Anggara Erik Dwi Primary Author mixed material bibliography Bandung Maranatha University Press 2022 Indonesia

Artikel Jurnal

hlm : 218-234 Abstract Employee performance is one element that greatly determines the quality of an organization, both government and private. Employee performance appraisal has become a routine for most companies. Performance appraisal is required for the process of salary increases, promotions, and demotions. Until this research was carried out, the processing of employee performance appraisal and evaluation at Prasama Bhakti Foundation was still done manually, so that sometimes employee promotions were carried out late or even on an inconsistent basis for each employee. Therefore, it is necessary to group data with the help of machine learning that can help predict the eligibility of an employee to get a promotion based on his performance. Classification is one method for classifying or classifying data that are arranged systematically. Decision tree and logistic regression methods are classification or grouping methods that have been widely used for solving classification problems. In this study, it will be explained how the process of processing employee performance appraisal data starts from data preparation to determine the accuracy of the decision tree model and logistic regression that is formed. The two classification models are used to predict employee performance as a recommendation for employee promotion at the Prasama Bhakti Foundation. Informatika Sistem Informasi JUTISI 24432210 Perpustakaan Teknik UPI YAI JUTISI V8N1 April 2022 JUTISI7a-018 Perpustakaan FT UPI YAI JUTISI V8N1 April 2022 JUTISI7b-018 Perpustakaan FT UPI YAI JUTISI V8N1 April 2022 cover_issue_174_en_US.png.png 59313 2023-03-01 10:20:36 2023-03-01 10:20:36 machine generated