Pub Date : 2016-10-12DOI: 10.1109/ICTS.2016.7910274
Oscar Karnalim
Even though there are various source code plagiarism detection approaches, most of them only concern with low-level plagiarism attack with an assumption that plagiarism is only conducted by students who are not proficient in programming. However, plagiarism is often conducted not only due to student incapability, but also because of bad time management. Thus, high-level plagiarism attack should be detected and evaluated. This paper proposes source code plagiarism detection approach which can detect most introductory-programming-course plagiarism attacks at any level by utilizing low-level instructions instead of source code tokens. Several mechanisms are also introduced to improve its effectiveness such as instruction generalization, instruction reinterpretation, method-based comparison, and method linearization. Since low-level instruction is a language-dependent feature, Java is selected as target programming language with bytecode as its low-level instruction. Based on evaluation, it can be concluded that our approach is more effective to detect most plagiarism attack types than raw source code approach on introductory programming course. This evaluation is based on plagiarism attack types that are collected through controlled experiment.
{"title":"Detecting source code plagiarism on introductory programming course assignments using a bytecode approach","authors":"Oscar Karnalim","doi":"10.1109/ICTS.2016.7910274","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910274","url":null,"abstract":"Even though there are various source code plagiarism detection approaches, most of them only concern with low-level plagiarism attack with an assumption that plagiarism is only conducted by students who are not proficient in programming. However, plagiarism is often conducted not only due to student incapability, but also because of bad time management. Thus, high-level plagiarism attack should be detected and evaluated. This paper proposes source code plagiarism detection approach which can detect most introductory-programming-course plagiarism attacks at any level by utilizing low-level instructions instead of source code tokens. Several mechanisms are also introduced to improve its effectiveness such as instruction generalization, instruction reinterpretation, method-based comparison, and method linearization. Since low-level instruction is a language-dependent feature, Java is selected as target programming language with bytecode as its low-level instruction. Based on evaluation, it can be concluded that our approach is more effective to detect most plagiarism attack types than raw source code approach on introductory programming course. This evaluation is based on plagiarism attack types that are collected through controlled experiment.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127101709","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910272
Muhtadin, Achmad Rizal Muttaqin, S. Sumpeno
Communication between man and machine is a challenging subject. In general, the communication between man and machine is done with rigid language (inhuman). Many scientists are trying to create a way of communication between humans and machines charmer, more personal and interactive. This paper presents the results of research work that implements interactive communication between humans and machines (robots). Communication becomes more personal by using face detection to the speaker (human). Communication is also done with more interactive by adding the ability for robots to communicate using Indonesian language. We utilize the NAO robot as a machine that can interact with humans. We employ speech Engine System consisted of Speech to Text, dialog machine, and Text to Speech which make NAO Robot can speak and understand simple human speech in Indonesian Language. The resulted system was able to perform face detection continuously on angles of range between 0° and 30°, detect human speech accurately by 80.45%, and give response to human speech appropriately by 47.58%.
{"title":"Implementation of face detection and recognition of Indonesian language in communication between humans and robots","authors":"Muhtadin, Achmad Rizal Muttaqin, S. Sumpeno","doi":"10.1109/ICTS.2016.7910272","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910272","url":null,"abstract":"Communication between man and machine is a challenging subject. In general, the communication between man and machine is done with rigid language (inhuman). Many scientists are trying to create a way of communication between humans and machines charmer, more personal and interactive. This paper presents the results of research work that implements interactive communication between humans and machines (robots). Communication becomes more personal by using face detection to the speaker (human). Communication is also done with more interactive by adding the ability for robots to communicate using Indonesian language. We utilize the NAO robot as a machine that can interact with humans. We employ speech Engine System consisted of Speech to Text, dialog machine, and Text to Speech which make NAO Robot can speak and understand simple human speech in Indonesian Language. The resulted system was able to perform face detection continuously on angles of range between 0° and 30°, detect human speech accurately by 80.45%, and give response to human speech appropriately by 47.58%.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127100854","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910287
T. M. S. Mulyana
Noise is a problem that is often encountered when separating the object from the background in the binary image. Noise may occur in the background and the object, can be spot or patchy and the tassel is connected to the object. The research segmentation of pupil object from eye image, tries to using non-linear spatial filtering of mode to reduce noise in the binary image. Using this filtering at the binary image, can be reduced the both of black noise at the background and the white noise at the object image. Also reduce spot noise and tassel noise.
