technologies in the IoT field, and it can build Low-Power Wide Area Network (LPWAN). However, the network performance of LoRa strongly depends on an environment where LoRa is installed. Therefore, before deploying a network with LoRa, we need to evaluate network performance. At present, researchers or developers evaluate it manually. In this paper, we provide a design of a measurement tool for evaluating network performance with LoRa to support for deploying a LoRA network. We also show experimental results by using our measurement tool, and we then discussed installing the LoRa network in our crab park environment.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114881584","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 : 2018-11-01DOI: 10.1109/EIConCIT.2018.8878521
Darmastuti, E. P. Wibowo, Metty Mustikasari, J. Harlan, S. Widiyanto, D. Sundani
Panoramic X-Ray is one type of image that can be used in the health world to identify various diseases and damage that occur in the jaw and teeth. This study aims to identify the inferior mandibular cortex and detecting mandibular resorption as an indication of osteoporosis. Several stages are conducted in the proposed method. The first step in the pre-processing stage to be done is cropping, to obtain the Region of Interest (ROI). The next step in the pre-processing stage is image improvement to get image with favorable quality. The extraction stage is conducted in two steps. In the first step the image is processed using the edge detection method. In the second step of the extraction stage we use quantum edge detection to produce the upper edge of inferior mandibular cortex. Then, the lower border of inferior mandibular cortex is projected to obtain a difference between the upper and the lower border of the inferior mandibular cortex. As the result of study, we can identify bone resorption in the inferior mandibular cortex. Resorption of the mandibular cortex is an indication of osteoporosis. It is concluded that damage to the jaw bone can be seen from the result of panoramic X-Ray images after performing image processing.
{"title":"Panoramic X-Ray Analysis Using Edge Detection Method on Mandibular Cortex","authors":"Darmastuti, E. P. Wibowo, Metty Mustikasari, J. Harlan, S. Widiyanto, D. Sundani","doi":"10.1109/EIConCIT.2018.8878521","DOIUrl":"https://doi.org/10.1109/EIConCIT.2018.8878521","url":null,"abstract":"Panoramic X-Ray is one type of image that can be used in the health world to identify various diseases and damage that occur in the jaw and teeth. This study aims to identify the inferior mandibular cortex and detecting mandibular resorption as an indication of osteoporosis. Several stages are conducted in the proposed method. The first step in the pre-processing stage to be done is cropping, to obtain the Region of Interest (ROI). The next step in the pre-processing stage is image improvement to get image with favorable quality. The extraction stage is conducted in two steps. In the first step the image is processed using the edge detection method. In the second step of the extraction stage we use quantum edge detection to produce the upper edge of inferior mandibular cortex. Then, the lower border of inferior mandibular cortex is projected to obtain a difference between the upper and the lower border of the inferior mandibular cortex. As the result of study, we can identify bone resorption in the inferior mandibular cortex. Resorption of the mandibular cortex is an indication of osteoporosis. It is concluded that damage to the jaw bone can be seen from the result of panoramic X-Ray images after performing image processing.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126203735","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 : 2018-11-01DOI: 10.1109/EIConCIT.2018.8878566
Bustani, M. Zainuddin, Arbain, A. F. O. Gaffar, Mulyanto, Purnawansyah
The electrical power usage forecasting is the basis for energy investment planning and plays an important role in developing institutions and agencies. The combination of computational mathematical concepts and computer technology has widely used for forecasting electric power usage while those methods proved very powerful to predict the electric power usage in the future. There are two main roots in logic and reasoning in the philosophy of science and mathematics which are the basis of all computational activities. One of them is a heuristic approach that has widely applied in various studies in the areas of predictive problems, selection, and search problems. In this study, the prediction of electric power usage for each category carried out by applying the concept of a heuristic network. Time series data modeling is done using a weighted network. The values of each network weighting are obtained using a heuristic approach. The purpose of this study is to simultaneously predict two categories of electricity use by implementing a heuristic network. The results of the study show that the MISO (Multi Input Single Output) Heuristic Network can be stated to be significant enough to carry out the activity of predicting two categories of time series data simultaneously. Furthermore, the results of this study obtained concluded that the parameter that has the most dominant influence on training results is the number of model orders.
