scholarly journals Implementasi Metode AHP-TOPSIS dalam Sistem Pendukung Rekomendasi Mahasiswa Berprestasi

2021 ◽  
Vol 3 (1) ◽  
pp. 01-10
Author(s):  
Moh. Zulkifli Katili ◽  
Lanto Ningrayati Amali ◽  
Mohamad Syafri Tuloli
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Model Development ◽  
Black Box ◽  
Decision Making Process ◽  
Topsis Method ◽  
Application System ◽  
Development Method ◽  
Waterfall Model ◽  
Faculty Department

Menentukan mahasiswa berprestasi untuk diikutkan pada perlombaan atau untuk seleksi beasiswa merupakan masalah yang selalu dialami oleh pihak fakultas/jurusan. Untuk mengatasi masalah tersebut dibutuhkan penggunaan aplikasi untuk membantu dalam pengambilan keputusan. Tujuan penelitian ini adalah untuk merancang aplikasi Sistem Pendukung Keputusan (SPK) untuk pemberian rekomendasi mahasiswa berprestasi. Penelitian ini menggunakan metode pengembangan sistem model Waterfall dan metode AHP-TOPSIS untuk penentuan kriteria data mahasiswa berupa nilai matakuliah, kegiatan yang diikuti, ataupun prestasi yang dimiliki. Untuk memastikan fungsionalitas, sistem aplikasi telah diuji melalui Uji Black-box dan White-box. Penelitian ini menghasilkan aplikasi SPK untuk pemberian rekomendasi mahasiswa berprestasi yang dapat disesuaikan dengan kriteria dan kebutuhan pihak fakultas/jurusan selaku pengguna. Deciding which outstanding students to be enrolled in competitions or scholarships is a problem that faculties or departments always experience. Hence, an application is needed to help in the decision-making process. This research aims to design a decision support system (DSS) application to give recommendations regarding outstanding students. The Waterfall Model development method and the AHP-TOPSIS method were employed to determine the criteria for the students’ data, such as subject scores, activities being participated in, and achievements. The application system has already been tested through the Black-box and White-box tests to ensure its functionality. It resulted in a DSS application that gives recommendations about outstanding students, which may be adjusted according to the criteria and needs of the faculty/department as the users.

Models of decision support in socio-cyber-physical systems

2019 ◽  
pp. 55-70 ◽  
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Situation Awareness ◽  
Cyber Physical Systems ◽  
Emergent Behavior ◽  
Emergent Properties ◽  
Decision Making Process ◽  
Physical Systems ◽  
Decision Support Models ◽  
Common Goals

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.

Multivariable Automatisierungsentscheidungen*/Multivariate automation decisions – A tool for cost-benefit assessments as a basis for decision-making

2019 ◽  
Vol 109 (03) ◽  
pp. 134-139
Author(s):  
P. Burggräf ◽  
J. Wagner ◽  
M. Dannapfel ◽  
K. Müller ◽  
B. Koke
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Environmental Conditions ◽  
Cost Benefit ◽  
Decision Support Tool ◽  
Decision Making Process ◽  
Support Tool ◽  
Cost And Benefit ◽  
Benefit Evaluation ◽  
Level Of Automation

Der wachsende Bedarf an Wandlungsfähigkeit führt zu einer höheren Frequenz in der Umplanung von Montagesystemen und erfordert eine kontinuierliche Überprüfung und Anpassung des Automatisierungsgrades. Um auch die komplexen Umgebungsbedingungen abzubilden, sollen nicht-monetäre Faktoren in den Entscheidungsprozess eingebunden werden. Um die Entscheidung zu unterstützen, stellt dieser Beitrag ein Tool zur Identifizierung und Bewertung von Automatisierungsszenarien mittels einer Nutzwert-Aufwand-Analyse vor.   The increasing need for adaptability in assembly leads to a higher planning frequency of the system and requires continuous checks and adaptations of the appropriate level of automation. To account for the complex environmental conditions, non-monetary factors are included in the decision-making process. This paper presents a decision support tool to identify and evaluate automation scenarios by means of cost and benefit evaluation.

scholarly journals Decision Support System of Employee Performance Evaluation

2019 ◽  
Vol 8 (6S2) ◽  
pp. 1007-1012
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Decision Support ◽  
Decision Support System ◽  
Performance Appraisal ◽  
Support System ◽  
Employee Performance ◽  
Accurate Information ◽  
Intellectual Capacity ◽  
Waterfall Model

