www.fujipress.jp Open in urlscan Pro
61.194.35.66  Public Scan

Form analysis
6 forms found in the DOM

GET https://www.fujipress.jp/

<form role="search" method="get" action="https://www.fujipress.jp/">
  <input type="hidden" name="post_type" value="page">
  <input type="hidden" name="cat" value="-2">
  <input type="hidden" name="search_type" value="site">
  <input type="text" value="" name="s" class="searchWindow" placeholder=" Site search">
  <input type="submit" class="submitBtn" name="siteBtn" value="">
</form>

---

POST https://www.fujipress.jp/main/wp-content/themes/Fujipress/pdf_subscribed.php

<form class="pdfdl_class" action="https://www.fujipress.jp/main/wp-content/themes/Fujipress/pdf_subscribed.php" method="post">
  <input type="hidden" name="xid" value="JACII002800050006"><input type="hidden" name="doi" value="10.20965/jaciii.2024.p1117">
  <button type="submit" value="Full text" onclick="__gaTracker('send', 'event', 'Full_pdf_DL', 'JACIII', 'JACII002800050006');">Full text <span class="sml80">(1.1MB) (free)</span></button>
</form>

---

POST https://www.fujipress.jp/citeinfo/

<form class="citedl citedl_fm" action="https://www.fujipress.jp/citeinfo/" method="post" target="_blank">
  <input type="hidden" name="xid" value="JACII002800050006"><input type="hidden" name="fname" value="jaciii28_1117.bib">
  <input type="hidden" name="citedata" value="@article{ Briscilla_2024jaciii,
	title={A Multi-Criteria Decision Making for Employee Selection Using SAW and Profile Matching},
	author={S. Jenifer Briscilla and R. Sundarrajan},
	journal={Journal of Advanced Computational Intelligence and Intelligent Informatics},
	volume={28},
	number={5},
	pages={1117-1125},
	year={2024},
	doi={10.20965/jaciii.2024.p1117}
 }
	">
  <button class="citedl_btn" type="submit" onclick="__gaTracker('send', 'event', 'cite_DL', 'JACIII', 'JACII002800050006.bib');">BIB TEX <span class="sml80">(BibDesk, LaTeX)</span></button>
</form>

---

POST https://www.fujipress.jp/citeinfo/

<form class="citedl citedl_fm" action="https://www.fujipress.jp/citeinfo/" method="post" target="_blank">
  <input type="hidden" name="xid" value="JACII002800050006"><input type="hidden" name="fname" value="jaciii28_1117.ris">
  <input type="hidden" name="citedata" value="Provider: Fuji Technology Press
	Database: fujipress
	Content:text/plain; charset='utf-8'
	TY  - JOUR
	TI  - A Multi-Criteria Decision Making for Employee Selection Using SAW and Profile Matching
	TI  -  
	AU  -  Briscilla, S. Jenifer
AU  -  Sundarrajan, R.
JO  - Journal of Advanced Computational Intelligence and Intelligent Informatics
	VL  - 28
	IS  - 5
	SP  - 1117
	EP  - 1125
	PY  - 2024
	DO  - 10.20965/jaciii.2024.p1117
	ER  - 
	">
  <button class="citedl_btn" type="submit" onclick="__gaTracker('send', 'event', 'cite_DL', 'JACIII', 'JACII002800050006.ris');">RIS <span class="sml80">(EndNote, Reference Manager, etc)</span></button>
</form>

---

POST https://www.fujipress.jp/citeinfo/

<form class="citedl citedl_fm" action="https://www.fujipress.jp/citeinfo/" method="post" target="_blank">
  <input type="hidden" name="xid" value="JACII002800050006"><input type="hidden" name="fname" value="jaciii28_1117.txt">
  <input type="hidden" name="citedata" value="S.  Briscilla and R.  Sundarrajan, “A Multi-Criteria Decision Making for Employee Selection Using SAW and Profile Matching,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.5, pp. 1117-1125, 2024
	DOI: 10.20965/jaciii.2024.p1117
	ABSTRACT:
	Multi-criteria decision making process has been one of the fastest growing areas during the last decades depending on the change in the business sector. Multi-criteria decision making is the most important branch of operation research by which people make complex decision daily life. The major steps in the decision- making approach are selecting the most preferred alternative for the decision-maker, ranking alternatives in order of importance for selection problems, and screening alternatives for the final decision. Employees are an important element of a company that determines its progress. Conventional (manual) recruitment methods are vulnerable to non-technical factors, such as frequent duplication or invalid data. In this study, simple additive weighting and profile matching are proposed to solve the employee selection problem. This study was conducted at the (UPT) Career Development and Entrepreneurship Universitas Brawijaya Malang using data collected from written test selection in 2019. The effectiveness of both methods was analyzed using confusion matrix. The SAW method provides an accuracy rate of 94.7%, a precision rate of 87.5%, Recall rate of 91.3% and F-measure rate of 89.4%. On the other hand, profile matching method obtained the Accuracy rate of 90.4%, Precision rate of 81.4%, Recall rate of 81.4% and F-measure rate of 81.4%. Thus, it can be concluded that both methods have high accuracy values accompanied by high precision values when used for the selection process. This system can also effectively reduce the bias rate of the same data very well, as can be seen from the high recall and F-measure rates.
	">
  <button class="citedl_btn" type="submit" onclick="__gaTracker('send', 'event', 'cite_DL', 'JACIII', 'JACII002800050006.txt');">   TEXT   </button>
</form>

