Kristin D R Sianipar, Septri Wanti Siahaan, I. Parlina
{"title":"神经网络在反向传播法预测学生英语理解水平中的应用","authors":"Kristin D R Sianipar, Septri Wanti Siahaan, I. Parlina","doi":"10.30596/jcositte.v1i2.5072","DOIUrl":null,"url":null,"abstract":"English is a language that unites humans in communicating with others. The existence of language differences can make it difficult for people to understand each other in dialogue. Therefore, the role of English is very useful to unite human communication. In this case, researchers make research to predict the level of understanding of students in English. Predicting the level of understanding of students in English is needed to determine the level of ability or understanding of students in English so that students can further enhance student abilities. English is very necessary for students to support a bright future. In this study implements the Artificial Neural Network in conducting research and applying the bacpropagation method in it. To complete this study, researchers used several criteria, namely: Reading References, Hearing from the Environment, Practicing, Utilizing Technology. Of the four criteria using the backpropagation method is useful for training in predicting the level of understanding of students in English. The results of this research test get that the level of understanding of students in English is with the level of accuracy and architecture Keyword : Artificial Neural Network; Prediction; English; Level of Understanding; Backpropagation. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Corresponding Author: Septri Wanti Siahaan, Department of Informatics Engineering STIKOM Tunas Bangsa Pematangsiantar Jl. Jend. Sudirman, Blok. A, No. 1, 2, dan 3, Pematangsiantar, 21143, Sumatera Utara, Indonesia. Email : septriwanti26@gmail.com Article history: Received Aug 21, 2020 Revised Aug 27, 2020 Accepted Sep 01, 2020","PeriodicalId":202535,"journal":{"name":"Journal of Computer Science, Information Technologi and Telecommunication Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Implementation of Artificial Neural Networks In Predicting Students ‘English Understanding Level Using The Backpropagation Method\",\"authors\":\"Kristin D R Sianipar, Septri Wanti Siahaan, I. Parlina\",\"doi\":\"10.30596/jcositte.v1i2.5072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"English is a language that unites humans in communicating with others. The existence of language differences can make it difficult for people to understand each other in dialogue. Therefore, the role of English is very useful to unite human communication. In this case, researchers make research to predict the level of understanding of students in English. Predicting the level of understanding of students in English is needed to determine the level of ability or understanding of students in English so that students can further enhance student abilities. English is very necessary for students to support a bright future. In this study implements the Artificial Neural Network in conducting research and applying the bacpropagation method in it. To complete this study, researchers used several criteria, namely: Reading References, Hearing from the Environment, Practicing, Utilizing Technology. Of the four criteria using the backpropagation method is useful for training in predicting the level of understanding of students in English. The results of this research test get that the level of understanding of students in English is with the level of accuracy and architecture Keyword : Artificial Neural Network; Prediction; English; Level of Understanding; Backpropagation. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Corresponding Author: Septri Wanti Siahaan, Department of Informatics Engineering STIKOM Tunas Bangsa Pematangsiantar Jl. Jend. Sudirman, Blok. A, No. 1, 2, dan 3, Pematangsiantar, 21143, Sumatera Utara, Indonesia. Email : septriwanti26@gmail.com Article history: Received Aug 21, 2020 Revised Aug 27, 2020 Accepted Sep 01, 2020\",\"PeriodicalId\":202535,\"journal\":{\"name\":\"Journal of Computer Science, Information Technologi and Telecommunication Engineering\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer Science, Information Technologi and Telecommunication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30596/jcositte.v1i2.5072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Science, Information Technologi and Telecommunication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30596/jcositte.v1i2.5072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of Artificial Neural Networks In Predicting Students ‘English Understanding Level Using The Backpropagation Method
English is a language that unites humans in communicating with others. The existence of language differences can make it difficult for people to understand each other in dialogue. Therefore, the role of English is very useful to unite human communication. In this case, researchers make research to predict the level of understanding of students in English. Predicting the level of understanding of students in English is needed to determine the level of ability or understanding of students in English so that students can further enhance student abilities. English is very necessary for students to support a bright future. In this study implements the Artificial Neural Network in conducting research and applying the bacpropagation method in it. To complete this study, researchers used several criteria, namely: Reading References, Hearing from the Environment, Practicing, Utilizing Technology. Of the four criteria using the backpropagation method is useful for training in predicting the level of understanding of students in English. The results of this research test get that the level of understanding of students in English is with the level of accuracy and architecture Keyword : Artificial Neural Network; Prediction; English; Level of Understanding; Backpropagation. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Corresponding Author: Septri Wanti Siahaan, Department of Informatics Engineering STIKOM Tunas Bangsa Pematangsiantar Jl. Jend. Sudirman, Blok. A, No. 1, 2, dan 3, Pematangsiantar, 21143, Sumatera Utara, Indonesia. Email : septriwanti26@gmail.com Article history: Received Aug 21, 2020 Revised Aug 27, 2020 Accepted Sep 01, 2020