Implementasi Metode Weighted Aggregated Sum Product Assesment (WASPAS) Dalam Pemilihan Karyawan Terbaik Berbasis Sistem Pendukung Keputusan

Masitah Handayani, Nasrun Marpaung, Syartika Anggraini

Abstract


One of the human resources (HR) owned by an agency is employees. Employees are one of the important aspects in an agency. The management of human resources (HR) of a company greatly influences many aspects of determining the work success of the agency. One of the most important in HR management in an agency is the selection of the best employees periodically so that the selected ones will be given an award in the form of bonuses to motivate employees to improve their performance and loyalty. The large number of employees in an agency makes the process of selecting the best employees less effective if done manually. This is due to a comparison between many criteria with many alternatives. WASPAS method is one method that can solve problems in the process of selecting employees. The highest Qi value is Q1 alternative value that will be recommended to be the best employee, which is 0,85.

Full Text:

PDF

References


Asep Abdul Wahid, et al. (2012). Sistem Pendukung Keputusan Penentuan Jumlah Pemesanan Barang. Jurnal Algoritma Sekolah Tinggi Teknologi Garut, 9(22).

Barus, Safrizal dkk (2018). Sistem Pendukung Keputusan Pengangkatan Guru Tetap Menerapkan Metode Weight Aggregated Sum Product Assesment (WASPAS). MEDIA INFORMATIKA BUDIDARMA, 2(2) : 10-15

Dwi Gandika Supartha dan Purnama Dewi. (2014). Sistem Pendukung Keputusan Penentuan Jurusan pada SMK Kertha Wisata Denpasar Menggunakan Fuzzy SAW. JURNAL NASIONAL PENDIDIKAN TEKNIK INFORMATIKA (JANAPATI), 3(2).

Marpaung, Nasrun (2017). Penerapan Metode Simple Additive Weighting Pada Sistem Pendukung Keputusan Untuk Menentukan Kenaikan Gaji Karyawan. JURTEKSI, 4(2) : 171-178.

Simanjuntak, Paulus dkk (2018). Penentuan Kayu Terbaik Untuk Bahan Gitar Dengan Metode Weighted Aggregated Sum Product Assesment (WASPAS). JURIKOM, 5(1) : 36-42




DOI: http://dx.doi.org/10.30645/senaris.v1i0.122

Refbacks

  • There are currently no refbacks.


&nbsp