Himayati Himayati, Ni Wayan Switrayni, D. Komalasari, Nurul Fitriyani
{"title":"Analisis Rotasi Ortogonal pada Teknik Analisis Faktor Menggunakan Metode Procrustes","authors":"Himayati Himayati, Ni Wayan Switrayni, D. Komalasari, Nurul Fitriyani","doi":"10.29303/emj.v1i2.66","DOIUrl":null,"url":null,"abstract":"Factor analysis is a multivariate statistical method that tries to explain the relationship between a number of independent variables by grouping these variables into factors. With this grouping, the existing variables will be easier to interpret. In increasing the power of factor interpretation, a matrix loading factor transformation must be performed. The transformation can be done by choosing the method that is in orthogonal rotation, the varimax or quartimax or equamax method. In order to find out which rotation techniques is the most appropriate, the minimum square distance values () generated from the procrustes method used. In this study three data were used from the results of the questionnaire, for data I obtain the value of the minimum distance squared with a varimax rotation that is with ; for data II obtain the value of the minimum distance squared with a quartimax rotation that is with ; for data III obtain the value of the minimum distance squared with a varimax rotation that is with .","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"126 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EIGEN MATHEMATICS JOURNAL","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29303/emj.v1i2.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Factor analysis is a multivariate statistical method that tries to explain the relationship between a number of independent variables by grouping these variables into factors. With this grouping, the existing variables will be easier to interpret. In increasing the power of factor interpretation, a matrix loading factor transformation must be performed. The transformation can be done by choosing the method that is in orthogonal rotation, the varimax or quartimax or equamax method. In order to find out which rotation techniques is the most appropriate, the minimum square distance values () generated from the procrustes method used. In this study three data were used from the results of the questionnaire, for data I obtain the value of the minimum distance squared with a varimax rotation that is with ; for data II obtain the value of the minimum distance squared with a quartimax rotation that is with ; for data III obtain the value of the minimum distance squared with a varimax rotation that is with .