Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Sinus
Ruvyanto Dwi Nugroho
STMIK Sinar Nusantara Surakarta
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Sistem Penunjang Keputusan Menggunakan Algoritma Naive Bayes Pada konsep Human Resource Information System (HRIS) (Studi kasus :Penerusan Kontrak Kerja Karyawan di PT. XYZ) Dwi Remawati; Paulus Harsadi; Ruvyanto Dwi Nugroho
Jurnal Ilmiah SINUS Vol 18, No 1 (2020): Vol 18, No 1, Januari 2020
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (995.755 KB) | DOI: 10.30646/sinus.v18i1.440

Abstract

One of the valuable assets in a company is human resources (HR).  Human Resource Information System (HRIS) has emerged as one of the drivers of competitiveadvantage and strategic decision making tool. One of the HRIS task is employee recruitment. Employees become an important role. Therefore, this research is conducted forclassification of employee status determination using the Naïve Bayes methods.  One of the duties of employees is to provide service to customer in the process of purchasing goods until the payment transaction process directly. Because of the large number of contract employees at the time of certain events, it requires companies to select every three months for the continuation of the work contract period for employees according to store needs so that the company's employee payroll expenses do not exceed the budget. One of the criteria is for being able to work in flexible groups between the ages of 17 and 25 for contract employees with a minimum of high school or vocational education. The purposes of this study are to design and build a Decision Support System application for the Continuation of Employee Employment Contracts Using the Naïve Bayes Method at PT. XYZ Retail. The result of the research is the application using the naïve bayes method with an accuracy rate of 90%. 
Co-Authors Dwi Remawati paulus harsadi