Two-Envelope System for Consultant Selection using Weighted Sum Model

Consultant Selection is one of a classical problem in Multi Criteria Decision Making (MCDM). Most of the literature in Operation Research only concentrates on model building rather than developing an inclusive analytic tool that extends to a Decision Support System (DSS). In this paper, we deploy a case study approach to understand the user requirement for DSS development. We observe the process of consultant selection and the decision making at one of the technical department which involve in the infrastructure project in Malaysia. A two-envelope system and a simple Weighted Sum Model are currently in use. We demonstrate the abstraction and application based on two case projects. Sensitivity analysis is also performed and the result shows that the decision changed if it is solely based on fees or with minimal quality criteria. Finally, we gather the findings from the organizational flows, user modelling and decision making process in order to benchmark with our future works. This will helps us to better understand and develop an improved decision support model or tools for consultant selection problem.

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Implementasi Metode SMARTER Untuk Rekomendasi Penerima Bantuan Raskin Masa Covid 19

JURNAL MEDIA INFORMATIKA BUDIDARMA ◽

10.30865/mib.v5i2.2914 ◽

2021 ◽

Vol 5 (2) ◽

pp. 549

Author(s):

Julfikar Rahmad ◽

Volvo Sihombing ◽

Masrizal Masrizal

Keyword(s):

Decision Making ◽

Decision Support ◽

Rural Areas ◽

Lower Class ◽

Developed Countries ◽

Decision Support Model ◽

Head Of Household ◽

Classic Problem ◽

The Government ◽

The Right

The problem of poverty is a classic problem that occurs in every country, both developed countries and developing countries like Indonesia. In every country, there are many programs carried out by the government to overcome the problem of poverty, one of which is the RASKIN program carried out by the Indonesian government. The method used to complete this research is SMARTER (Simple Multi Attribute Rating Technique Exploiting Ranks). During the Covid 19 pandemin, which is currently happening, various kinds of assistance are needed for middle and lower class people in rural areas, thus to distribute assistance, assistance distribution techniques are needed so that it reaches the right people. The SMARTER method was chosen because it is a form of decision support model used in decision making with multi attributes that will be used to solve decision-making problems. The research was conducted in Sei Beluru Village, Meranti District, Asahan Regency. In Sei Beluru Village, several criteria were obtained from direct observation of the field, namely the area of the house floor, the type of floor of the house, the type of house wall, the toilet facilities, the source of drinking water, lighting, materials. fuel used, frequency of eating, ability to buy meat, ability to buy clothes, ability to seek treatment, monthly income, education of the head of household, ownership of assets. Decision support systems using the Smarter method are able to analyze data on people who are entitled to receive Raskin assistance. The results obtained from this study are that from several prospective recipients of Raskin assistance with the specified criteria, it is found that the most prioritized alternative has the highest value of 0.603 using the Smarter method.

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Auxiliary Decision Support Model of Sports Training Based on Association Rules

Mobile Information Systems ◽

10.1155/2021/7233800 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Changnian Zhang ◽

MeiJie Li ◽

Hui Wang ◽

Ning Wang

Keyword(s):

Decision Making ◽

Decision Support ◽

Association Rules ◽

Human Body ◽

Movement Trajectory ◽

Classification Rules ◽

Sports Training ◽

Decision Support Model ◽

Discriminative Ability ◽

Support Model

In sports or fitness training, nonstandard movements will affect the training effect and even lead to sports injuries. However, the standard movements of various sports activities need professional guidance, so it is difficult to find out whether the movements are standard or not. In recent years, body pose estimation has become a hot topic in computer vision research. A deep learning model can effectively identify the human nodes and movement trajectory in pictures or videos and evaluate the movements of the target human body. However, the movement process is generally covered by others or the situation of nearby personnel, which leads to the deviation of the movement recognition of the human body and affects the evaluation of the movement. Thus, it is unable to effectively correct the wrong movement, but will mislead the training personnel. Therefore, this paper proposes a novel decision support model for sports training based on association rules. We use posterior probability settings to reveal the weights of the discriminative ability of attribute items and set the classification performance to reflect the weights of three measures to evaluate credit contribution. Thus, the learning threshold setting reflects the weight of the decision-making ability of sports training. Furthermore, compared with traditional association rules, attribute items, frequent item sets, and classification rules that can improve the decision-making performance of sports training are discovered, which complement the deficiencies of different measures. Finally, using the weighted voting strategy to fuse the decision-making information of the classification rules, we can effectively assist in sports training so that the coach can work out corresponding countermeasures and realize scientific management.

