{"title":"Implementasi Algoritma C4.5 Untuk Tes Kepribadian Penerimaan Karyawan Di Dinas Perhubungan Provinsi Sulawesi Tengah","authors":"Andi Oktafiqurahman, K. Kusrini, Asro Nasiri","doi":"10.30646/tikomsin.v11i1.719","DOIUrl":null,"url":null,"abstract":"The employee who has bad performance in working can influence the other employee to disturb many jobs. The purpose of this research is creating prediction system which it makes easier for HRD to select prospective employees who have appropriate personality based on the position, by utilizing the C4.5 algorithm known to be the personality of employees of the Central Sulawesi Provincial Transportation Office with a level of accuracy in the implementation of the C.45 algorithm. Testing using the confusion matrix, obtained a system accuracy of 79.167%. ","PeriodicalId":189908,"journal":{"name":"Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30646/tikomsin.v11i1.719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The employee who has bad performance in working can influence the other employee to disturb many jobs. The purpose of this research is creating prediction system which it makes easier for HRD to select prospective employees who have appropriate personality based on the position, by utilizing the C4.5 algorithm known to be the personality of employees of the Central Sulawesi Provincial Transportation Office with a level of accuracy in the implementation of the C.45 algorithm. Testing using the confusion matrix, obtained a system accuracy of 79.167%.