SISTEM PENDUKUNG KEPUTUSAN UNTUK SELEKSI PENERIMAAN PEGAWAI BARU DENGAN MENGGUNAKAN METODE TOPSIS ( TECHNIQUE FOR ODER PREFERENCE BY SIMILARITY IDEAL)

Nur Bani Ischak, NIM. 13650082 (2018) SISTEM PENDUKUNG KEPUTUSAN UNTUK SELEKSI PENERIMAAN PEGAWAI BARU DENGAN MENGGUNAKAN METODE TOPSIS ( TECHNIQUE FOR ODER PREFERENCE BY SIMILARITY IDEAL). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Human Resources (HR) is the most important element for the organization. Without the human element as an employee, the organization's goals will not be achieved as expected. The success of a process of achieving organizational goals that have been determined is highly dependent on the human element who leads and carries out the tasks and activities carried out to achieve the objectives. In this digital era, technology and communication are growing rapidly, so the decision support system is really important for the smooth process of selecting new employees. This decision support system is used with the Technique for Order by Similarity Ideal (TOPSIS) method. This topsis method is used because the concept is simple and easy to understand. Criteria are used as assessment indicators and alternatives are used as support to determine decisions. The development of this software system is used in the waterfall method with five stages, namely analysis, design, implementation, testing and maintenance. The testing technique that is used in developing this decision support system is blackbox testing.. Research and testing have been carried out, and the decision support system has been running properly. The system displays and stores rankings based on calculations with the TOPSIS method. Ranking is sorted from the largest value to the smallest value. The calculation results contained in the system are in accordance with the calculations performed manually. Determination of assessment criteria in the system can be changed at any time according to the needs of the company or agency. So, overall this system displays data on new employee recommendations easily and quickly.

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