RANCANG BANGUN SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN KARYAWAN BARU DENGAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) BERBASIS WEB DI LOSE STORE
DOI:
https://doi.org/10.31000/.v2i2.1516Abstract
Recruitment is an important thing for the company, in acquiring prospective new employees to occupy a position. Most companies, recruitment process is still not done by a professional. This happens because there is no systematic method to assess the feasibility of prospective new employees. Recruitment decision support system applications are built using the Simple Additive Weighting (SAW) method. This method was chosen because it can determine the weight values for each attribute, and then proceed with the ranking process that will select the best alternative from several alternatives. In this case, the alternative is entitled to be accepted as a new employee in accordance with the criteria specified. Based on test results, a system built to simplify and speed up the selection process for recruitment, and assist Human Resources Department (HRD) managers in decision-making to determine a new employee at a company.
References
Anhar. (2010). Panduan Menguasai PHP dan MySQL secara otodidak. Jakarta: Media kita.
Arief, M. R. (2011). Pemrograman Web Dinamis menggunakan PHP dan MySQL. Yogjakarta: ANDI.
Bunfir, N. (2013). Dasar Pemrograman Web PHP - MySQL dengan Dreamweaver. Yogyakarta: Gava Media.
Fishburn, P. (1967). Additive Utilities with Incomplete Product set : Application to Priorities and Assignments.
Handoko. (2008). Manajemen Personalia Sumber Daya Manusia. Yogjakarta: BPFE.
Jogiyanto. (2014). Analisis dan Desain Sistem Informasi. Yogyakarta: Andi.
Kartini. (2013). Perancangan Sistem Informasi Pemesanan Tiket Konser Musik Online Berbasis Lokasi. Yogjakarta: Semnasteknomedia.
Kusrini. (2007). Konsep dan Aplikasi Sistem Pendukung Keputusan. Yogyakarta: Andi.
Kusumadewi. (2006). Fuzzy Multi-Attribut Decision Making (FUZZYMADM). Yogyakarta: Graha Ilmu.
MacCrimmon, K. (1968). Decision Making among Multiple Atribut Alternatives : a survey and Consolidated Approach.
Moekijat. (2010). Manajemen Sumber Daya Manusia. Bandung: Mandar Maju.
Rohmat Taufiq, S. M. (2013). Sistem Informasi Manajemen. Yogjakarta: Graha Ilmu.
Setia, B. I. (2014). Jago Pemograman PHP. Jakarta: Dunia Komputer.
Shalahuddin. (2011). Modul Pembelajaran Rekayasa Perangkat Lunak (Terstrukur dan Berorientasi Objek). Bandung: Modula.
Siswanti, S. (2015). Sistem Pendukung Keputusan. Yogyakarta: Graha Ilmu.
Turban, E. A. (2011). Decision Support System and Intelligence System 7th . Printice Education International.
Widodo Prabowo.P, D. (2011). Pemodelan Sistem Berorientasi Obyek Dengan UML. Yogyakarta: Graha Ilmu.
Yoder, D. (2010). Manajemen Sumber Daya Manusia. Jakarta: Salemba Empat.
Downloads
Published
Issue
Section
License
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.