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Business Intelligence: How Sport Scientists Can Support Organization Decision Making in Professional Sport

International Journal of Sports Physiology and Performance ◽

10.1123/ijspp.2018-0903 ◽

2019 ◽

Vol 14 (4) ◽

pp. 544-546 ◽

Cited By ~ 5

Author(s):

Patrick Ward ◽

Johann Windt ◽

Thomas Kempton

Keyword(s):

Decision Making ◽

Decision Support ◽

Data Collection ◽

Business Intelligence ◽

Professional Sport ◽

Data Systems ◽

Decision Support Model ◽

Systematic Analysis ◽

Domain Specific ◽

Specific Expertise

The application of scientific principles to inform practice has become increasingly common in professional sports, with increasing numbers of sport scientists operating in this area. The authors believe that in addition to domain-specific expertise, effective sport scientists working in professional sport should be able to develop systematic analysis frameworks to enhance performance in their organization. Although statistical analysis is critical to this process, it depends on proper data collection, integration, and storage. The purpose of this commentary is to discuss the opportunity for sport-science professionals to contribute beyond their domain-specific expertise and apply these principles in a business-intelligence function to support decision makers across the organization. The decision-support model aims to improve both the efficiency and the effectiveness of decisions and comprises 3 areas: data collection and organization, analytic models to drive insight, and interface and communication of information. In addition to developing frameworks for managing data systems, the authors suggest that sport scientists’ grounding in scientific thinking and statistics positions them to assist in the development of robust decision-making processes across the organization. Furthermore, sport scientists can audit the outcomes of decisions made by the organization. By tracking outcomes, a feedback loop can be established to identify the types of decisions that are being made well and the situations where poor decisions persist. The authors have proposed that sport scientists can contribute to the broader success of professional sporting organizations by promoting decision-support services that incorporate data collection, analysis, and communication.

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How to Discourage Adversaries From Affecting Decision Outcomes of a Repeated Patent Application Decision--Making Process

10.20944/preprints202106.0676.v1 ◽

2021 ◽

Author(s):

Willem van der Sluis

Keyword(s):

Decision Making ◽

Decision Support ◽

Decision Maker ◽

Patent Application ◽

Decision Making Process ◽

Sequential Decision ◽

Decision Support Model ◽

Application Process ◽

Decision Outcomes ◽

Application Decision

Outcomes of repeated decision--making processes may be affected by adversarial actors, without being noticed. Adversaries may try to gain knowledge about a particular decision--making process, identify its decision--makers, and guess which underlying decision support model is used. Then they can simulate the process, and craft different scenarios to affect its decision outcomes. Therefore, designers of decision support systems need to incorporate this in the decision modeling phase. The purpose of this study is to demonstrate this for the repeated decision--making in a patent application process. In this process, two sequential decision outcomes can be affected by adversarial actors: a company's decision to which type of patent office to send a patent request to, and the decision of a specialized patent officer to grant an application, or not. It is motivated that the company's decision--maker is \emph{bounded} rational. A theory for information--theoretic bounded rational decision--making under uncertainty proposed by Ortega et al.\ is adopted to model this type of decision--maker. A framework is provided to simulate a number of scenarios that adversaries may deploy to affect decision outcomes of a repeated patent application decision--making process. The framework is also utilized for statistically testing the presence of the scenarios, and to demonstrate how to discourage adversaries from deploying them.

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Assistance Decision Model for SMEs

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d5875.018520 ◽

2020 ◽

Vol 8 (5) ◽

pp. 1248-1255

Keyword(s):

Decision Making ◽

Decision Support ◽

Support System ◽

Research Method ◽

Decision Model ◽

Financial Assistance ◽

System Model ◽

Decision Making Process ◽

Decision Support Model ◽

The Government

SMEs in Indonesia are one of the economic drivers of the nation. Its presence and development shows a sizeable contribution to Gross Domestic Income (GDP) each year. With this background, the Indonesian government provides stimulants in the form of financial assistance for the special SMEs for beginner SMEs. The government is encouraging the growth of SMEs by providing assistance to SMEs. During this time the process of determining the provision of assistance is done manually so that it is less effective and efficient. Therefore, the purpose of this study is to make a decision support model for the Ministry of SMEs to provide financial assistance to SMEs. The research method uses AHP and Promethee. Based on the results and discussion produced a Decision Support System model to help the Ministry of SMEs provide financial assistance to SMEs. The conclusion of this study is the suitability of SME ministry staff with the resulting model in the form of ease in the decision making process of providing assistance to SMEs.

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