Memilih System Engineer Terbaik Menggunakan Algoritma WP (Studi Kasus Divisi Teknikal PT Inov Perdana Teknologi)

HILMI, M DZAKI (2022) Memilih System Engineer Terbaik Menggunakan Algoritma WP (Studi Kasus Divisi Teknikal PT Inov Perdana Teknologi). S1 thesis, Universitas Mercu Buana Jakarta - Menteng.

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Abstract

Apresiasi system engineer terbaik perlu dilakukan untuk meningkatkan semangat kerja serta loyalitas engineer terhadap perusahaan. Apresiasi tersebut nantinya diharapkan berguna untuk menunjang kemajuan perusahaan.Sebelumnya pada divisi tersebut sudah ada pemlihan engineer terbaik setiap tahunnya namun penilaiannya hanya berdasarkan pada 1 kriteria yaitu total case pekerjaan selama setahun. Dengan demikian akan dirancang sebuah sistem untuk mendukung sebuah keputusan dengan metode Weighted Product (WP) dan metode Simple Additive Weighting (SAW) dengan 5 kriteria yang telah ditentukan yaitu Disiplin, Presensi, Loyalitas, Masa Kerja dan Time study. Dua metode atau algoritma tersebut akan diuji untuk mendapatkan algotima atau metode yang relevan untuk diimplementasikan kedalam sistem pendukung keputusan berbasis web ,sehingga diharapkan dapat membantu manajer teknikal dalam membuat keputusan pemilihan system engineer terbaik tiap tahun. Analisis dilaksanakan memakai level akurasi dari kedua algoritma dalam pengerjaan kasus sebagai acuan. Hasil dari level kesesuaian algoritma WP yaitu sebesar 99.999% dan algoritma SAW sebesar 99.998%, jadi demikian algoritma WP ialah metode yang paling cocok atau relevan dalam menyelesaikan pemilihan system engineer terbaik. Kata kunci: Weighted Product, Simple additive Weighting, Sistem Pendukung Keputusan, Bobot Kriteria, Alternatif. Appreciation of the best system engineers needs to be done to increase morale and engineer loyalty to the company. The appreciation is expected to be useful to support the progress of the company. Previously in the division, there was already a selection of the best engineers every year but the assessment was only based on 1 criterion, namely the total work cases for a year. Thus, a system will be designed to support a decision with the Weighted Product (WP) method and the Simple Additive Weighting (SAW) method with 5 predetermined criteria, namely Discipline, Attendance, Loyalty, Service Period, and Time study. The two methods or algorithms will be tested to obtain the relevant algorithms or methods to be implemented into a web-based decision support system so that it is expected to assist technical managers in making decisions on the selection of the best system engineer each year. The analysis was carried out using the level of accuracy of the two algorithms in working on the case as a reference. The result of the conformity level of the WP algorithm is 99.999% and the SAW algorithm is 99.998%, so the WP algorithm is the most suitable or relevant method in completing the selection of the best system engineer. Keywords: Weighted Product, Simple additive Weighting, Decision Support System, Criterion Weight, Alternative.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41518110109
Uncontrolled Keywords: Weighted Product, Simple additive Weighting, Sistem Pendukung Keputusan, Bobot Kriteria, Alternatif. Weighted Product, Simple additive Weighting, Decision Support System, Criterion Weight, Alternative.
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: Maulana Arif Hidayat
Date Deposited: 18 Aug 2022 07:11
Last Modified: 18 Aug 2022 07:11
URI: http://repository.mercubuana.ac.id/id/eprint/67944

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