电力使用预测是能源投资规划的基础，在发展机构中起着重要的作用。计算数学概念与计算机技术的结合已被广泛应用于电力使用预测，并被证明是预测未来电力使用的有力方法。在科学哲学和数学中，逻辑和推理是所有计算活动的基础，这两个主要根源。其中之一是启发式方法，广泛应用于预测问题、选择和搜索问题等领域的各种研究。在本研究中，运用启发式网络的概念对各个类别的用电量进行预测。时间序列数据建模使用加权网络。使用启发式方法获得每个网络的权重值。本研究的目的是通过实施启发式网络来同时预测两类电力使用。研究结果表明，MISO (Multi - Input Single - Output，多输入单输出)启发式网络具有显著性，可以同时对两类时间序列数据进行预测。此外，本研究的结果得出结论，对训练结果影响最大的参数是模型阶数。
{"title":"Electrical Power Usage Prediction using A Multi Input Single Output Heuristic Network","authors":"Bustani, M. Zainuddin, Arbain, A. F. O. Gaffar, Mulyanto, Purnawansyah","doi":"10.1109/EIConCIT.2018.8878566","DOIUrl":"https://doi.org/10.1109/EIConCIT.2018.8878566","url":null,"abstract":"The electrical power usage forecasting is the basis for energy investment planning and plays an important role in developing institutions and agencies. The combination of computational mathematical concepts and computer technology has widely used for forecasting electric power usage while those methods proved very powerful to predict the electric power usage in the future. There are two main roots in logic and reasoning in the philosophy of science and mathematics which are the basis of all computational activities. One of them is a heuristic approach that has widely applied in various studies in the areas of predictive problems, selection, and search problems. In this study, the prediction of electric power usage for each category carried out by applying the concept of a heuristic network. Time series data modeling is done using a weighted network. The values of each network weighting are obtained using a heuristic approach. The purpose of this study is to simultaneously predict two categories of electricity use by implementing a heuristic network. The results of the study show that the MISO (Multi Input Single Output) Heuristic Network can be stated to be significant enough to carry out the activity of predicting two categories of time series data simultaneously. Furthermore, the results of this study obtained concluded that the parameter that has the most dominant influence on training results is the number of model orders.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127278910","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 : 2018-11-01DOI: 10.1109/EIConCIT.2018.8878538
Lukman Syafie, Fitriyani Umar, Aliyazid Mude, Herdianti Darwis, Herman, Harlinda
Missing data is one of the problems in classification that can reduce classification accuracy. This paper mainly studies the technique of fixing missing data by using deletion instances, mean imputation and median imputation. We use Naive Bayes based method which is used in many classification techniques. We proposed the improvement of the Naive Bayes formula into the Naive Bayes Logarithm (NBL) formula to anticipate the final result which can obtain zero for the prior probability of classifier. If the the prior probability of classifier obtained zero it will result failure in the classification process. In this research, we use Web-Kb dataset that has been used in other classification method. By Naive Bayes Logarithm, we study the effect of missing data on the classification accuracy in different types of method of fixing data. The results show the documents can be classified well in average 84.909% when using mean imputation, median imputation and deletion instances. It concludes that Naive Bayes Logarithm is reliable in the classification of documents.
{"title":"Missing Data Handling Using The Naive Bayes Logarithm (NBL) Formula","authors":"Lukman Syafie, Fitriyani Umar, Aliyazid Mude, Herdianti Darwis, Herman, Harlinda","doi":"10.1109/EIConCIT.2018.8878538","DOIUrl":"https://doi.org/10.1109/EIConCIT.2018.8878538","url":null,"abstract":"Missing data is one of the problems in classification that can reduce classification accuracy. This paper mainly studies the technique of fixing missing data by using deletion instances, mean imputation and median imputation. We use Naive Bayes based method which is used in many classification techniques. We proposed the improvement of the Naive Bayes formula into the Naive Bayes Logarithm (NBL) formula to anticipate the final result which can obtain zero for the prior probability of classifier. If the the prior probability of classifier obtained zero it will result failure in the classification process. In this research, we use Web-Kb dataset that has been used in other classification method. By Naive Bayes Logarithm, we study the effect of missing data on the classification accuracy in different types of method of fixing data. The results show the documents can be classified well in average 84.909% when using mean imputation, median imputation and deletion instances. It concludes that Naive Bayes Logarithm is reliable in the classification of documents.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122199594","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 : 2018-11-01DOI: 10.1109/eiconcit.2018.8878612
{"title":"[EIConCIT 2018 Keynote Speaker Biographies]","authors":"","doi":"10.1109/eiconcit.2018.8878612","DOIUrl":"https://doi.org/10.1109/eiconcit.2018.8878612","url":null,"abstract":"","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116488648","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 : 2018-11-01DOI: 10.1109/eiconcit.2018.8878643
{"title":"[EIConCIT 2018 Copyright notice]","authors":"","doi":"10.1109/eiconcit.2018.8878643","DOIUrl":"https://doi.org/10.1109/eiconcit.2018.8878643","url":null,"abstract":"","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114959942","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 : 2018-11-01DOI: 10.1109/eiconcit.2018.8878590
{"title":"[EIConCIT 2018 Title Page]","authors":"","doi":"10.1109/eiconcit.2018.8878590","DOIUrl":"https://doi.org/10.1109/eiconcit.2018.8878590","url":null,"abstract":"","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115094602","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 : 2018-11-01DOI: 10.1109/EIConCIT.2018.8878595
Muliati, Irwan Gani, Emmilya Umma Aziza Gaffar, Haviluddin, A. F. O. Gaffar
Poverty alleviation is still a major problem for many international and developing countries. In a weak economic situation, low-income households are very vulnerable to poverty. Therefore, the study of poverty is very important for various economic development plans. Analysis of various social aspects can conclude that poverty can be a function of the diminished ability of a person to live the type of life they choose. This study chooses aspects of health, human capital, and economic well-being as latent variables which are assumed to influence poverty. The relationship between variables modeled by the structure equation through the heuristic network. The purpose of this study is to evaluate the effect of all latent variables (also called independent variables) on poverty. This evaluation is carried out on all the final coefficients of the trained network. The results of the study have shown that the heuristic network significant enough to be used as a representation of the structural equation model. It has proven by MAPE of small enough. The results of this study also have shown that all independent variables did not interdependent. Indicator variables of health did not give any influence on poverty. This concluded that only indicator variables of human capital and economic well-being influence poverty. The results of this study have also shown that only food consumption (as one of indicator variable of economic well-being) which have a negative influence on poverty.