{"title":"Reduce noise in the binary image using non linear spatial filtering of mode","authors":"T. M. S. Mulyana","doi":"10.1109/ICTS.2016.7910287","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910287","url":null,"abstract":"Noise is a problem that is often encountered when separating the object from the background in the binary image. Noise may occur in the background and the object, can be spot or patchy and the tassel is connected to the object. The research segmentation of pupil object from eye image, tries to using non-linear spatial filtering of mode to reduce noise in the binary image. Using this filtering at the binary image, can be reduced the both of black noise at the background and the white noise at the object image. Also reduce spot noise and tassel noise.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126185864","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910277
A. Yunanto, D. Herumurti
Face recognition is an important area in biometrics and computer vision. A lot of feature extraction can handle face recognition method such as checking pixel neighbor. Local Binary Pattern, Local Graph Structure, and Symmetric Local Graph Structure are an operator of the feature extraction. This research called Extended Symmetric Local Graph Structure which it is an improvement operator from SLGS to build more symmetric neighbor. The result of ESLGS has average accuracy 84.24% in one until five retrieval similarity of YALE dataset image and 80.59% in one until five retrieval similarity of ORL dataset image. The conclusion indicates that our proposed operator has more accuracy than LBP, LGS and SLGS operator. Advantage of proposed method is to provide better performance in accuracy and complexity than other operator.
{"title":"Face recognition based on Extended Symmetric Local Graph Structure","authors":"A. Yunanto, D. Herumurti","doi":"10.1109/ICTS.2016.7910277","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910277","url":null,"abstract":"Face recognition is an important area in biometrics and computer vision. A lot of feature extraction can handle face recognition method such as checking pixel neighbor. Local Binary Pattern, Local Graph Structure, and Symmetric Local Graph Structure are an operator of the feature extraction. This research called Extended Symmetric Local Graph Structure which it is an improvement operator from SLGS to build more symmetric neighbor. The result of ESLGS has average accuracy 84.24% in one until five retrieval similarity of YALE dataset image and 80.59% in one until five retrieval similarity of ORL dataset image. The conclusion indicates that our proposed operator has more accuracy than LBP, LGS and SLGS operator. Advantage of proposed method is to provide better performance in accuracy and complexity than other operator.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115508197","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910305
Kadek Aldrin Wiguna, R. Sarno, Nurul Fajrin Ariyani
The process of Solar Farm site selection is a complex issue because it involves many criteria and many factors that are classified as problem Multi-Criteria Decision Making (MCDM). With computer technology, it is possible to analyze systematically the MCDM complex problems through computational intelligence techniques. Many methods have been developed to solve optimization problems of Solar Farm site selection such as Fuzzy AHP - PROMETHEE. However, these methods have not integrated directly into GIS software. In this research this methods will be integrated into GIS software especially ArcGIS as a toolbox. With this toolbox, determining the location of the solar farm will be more effective and easily. This research provide the methodology and decision support so that decision makers can more easily and quickly to determine the best location of solar farm.
{"title":"Optimization Solar Farm site selection using Multi-Criteria Decision Making Fuzzy AHP and PROMETHEE: case study in Bali","authors":"Kadek Aldrin Wiguna, R. Sarno, Nurul Fajrin Ariyani","doi":"10.1109/ICTS.2016.7910305","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910305","url":null,"abstract":"The process of Solar Farm site selection is a complex issue because it involves many criteria and many factors that are classified as problem Multi-Criteria Decision Making (MCDM). With computer technology, it is possible to analyze systematically the MCDM complex problems through computational intelligence techniques. Many methods have been developed to solve optimization problems of Solar Farm site selection such as Fuzzy AHP - PROMETHEE. However, these methods have not integrated directly into GIS software. In this research this methods will be integrated into GIS software especially ArcGIS as a toolbox. With this toolbox, determining the location of the solar farm will be more effective and easily. This research provide the methodology and decision support so that decision makers can more easily and quickly to determine the best location of solar farm.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122300855","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910270
Ridho Rahman Hariadi, Imam Kuswardayan
Unity Leap Motion SDK is a tool which can be an alternative way to control input and interact with computer without touching. In this research, we use leap motion controller to develop an application to learn Indonesian traditional musical instrument such as: angklung, saron, kenong and kendang. This application is named VIMi (Virtual Indonesian Musical Instrument). Leap Motion Controller itself uses motion capture to help user interact with computer. We implemented VIMi using leap motion, laptop and speaker. Leap motion was used to capture the user's motion, laptop for the view of Indonesian traditional musical instrument, and speaker for the output sound. This research aims to develop an interactive learning media and introduce Indonesian traditional musical instrument.