---

GET https://www.fujipress.jp/advanced_search/

<form role="search" method="get" class="searchform cf" action="https://www.fujipress.jp/advanced_search/">
  <h3>Search articles</h3>
  <label><input type="checkbox" name="s-type[]" value="rb" checked="">JRM</label>
  <label><input type="checkbox" name="s-type[]" value="au" checked="">IJAT</label>
  <label><input type="checkbox" name="s-type[]" value="jc" checked="">JACIII</label>
  <label><input type="checkbox" name="s-type[]" value="dr" checked="">JDR</label>
  <div id="search1">
    <input type="text" name="s[]" placeholder=" term1 term2 term3 ..."> <!-- value="" -->
    <input type="hidden" name="search_type" value="article">
  </div>
  <div id="search2">
    <p><a href="https://www.fujipress.jp/search/">Advanced Search</a></p>
  </div>
  <div id="search3"><input type="submit" value="Search"></div>
</form>

---

Text Content

 * English
 * Japanese

 * Top
 * Submission
 * Subscription
 * Contact

Top > JACIII > A Multi-Criteria Decision Making for Employee Selection Using ...

single-jc.php

« previous
next »
JACIII Vol.28 No.5 pp. 1117-1125
doi: 10.20965/jaciii.2024.p1117
(2024)

Research Paper:

Views over last 60 days: 7


A MULTI-CRITERIA DECISION MAKING FOR EMPLOYEE SELECTION USING SAW AND PROFILE
MATCHING


S. JENIFER BRISCILLA† AND R. SUNDARRAJAN

Department of Information Technology, Kalasalingam Academy of Research and
Education (KARE)
Anand Nagar, Krishnankoil, Tamil Nadu 626126, India


†Corresponding author

Received:November 30, 2023Accepted:June 4, 2024Published:September 20, 2024

Keywords:employee selection, multi-criteria analysis, SAW, profile matching
Abstract

Multi-criteria decision making process has been one of the fastest growing areas
during the last decades depending on the change in the business sector.
Multi-criteria decision making is the most important branch of operation
research by which people make complex decision daily life. The major steps in
the decision- making approach are selecting the most preferred alternative for
the decision-maker, ranking alternatives in order of importance for selection
problems, and screening alternatives for the final decision. Employees are an
important element of a company that determines its progress. Conventional
(manual) recruitment methods are vulnerable to non-technical factors, such as
frequent duplication or invalid data. In this study, simple additive weighting
and profile matching are proposed to solve the employee selection problem. This
study was conducted at the (UPT) Career Development and Entrepreneurship
Universitas Brawijaya Malang using data collected from written test selection in
2019. The effectiveness of both methods was analyzed using confusion matrix. The
SAW method provides an accuracy rate of 94.7%, a precision rate of 87.5%, Recall
rate of 91.3% and F-measure rate of 89.4%. On the other hand, profile matching
method obtained the Accuracy rate of 90.4%, Precision rate of 81.4%, Recall rate
of 81.4% and F-measure rate of 81.4%. Thus, it can be concluded that both
methods have high accuracy values accompanied by high precision values when used
for the selection process. This system can also effectively reduce the bias rate
of the same data very well, as can be seen from the high recall and F-measure
rates.

