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Analysis of classic assumption test and multiple linear regression coefficient test for employee structural office recommendation


 
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1. Title Title of document Analysis of classic assumption test and multiple linear regression coefficient test for employee structural office recommendation
 
2. Creator Author's name, affiliation, country Debby Alita; Universitas Teknokrat Indonesia; Indonesia
 
2. Creator Author's name, affiliation, country Ade Dwi Putra; Universitas Teknokrat Indonesia; Indonesia
 
2. Creator Author's name, affiliation, country Dedi Darwis; Universitas Teknokrat Indonesia; Indonesia
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) job promotion; multiple linear regression; predictive model; structural position
 
4. Description Abstract The performance appraisal process in Religious High Court Bandar Lampung has not been carried out objectively, but rather a subjectivity element (relationship closeness). Some employees occupy structural positions but do not fulfil competence and promotion principles, so that it has an impact on providing promotion to a position in the judiciary. Multiple Linear Regression method can provide a predictive model for employee recommendations entitled to occupy positions in the agency. The method implementation using SPSS produces an equation Y = 74.177 + 0.035X1 + 0.020X2 - 0.026X3 + 0.045X4 + 0.001X5. This equation is applied to the employee performance values, and it is obtained from 40 employees 26 employees deserve to be given recommendations promotion. Regression performance testing results using 10-cross validation get the correlation coefficient value is 80.66% with MAE value of 2.24% and RMSE 3.88%, which mean has good performance.
 
5. Publisher Organizing agency, location IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2021-07-31
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier https://jurnal.ugm.ac.id/ijccs/article/view/65586
 
10. Identifier Digital Object Identifier (DOI) https://doi.org/10.22146/ijccs.65586
 
11. Source Title; vol., no. (year) IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 15, No 3 (2021): July
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions Copyright (c) 2021 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
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