{"title":"二元逻辑回归在确定某学科学生毕业影响因素中的应用","authors":"Shedriko Shedriko","doi":"10.36378/jtos.v4i1.1401","DOIUrl":null,"url":null,"abstract":"Good communication and coordination between lecturers are needed in delivering material by different lecturers to ensure the relatively uniform quality of education. Knowing the success information from several classes to predict other classes, should be completed by significant parameters used in the algorithm. This research is using a quantitative analysis method with binary logistic regression methodology in determining critical factors of train data on “Introduction to Information Technology” subject in the university of XYZ. Several statistical testing are conducted to give the expected results using software excel with Real Statistics add-ins and Orange Data Mining in testing the pass-prediction from the given data training. The successive model can also be used to classify graduation for the different subjects.","PeriodicalId":114474,"journal":{"name":"JURNAL TEKNOLOGI DAN OPEN SOURCE","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"BINARY LOGISTIC REGRESSION IN DETERMINING AFFECTING FACTORS STUDENT GRADUATION IN A SUBJECT\",\"authors\":\"Shedriko Shedriko\",\"doi\":\"10.36378/jtos.v4i1.1401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Good communication and coordination between lecturers are needed in delivering material by different lecturers to ensure the relatively uniform quality of education. Knowing the success information from several classes to predict other classes, should be completed by significant parameters used in the algorithm. This research is using a quantitative analysis method with binary logistic regression methodology in determining critical factors of train data on “Introduction to Information Technology” subject in the university of XYZ. Several statistical testing are conducted to give the expected results using software excel with Real Statistics add-ins and Orange Data Mining in testing the pass-prediction from the given data training. The successive model can also be used to classify graduation for the different subjects.\",\"PeriodicalId\":114474,\"journal\":{\"name\":\"JURNAL TEKNOLOGI DAN OPEN SOURCE\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JURNAL TEKNOLOGI DAN OPEN SOURCE\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36378/jtos.v4i1.1401\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JURNAL TEKNOLOGI DAN OPEN SOURCE","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36378/jtos.v4i1.1401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
在不同讲师的授课过程中,需要讲师之间进行良好的沟通和协调,以保证教学质量的相对统一。知道几个类的成功信息来预测其他类,需要通过算法中使用的重要参数来完成。本研究采用二元逻辑回归的定量分析方法,对XYZ大学“信息技术导论”课程的培训数据进行关键因素的确定。通过使用带有Real Statistics插件的excel软件和Orange Data Mining软件对给定数据训练的通过率预测进行了多次统计测试,得出了预期的结果。该逐次模型也可用于不同学科的毕业分类。
BINARY LOGISTIC REGRESSION IN DETERMINING AFFECTING FACTORS STUDENT GRADUATION IN A SUBJECT
Good communication and coordination between lecturers are needed in delivering material by different lecturers to ensure the relatively uniform quality of education. Knowing the success information from several classes to predict other classes, should be completed by significant parameters used in the algorithm. This research is using a quantitative analysis method with binary logistic regression methodology in determining critical factors of train data on “Introduction to Information Technology” subject in the university of XYZ. Several statistical testing are conducted to give the expected results using software excel with Real Statistics add-ins and Orange Data Mining in testing the pass-prediction from the given data training. The successive model can also be used to classify graduation for the different subjects.