SAW and profile matching applications in DSS

Full text (1.1MB) (free)
Cite this article as:S. Briscilla and R. Sundarrajan, “A Multi-Criteria Decision
Making for Employee Selection Using SAW and Profile Matching,” J. Adv. Comput.
Intell. Intell. Inform., Vol.28 No.5, pp. 1117-1125, 2024.Data files:
BIB TEX (BibDesk, LaTeX)
RIS (EndNote, Reference Manager, etc)
   TEXT   
References
 1.  [1] M. Popović, “An MCDM approach for personnel selection using the COCOSO
     method,” J. of Process Management and New Technologies, Vol.9, Issues 3-4,
     pp. 78-88, 2021.
 2.  [2] Sunarti and J. Sundari, “Comparison of SAW and Profile Matching Methods
     for Home Selection Case Study: Depok Housing,” J. Nasional Tidak
     Terakreditasi, Vol.2, No.2, pp. 115-126, 2020.
 3.  [3] H. Taherdoost, “Analysis of Simple Additive Weighting Method (SAW) as a
     Multi Attribute Decision-Making Technique: A Step-by-Step Guide,” J. of
     Management Science & Engineering Research, Vol.6, Issue 1, 2023.
 4.  [4] T. Susilowati, E. Y. Anggraeni, Fauzi, W. Andewi, Y. Handayani, and A.
     Maseleno, “Using Profile Matching Method to Employee Position Movement,”
     Int. J. of Pure and Applied Mathematics, Vol.118, No.7, pp. 415-423, 2018.
 5.  [5] N. A. Azhar, N. A. M. Radzi, A. M. Nurul, and W. S. H. M. W. Ahmad,
     “Multi-criteria Decision Making: A Systematic Review,” Recent Advances in
     Electrical & Electronic Engineering, Vol.14, No.8, pp. 779-801, 2021.
 6.  [6] M. D. L. Siahaan, Elviwani, A. Br. Surbakti, A. H. Lubis, and A. P. U.
     Siahaan, “Implementation of Simple Additive Weighting Algorithm in
     Particular Instance,” Int. J. of Scientific Research in Science and
     Technology, Vol.3, Issue 6, 2017.
 7.  [7] J. Martinez-Gil, A. L. Paoletti, G. Rácz, A. Sali, and K. Schewe,
     “Accurate and Efficient Profile Matching in Knowledge Bases,” Data &
     Knowledge Engineering, Vol.117, pp. 195-215, 2017.
     https://doi.org/10.1016/j.datak.2018.07.010
 8.  [8] L. Sopianti and N. Bahtiar, “Students Major Determination Decision
     Support Systems using Profile Matching Method with SMS Gateway
     Implementation,” J. Sains & Matematika, Vol.23, Issue 1, pp. 14-24, 2015.
 9.  [9] M. Rashidi, M. Ghodrat, B. Samali, and M. Mohammadi, “Decision Support
     Systems,” Management of Information Systems, 2018.
 10. [10] P. G. W. Keen and M. S. Scott Morton, “Decision Support Systems: An
     Organisational Perspective,” Addison-Wesley Publishing Company, 1978.
 11. [11] R. Bonczek, C. Holsapple, and A. Whinston, “The evolving roles of
     models in decision support systems,” Decision Sciences, Vol.11, Issue 2,
     pp. 337-356, 2007.
 12. [12] M. Mora, G. Forgionne, and J. Gupta, “Decision Making Support Systems:
     Achievements and Challenges for the New Decade,” Natural Resources
     Planning, Silva Fennica: Harrisburg, 2003.
 13. [13] A. Memariani, A. Amini, and A. Alinezhad, “Sensitivity analysis of
     simple additive weighting method (SAW): The results of change in the weight
     of one attribute on the final ranking of alternatives,” J. of Industrial
     Engineering, Vol.2, Issue 4, pp. 13-18, 2009.
 14. [14] T. Susilowati, E. Y. Anggraeni, W. Fauzi, Y. Andewi, A. Handayani, and
     A. Maseleno, “Using Profile Matching Method to Employee Position Movement,”
     Int. J. of Pure and Applied Mathematics, Vol.118, No.7, pp. 415-423, 2018.


 This article is published under a Creative Commons Attribution-NoDerivatives
4.0 Internationa License.


 * SEARCH ARTICLES
   
   JRM IJAT JACIII JDR
   
   
   Advanced Search
   
   


 * MOST VIEWED ABSTRACTS
   
   are now shown on
   “Most Viewed Abstracts” page


 * JIF JC TEXT-6
   
   Journal Impact Factor
   
   2023
   
   0.7

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome,
Firefox, Safari, Edge, Opera.

Last updated on Sep. 20, 2024

 * Login
 * Sitemap
 * Terms and Conditions
 * Privacy Policy
 * Advertising Information
 * About Us
 * Contact

Journal articles on this site, except where otherwise noted, are published under
a Creative Commons License CC-BY-ND 4.0.


Copyright © 2024 Fuji Technology Press Ltd.

 

Scroll Up