SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN TERBAIK DENGAN METODE SAW PADA PT TARGET MAKMUR SENTOSA
DOI:
https://doi.org/10.31000/jika.v7i1.6899Abstrak
Kualitas dari sumber daya manusia merupakan faktor utama dalam menentukan keberhasilan perusahaan. Dengan memiliki sumber daya manusia yang sangat baik, maka perusahaan dapat menjalankan bisnisnya dengan sangat lancar serta sesuai dengan tujuan dari perusahaan. PT Target Makmur Sentosa merupakan salah satu perusahaan yang ada dijakarta yang bergerak dalam bidang. Untuk membangun kinerja dari para karyawan agar memiliki kualitas yang sangat baik, maka PT Target Makmur Sentosa melakukan pengambilan keputusan yang bertujuan untuk menentukan karyawan terbaik dengan menggunakan metode SAW. Pada penelitian ini dibuatlah sistem penilaian kepada karyawan dengan menggunakan metode saw dan memasukan nilai dari bobot kriteria seperti kehadiran, kedisiplinan, kerja sama dan tanggung jawab. Berdasarkan hasil dari penilaian yang sudah dilakukan dengan sistem metode saw, maka terpilihlah Lulik Kurnia sebagai karyawan terbaik dengan memiliki rata-rata nilai dari masing - masing kriteria seperti kehadiran, kedisiplinan, tanggung jawab dan kerjasama yang mendapatkan nilai bobot 5 serta memperoleh hasil nilai akhir rangking sebesar 1. Dengan dibuatnya sistem ini, diharapkan agar penilaian karyawan tidak dilakukan secara manual melainkan hanya memasukkan nilai dari kriteria dan penilaian dilakukan secara otomatis dari sistemnya.Referensi
Andreas, A., Elisabet, Y. A., Ahmad, K., Adi, P. N., Agus, S., Sucipto, Andino, M., Panji, A. P., Suryono, & Satria, A. (2021). sistem pendukung keputusan (p. 198).
Asdini, D., Khairat, M., & Utomo, D. P. (2022). Sistem Pendukung Keputusan Penilaian Kinerja Manajer di PT . Pos Indonesia dengan Metode WASPAS. JURIKOM (Jurnal Riset Komputer), 9(1), 41–47. https://doi.org/10.30865/jurikom.v9i1.3767
Akbar, S. M., Anugrah, G. I.,. (2022). Sistem Pendukung Keputusan Pemilihan Tempat Kos untuk Mahasiswa di Gresik dengan Metode SAW (Simple Additive Weighting). Jurnal Ilmiah Indonesia, 7(2), 2761-2769.
Budihartanti , Cahyani. (2019). Sistem Pendukung Keputusan dalam Penilaian Karyawan dengan Metode Simple Additive Weighting (SAW) ISSN : 2598-8719 (Online) ISSN : 2598-8700 (Printed). Journal of Information System, Apllied, Management, Accounting and Research, 3(3), 1–9.
Chandra, K. B., Firstian, B., Fikri, M., & Rosyani, P. (2020). Keluarga Mahasiswa Tegal (Kmt) Ciputat Berbasis Web. Jurnal Kreativitas Mahasiswa Informatika, 1, 126–132.
Utomo, A. R. & Purba, R. C. (2022). Jurnal Rekayasa Informasi , Implementation of Customer Relationship Management (CRM) on Web-based Urban Traffic Stores. Jurnal Rekayasa Informasi, 11(1), 48–57.
Sukiakhy, K.M. (2021). Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik pada CV EL GROLRY menggunakan Metode SAW. Jurnal Geuthèë: Penelitian Multidisiplin, 04(03), 160–168.
Dalimunthe, A. L. (2022). Sistem Informasi E-Learning Di SMA Negeri 1 Rantau Selatan Berbasis Web. Braz Dent J., 33(1), 1–12.
Fitriana, G. F. (2020). Pengujian Aplikasi Pengenalan Tulisan Tangan Menggunakan Model Behaviour Use Case. Jurnal Teknik Informatika Dan Sistem Informasi, 7(2), 2407–4322. http://jurnal.mdp.ac.id
Gulo, F., Sianturi, F. A., & Nusantara, S. P. (2022). Analisa Perbandingan Metode SAW Dengan Ahp Dalama Pelihan Supervisor Pada The Batik Hotel. Saintek (Jurnal Sains Dan Teknologi), 3(2), 43–50.
Khairul, A., Gusman, D., & Adeswastoto, H. (2022). Web-Based Waste Reporting Application Analysis in Dinas Lingkungan Hidup Kabupaten Kampar. Journal of Engineering Science and Technology Management, 1(2), 1–9.
Nurlaela, L., Suprapto, & Usanto. (2021). Sistem Pendukung Keputusan Pemeringkatan Siswa Menggunakan Metode SAW (Simple Additive Weighting). Jurnal Electro Dan Informatika Swadharma (JEIS), 01(2), 19–25.
Nurlela, S., Akmaludin, A., Hadianti, S., & Yusuf, L. (2019). Penyeleksian Jurusan Terfavorit Pada Smk Sirajul Falah Dengan Metode Saw. Jurnal Pilar Nusa Mandiri, 15(1), 1–6.
Ramadhani, F. D., Rahman, K. K. A., Rafi, M. Y., Salamah, U., & Rosyani, P. (2020). Perancangan Sistem Informasi Penjadwalan Mata Kuliah Menggunakan Algoritma Genetika Berbasis Web. Jurnal Kreativitas Mahasiswa Informatika, 1, 133–142.
Rosanaya, S. L., & Fitrayati, D. (2021). Pengembangan Media Pembelajaran Berbasis Video Animasi pada Materi Jurnal Penyesuaian Perusahaan Jasa. Edukatif : Jurnal Ilmu Pendidikan, 3(5), 2258–2267.
Setiadi, A., Yunita, Y., & Ningsih, A. R. (2018). Penerapan Metode Simple Additive Weighting(SAW) Untuk Pemilihan Siswa Terbaik. Jurnal Sisfokom (Sistem Informasi Dan Komputer), 7(2), 104–109.
Unduhan
Diterbitkan
Terbitan
Bagian
Lisensi
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with International Journal of Advances in Intelligent Informatics agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
International Journal of Advances in Intelligent Informatics use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Open Data Commons Attribution License, http://www.opendatacommons.org/licenses/by/1.0/ (default)
Creative Commons CC-Zero Waiver, http://creativecommons.org/publicdomain/zero/1.0/
Open Data Commons Public Domain Dedication and Licence, http://www.opendatacommons.org/licenses/pddl/1-0/
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.