Decision Support System for Employee Recruitment of A Company Using Multi Attribute Utility Theory

Mihuandayani, Mihuandayani; Arundaa, Rillya; Tamuntuan, Virginia

doi:10.1109/icoris50180.2020.9320817

Cited by 10 publications

(7 citation statements)

References 10 publications

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“…Under the 50~75% water supply rates, the algorithm chose to maintain irrigation to the three main branches (Branches 1, 22, and 38) and gradually reduce irrigation to the branches so as to ensure the most efficient allocation of water resources. Interestingly, over half of the solutions chosen by the target approach do not prioritize irrigation to the wider upstream branches but rather focus on the downstream branches as the main subjects of irrigation ( Branches 23,26,27,30,39,40,41,42,45,46,etc.). This contrasts strongly with traditional approaches to prioritize upstream over downstream to reduce water resource divergence.…”

Section: Rationality Of Using a Ga To Identify Skyline Solutionsmentioning

confidence: 99%

“…The purpose of decision support systems is to simulate human logical reasoning to process information automatically and, thus, swiftly and accurately provide recommendations to decision-makers. This enhances decision-making quality, shortens decision-making time, and reduces decision-making costs [26]. Decision support methods are, thus, widely applied in various fields to establish an efficient expert system to solve optimization problems such as product design [27][28][29], recommendation systems [30][31][32], and system improvement [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query

Loh,

Chen,

et al. 2024

Applied Sciences

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The steady increase in droughts worldwide has compelled many researchers to focus on water allocation. Multi-objective decision support for irrigation systems is a popular topic due to its relevance to the national economy and food supply. However, the majority of researchers have relied on conventional top-k designs for their decision support systems despite their limitations with regard to multi-objective systems. Thus, we propose applying a skyline query to the problem. As the input and output formats of skyline queries differ significantly from those of existing systems, we developed a new genetic algorithm and objective ranking. Qualitative and quantitative experiments using real-world data from Taiwan’s largest irrigated region demonstrate the effectiveness of the proposed approach.

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Section: Rationality Of Using a Ga To Identify Skyline Solutionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query

Loh,

Chen,

et al. 2024

Applied Sciences

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“…Multi Attribute Utility Theory (MAUT) merupakan suatu skema yang evaluasi akhir, v(x), dari suatu objek x didefenisikan sebagai bobot yang dijumlahkan dengan suatu nilai yang relevan terhadap nilai dimensinya. Ungkapan yang biasa digunakan untuk menyebutnya adalah nilai utilitas [11]- [14]. MAUT digunakan untuk merubah dari beberapa kepentingan kedalam nila numerik dengan skala 0-1 dengan 0 mewakili nilai terburuk dan 1 terbaik.…”

Section: Metode Multi Attribute Utility Theory (Maut)unclassified

Penerapan Metode Multi Attribute Utility Theory (MAUT) Dalam Pemilihan Karyawan yang di Non-Aktifkan di Masa Pandemi

Lubis

Esabella²,

Mesran³

et al. 2022

mib

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Coronavirus Disease 2019 (Covid-19) was first discovered in China, spread to various countries including Indonesia in March 2020. Until 2021 Covid-19 has not disappeared. This of course has an impact that can harm the country and society. Therefore, the government made a policy of Large-Scale Social Restrictions (PSBB) with the aim of breaking the chain of the spread of Covid-19. One of the impacts felt by the community with its presence is the deactivation of employees carried out by several companies to workers on the grounds that they do not have the money to pay the workers. PT. XYZ has difficulty choosing which employees to deactivate. This research is based on these reasons, so the authors decided to use the Multi Attribute Utility Theory (MAUT) method to help make decisions to choose employees who deserve to be deactivated with job prospects, age, length of work per year, education, dependents with an alternative number of 10 (Ten) ) employees. The use of the MAUT method is expected to determine the criteria for employees who deserve to be deactivated, because the MAUT method will perform a ranking process based on attributes with different weights so that the results are more optimal, then a ranking process will be carried out which will determine the optimal alternative as well. The 5 (five) alternatives that deserve to be deactivated are A2 with a result of 0,9303, A8 with a result of 0,5561, A4 with a result of 0,533, A9 with a result of 0,4978, and A1 with a result of 0,4867 is 5 a viable alternative to deactivate during the pandemic

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“…This study aims to optimize the recruitment process of financial managers using the Multi-Attribute Utility Theory (MAUT) Method. MAUT will be applied to integrate various factors and preferences in the selection process to produce more objective and accurate decisions [5]. By adopting this approach, the study not only assists companies in selecting the most suitable candidates but also contributes to the academic literature by presenting practical applications of decision theory in the context of recruitment.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Recruitment of Prospective Financial Managers Through a Decision Support System with the Multi Attribute Utility Theory Method

Firmansyah,

Sahara,

Yeyi Gusla Nengsih

et al. 2024

E-Komtek

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This study evaluates the application of Multi Attribute Utility Theory (MAUT)-based decision support systems in the recruitment process of financial managers in technology companies "TechInnovate". This study aims to identify the extent to which the use of MAUT can increase objectivity and effectiveness in candidate selection. The quantitative method was used by collecting data from 50 candidates who volunteered for this position. The assessment criteria that have been determined include Education and Qualifications, Work Experience, Analytical and Financial Skills, Communication Skills, Leadership and Team Management, Ethics and Integrity, Technology Capabilities, Adaptability and Innovation, Decision Making Ability. Data is collected through scores assigned to each criterion for each candidate, which are then aggregated taking into account the relative weights of each criterion. Statistical analysis is applied to evaluate the distribution of scores and the effectiveness of the system in selecting the most suitable candidates. Results from this study show that the application of MAUT is significant in improving objectivity in recruitment decision making, with high scores strongly correlated with expected job performance in in-depth interviews and follow-up evaluations. This study proves that integrating a systematic approach in recruitment not only strengthens the selection process but also promotes data-driven and objective decisions. The implications of this research are relevant for companies operating in dynamic and technology-centric environments, suggesting the integration of MAUT-based decision support systems as an effective strategy in the recruitment process.

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Decision Support System for Employee Recruitment of A Company Using Multi Attribute Utility Theory

Cited by 10 publications

References 10 publications

Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query

Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query

Penerapan Metode Multi Attribute Utility Theory (MAUT) Dalam Pemilihan Karyawan yang di Non-Aktifkan di Masa Pandemi

Optimization of Recruitment of Prospective Financial Managers Through a Decision Support System with the Multi Attribute Utility Theory Method

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