{"title":"Measurement of Health, Human Capital, and Economic Welfare at The Poverty Level Influences using Heuristic Network Approach","authors":"Muliati, Irwan Gani, Emmilya Umma Aziza Gaffar, Haviluddin, A. F. O. Gaffar","doi":"10.1109/EIConCIT.2018.8878595","DOIUrl":"https://doi.org/10.1109/EIConCIT.2018.8878595","url":null,"abstract":"Poverty alleviation is still a major problem for many international and developing countries. In a weak economic situation, low-income households are very vulnerable to poverty. Therefore, the study of poverty is very important for various economic development plans. Analysis of various social aspects can conclude that poverty can be a function of the diminished ability of a person to live the type of life they choose. This study chooses aspects of health, human capital, and economic well-being as latent variables which are assumed to influence poverty. The relationship between variables modeled by the structure equation through the heuristic network. The purpose of this study is to evaluate the effect of all latent variables (also called independent variables) on poverty. This evaluation is carried out on all the final coefficients of the trained network. The results of the study have shown that the heuristic network significant enough to be used as a representation of the structural equation model. It has proven by MAPE of small enough. The results of this study also have shown that all independent variables did not interdependent. Indicator variables of health did not give any influence on poverty. This concluded that only indicator variables of human capital and economic well-being influence poverty. The results of this study have also shown that only food consumption (as one of indicator variable of economic well-being) which have a negative influence on poverty.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129522359","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 : 2018-11-01DOI: 10.1109/EIConCIT.2018.8878536
D. Wulandari, Fajrin Nurman Arifin, Gayatri Dwi Santika
Distribution is an important logistical problem in tape commodities because it has a short expiration time that requires speed and accuracy in shipping. This research collaborates implementation two methods. These are North West corner (NWC) and stepping stone. These methods make distribution scheduling model from many sources to destinations with minimum cost. This case has many steps. The first step is initial feasible solution with NWC. NWC is used this case because simple and fastest method for solving problem. NWC does not observe the cost of each shipping line in procedure. The second step revised with try and error the plan using stepping stone for optimization. In this research, collaboration these methods can reduce total cost of distribution equal to Rp.266.050. In fact, total distribution cost is Rp.317.500. After calculation, we can save cost Rp.51.450. Determination of the first source and destination in the North-west corner cell is greatly affect. If the first source and the destination have a small cost so the result is better. Stepping stone find optimization in second iteration because all of closed lanes have positive value. A positive value in repair index means that when given an allocation it will causing an increase in transportation costs. The allocation of product does not need to be changed because it will increase the cost of transportation so that the stepping stone work is completed. Percentage of differences is a formula to derive efficiency comparison between initial solution and optimal solution is 0.45%.
{"title":"Implementation North West Corner and Stepping Stone Methods for Solving Logistical Distribution Problem in Tape Production","authors":"D. Wulandari, Fajrin Nurman Arifin, Gayatri Dwi Santika","doi":"10.1109/EIConCIT.2018.8878536","DOIUrl":"https://doi.org/10.1109/EIConCIT.2018.8878536","url":null,"abstract":"Distribution is an important logistical problem in tape commodities because it has a short expiration time that requires speed and accuracy in shipping. This research collaborates implementation two methods. These are North West corner (NWC) and stepping stone. These methods make distribution scheduling model from many sources to destinations with minimum cost. This case has many steps. The first step is initial feasible solution with NWC. NWC is used this case because simple and fastest method for solving problem. NWC does not observe the cost of each shipping line in procedure. The second step revised with try and error the plan using stepping stone for optimization. In this research, collaboration these methods can reduce total cost of distribution equal to Rp.266.050. In fact, total distribution cost is Rp.317.500. After calculation, we can save cost Rp.51.450. Determination of the first source and destination in the North-west corner cell is greatly affect. If the first source and the destination have a small cost so the result is better. Stepping stone find optimization in second iteration because all of closed lanes have positive value. A positive value in repair index means that when given an allocation it will causing an increase in transportation costs. The allocation of product does not need to be changed because it will increase the cost of transportation so that the stepping stone work is completed. Percentage of differences is a formula to derive efficiency comparison between initial solution and optimal solution is 0.45%.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130682324","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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