{"title":"Design and implementation of Virtual Indonesian Musical Instrument (VIMi) application using Leap Motion Controller","authors":"Ridho Rahman Hariadi, Imam Kuswardayan","doi":"10.1109/ICTS.2016.7910270","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910270","url":null,"abstract":"Unity Leap Motion SDK is a tool which can be an alternative way to control input and interact with computer without touching. In this research, we use leap motion controller to develop an application to learn Indonesian traditional musical instrument such as: angklung, saron, kenong and kendang. This application is named VIMi (Virtual Indonesian Musical Instrument). Leap Motion Controller itself uses motion capture to help user interact with computer. We implemented VIMi using leap motion, laptop and speaker. Leap motion was used to capture the user's motion, laptop for the view of Indonesian traditional musical instrument, and speaker for the output sound. This research aims to develop an interactive learning media and introduce Indonesian traditional musical instrument.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122066722","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910276
Wanvy Arifha Saputra, D. Herumurti
Image of tuna as bigeye, skipjack and yellowfin have very high color similarity, but in the texture and shape can be differentiated. It requires a method to perform feature extraction of bigeye, skipjack and yellowfin appropriately, so the results on a classification of tuna have a high accurate rate. We propose a method to integrate gray level co-occurrence matrix (GLCM) and geometric feature extraction of region of interest (ROI) for classifying tuna. To measure the texture of tuna is require making region in an image using centroid as a parameter of center boundary to help determine head, body and tail. Thus, maximally get its extraction and produce an accurate classification. The experiment results show the integration GLCM and geometric shape feature extraction is successful and classify very well the image of bigeye, skipjack and yellowfin with 86.67% accurate, 0.8% Kappa, 0.11% MAE, 0.28% RMSE, 24.71% RAE and 58.95% RRSE using 10-fold cross-validation of the entire dataset.
{"title":"Integration GLCM and geometric feature extraction of region of interest for classifying tuna","authors":"Wanvy Arifha Saputra, D. Herumurti","doi":"10.1109/ICTS.2016.7910276","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910276","url":null,"abstract":"Image of tuna as bigeye, skipjack and yellowfin have very high color similarity, but in the texture and shape can be differentiated. It requires a method to perform feature extraction of bigeye, skipjack and yellowfin appropriately, so the results on a classification of tuna have a high accurate rate. We propose a method to integrate gray level co-occurrence matrix (GLCM) and geometric feature extraction of region of interest (ROI) for classifying tuna. To measure the texture of tuna is require making region in an image using centroid as a parameter of center boundary to help determine head, body and tail. Thus, maximally get its extraction and produce an accurate classification. The experiment results show the integration GLCM and geometric shape feature extraction is successful and classify very well the image of bigeye, skipjack and yellowfin with 86.67% accurate, 0.8% Kappa, 0.11% MAE, 0.28% RMSE, 24.71% RAE and 58.95% RRSE using 10-fold cross-validation of the entire dataset.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127001402","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910297
N. Suciati, Afdhal Basith Anugrah, C. Fatichah, H. Tjandrasa, A. Arifin, D. Purwitasari, D. A. Navastara
Iris is unique for each person, so that it can be used as one alternative solution for human identification. In this study, an iris recognition system is developed to automatically identify a person by using eye image data. Firstly, iris area of eye image is detected using Canny Edge Detection and Hough Transform methods. Secondly, texture feature of iris image is extracted using statistical moments of Wavelet Transform. Furthermore, the texture feature representation is recognized using Support Vector Machine classifier method. Experiment on CASIA eye image dataset gives good recognition rate, that is 93.5%.
{"title":"Feature extraction using statistical moments of wavelet transform for iris recognition","authors":"N. Suciati, Afdhal Basith Anugrah, C. Fatichah, H. Tjandrasa, A. Arifin, D. Purwitasari, D. A. Navastara","doi":"10.1109/ICTS.2016.7910297","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910297","url":null,"abstract":"Iris is unique for each person, so that it can be used as one alternative solution for human identification. In this study, an iris recognition system is developed to automatically identify a person by using eye image data. Firstly, iris area of eye image is detected using Canny Edge Detection and Hough Transform methods. Secondly, texture feature of iris image is extracted using statistical moments of Wavelet Transform. Furthermore, the texture feature representation is recognized using Support Vector Machine classifier method. Experiment on CASIA eye image dataset gives good recognition rate, that is 93.5%.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123210081","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910267
A. Putra, R. Sarno, E. Suryani
Electrical energy is one important factor in the development of every nation, including Indonesia. Electrical energy has an important role in the development of both the economic and social aspects. Remember so large and important energy benefits of electricity while the power generation energy sources, especially those from non renewable resource limited presence, and to ensure the sustainability of energy sources is necessary pursued strategic steps to support the provision of electrical energy in an optimal and affordable. This paper explores how dynamic modeling can help generate future scenarios of electricity consumption. This modeling study the structure of complex systems and to test different scenarios. This paper have 3 Scenario such as, normal condition, optimistic condition(growth increase 0.5% per month), and pessimist condition(growth decrease 0.5% per month). Also a large number of variables, which affect the behavior could be considered. Power producers, suppliers and distributors requires knowledge of the total consumption to support their business, such as investment decisions of new substations. Modeling and simulation of the results obtained to analyze the electrical energy demand Social and Public sector based on current conditions and forecast electricity demand in the field of Social and Public in the future and how the availability of electricity in the future.
{"title":"Dynamics simulation model of demand and supply electricity energy public facilities and social sector case study East Java","authors":"A. Putra, R. Sarno, E. Suryani","doi":"10.1109/ICTS.2016.7910267","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910267","url":null,"abstract":"Electrical energy is one important factor in the development of every nation, including Indonesia. Electrical energy has an important role in the development of both the economic and social aspects. Remember so large and important energy benefits of electricity while the power generation energy sources, especially those from non renewable resource limited presence, and to ensure the sustainability of energy sources is necessary pursued strategic steps to support the provision of electrical energy in an optimal and affordable. This paper explores how dynamic modeling can help generate future scenarios of electricity consumption. This modeling study the structure of complex systems and to test different scenarios. This paper have 3 Scenario such as, normal condition, optimistic condition(growth increase 0.5% per month), and pessimist condition(growth decrease 0.5% per month). Also a large number of variables, which affect the behavior could be considered. Power producers, suppliers and distributors requires knowledge of the total consumption to support their business, such as investment decisions of new substations. Modeling and simulation of the results obtained to analyze the electrical energy demand Social and Public sector based on current conditions and forecast electricity demand in the field of Social and Public in the future and how the availability of electricity in the future.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134212886","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 : 1900-01-01DOI: 10.1109/ICTS.2016.7910303
A. H. Utomo, R. Sarno, R. V. Ginardi
Dynamic wDAG Similarity algorithm can be applied to sugarcane annotation. At first, we have to make a wDAG structure of many different varieties of sugarcane. We also have to make wDAG of sugarcane that will be annotated. Then, we have to calculate the similarity between wDAG types of sugarcane that will be annotated and wDAG of all the existing types of sugarcane. This similarity calculation results will present sequence similarities ranging from the most similar to the most distant from sugarcane varieties were annotated. This Dynamic wDAG Similarity algorithm has difference compared with the previous wDAG Similarity algorithm. WDAG used in this research has the node labeled, arc labeled and arc weighted, where the weight of the arc can be changed dynamically. This research fixes the previous studies of static wDAG, in which the weight values on the arc of wDAG can not be changed. On Dynamic wDAG, the weight on each arc is based on the fuzzy calculations that show the tendency of sugarcane varieties were annotated. And the fuzzy value is calculated based on agronomic traits of sugarcane to be annotated. Leaf node is the part of wDAG that will be compared first. The similarity calculation result between the two wDAG is affected by data on a leaf node to be compared and the weights of the arcs. The result shows that this method gained the average of Precision of 96%, the average of Recall of 88.5%, and the average of Accuracy of 96%.
{"title":"Sugarcane variety identification using Dynamic Weighted Directed Acyclic Graph Similarity","authors":"A. H. Utomo, R. Sarno, R. V. Ginardi","doi":"10.1109/ICTS.2016.7910303","DOIUrl":"https://doi.org/10.1109/ICTS.2016.7910303","url":null,"abstract":"Dynamic wDAG Similarity algorithm can be applied to sugarcane annotation. At first, we have to make a wDAG structure of many different varieties of sugarcane. We also have to make wDAG of sugarcane that will be annotated. Then, we have to calculate the similarity between wDAG types of sugarcane that will be annotated and wDAG of all the existing types of sugarcane. This similarity calculation results will present sequence similarities ranging from the most similar to the most distant from sugarcane varieties were annotated. This Dynamic wDAG Similarity algorithm has difference compared with the previous wDAG Similarity algorithm. WDAG used in this research has the node labeled, arc labeled and arc weighted, where the weight of the arc can be changed dynamically. This research fixes the previous studies of static wDAG, in which the weight values on the arc of wDAG can not be changed. On Dynamic wDAG, the weight on each arc is based on the fuzzy calculations that show the tendency of sugarcane varieties were annotated. And the fuzzy value is calculated based on agronomic traits of sugarcane to be annotated. Leaf node is the part of wDAG that will be compared first. The similarity calculation result between the two wDAG is affected by data on a leaf node to be compared and the weights of the arcs. The result shows that this method gained the average of Precision of 96%, the average of Recall of 88.5%, and the average of Accuracy of 96%.","PeriodicalId":177275,"journal":{"name":"2016 International Conference on Information & Communication Technology and Systems (ICTS)","volume":"530 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133880097","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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