Employee Performance Evaluation at CV Artha Mandiri Pringsewu is still done manually, without a computerized system, so that it faces obstacles to obtain actual and accurate information. In order to be successful in business today, CV. Artha Mandiri needs information system that can support decision making and various information. Problems that often occur in the process of employee performance appraisal include the decision-making subjectivity, especially if several existing employees have abilities that are not much different. The use of decision support systems is a solution to reduce subjectivity in decision making designed with Visual Basic 6.0 programming, The calculations were performed on all criteria for all employees, so it is expected that employees with the best abilities are selected. Decision support system is supported by a descriptive method in the development of system software with Waterfall model. The calculation process is carried out to determine employee recommendations in the Promotion System based on 3 aspects namely Intellectual Capacity, Work Attitude and Behavior. The result of this process is employee ranking. This ranking is the basis for decision makers to choose employees who are suitable in the vacant positions that are expected to help evaluating the performance of employees at CV Artha Mandiri

scholarly journals Uncertainties in complex dynamic environments

2014 ◽  
Vol Volume 2 ◽  
Author(s):  
Hasmik Atoyan ◽  
Jean-Marc Robert ◽  
Jean-Rémi Duquet
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
User Interfaces ◽  
Dynamic Environments ◽  
Decision Making Process ◽  
Uncertain Information ◽  
Complex Environments ◽  
Complex Dynamic ◽  
Different Types ◽  
Machine Systems

The utilization of Decision Support Systems (DSS) in complex dynamic environments leads the human operator almost inevitably to having to face several types of uncertainties. Thus it is essential for system designers to clearly understand the different types of uncertainties that could exist in human-machine systems of complex environments, to know their impacts on the operator's trust in the systems and decision-making process, and to have guidelines on how to present uncertain information on user interfaces. It is also essential for them to have an overview of the different stages, levels, and types of system automation, and to know their possible impacts on the creation of different types of uncertainties. This paper investigates these topics and aim at helping researchers and practitioners to deal with uncertainties in complex environments.

scholarly journals Sistem Pendukung Keputusan Penyeleksian Colour Guard Pada Marching Band Ginada Dengan Menggunakan Metode Vikor Dan Borda

2020 ◽  
Vol 2 (1) ◽  
pp. 35-48
Author(s):  
Nurjannah ◽  
Dito Putro Utomo
Keyword(s):  
High School ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Body Language ◽  
Routine Activity ◽  
Decision Making Process ◽  
Marching Band

Decision support system for selecting color guard with VIKOR and Borda methods. It has been made as a tool to select color guard at the Sei Rampah High School. The criteria used in the decision support system for color guard selection are: height, weight, agility, stamina, and body language. Color guard selection activities are a routine activity every year, so GINADA marching band coach Sei Rampah hereby selects to select permanent members in the marching band. Decision Support System in an organization can be seen as important in supporting the smooth running of activities and achieving an organizational goal. SPK can come in various forms, ranging from simple forms of data processing to complex application forms, and can also be used to accelerate and improve the quality of the decision-making process in the organization.

scholarly journals Support of decision-making under risk by a risk-averse decision-maker

2020 ◽  
Vol 13 ◽  
Author(s):  
Andrzej Łodziński
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Maker ◽  
The State ◽  
Decision Making Process ◽  
Discrete Problem ◽  
Risk Averse ◽  
Control Parameters ◽  
Decision Making Under Risk ◽  
State Of The Environment

The paper presents the decision support under risk by the risk averse decision maker. Decision making under risk occurs when the result of the decision is not unequivocal and depends on the state of the environment. The decision making process is modeled with the use of multi-criteria optimization. The decision is made by solving the problem with the control parameters that determine the decision maker's aspirations and the evaluation of the solutions received. The decision maker asks the parameter for which the solution is determined. Then, evaluate the solution received accepting or rejecting it. In the second case, the decision maker gives a new parameter value and the problem is solved again for the new parameter. The work includes an simple discrete problem of decision support under risk

The Full Knowledge of Big Data in the Integration of Inter-Organizational Information

Web Services ◽  
2019 ◽  
pp. 803-821
Author(s):  
Thiago Poleto ◽  
Victor Diogho Heuer de Carvalho ◽  
Ana Paula Cabral Seixas Costa
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Decision Making Process ◽  
Data Repositories ◽  
Modeling And Analysis ◽  
Incremental Change ◽  
Working Together ◽  
Full Knowledge ◽  
Using Data

Big Data is a radical shift or an incremental change for the existing digital infrastructures, that include the toolset used to aid the decision making process such as information systems, data repositories, formal modeling, and analysis of decisions. This work aims to provide a theoretical approach about the elements necessary to apply the big data concept in the decision making process. It identifies key components of the big data to define an integrated model of decision making using data mining, business intelligence, decision support systems, and organizational learning all working together to provide decision support with a reliable visualization of the decision-related opportunities. The concepts of data integration and semantic also was explored in order to demonstrate that, once mined, data must be integrated, ensuring conceptual connections and bequeathing meaning to use them appropriately for problem solving in decision.

Development of the Decision-Making Algorithm on the Geological and Engineering Operations Based on the Infrastructure of the Digital Oil Field

2016 ◽  
Vol 685 ◽  
pp. 907-911 ◽  
Author(s):  
V.A. Silich ◽  
A.O. Savelev
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Oil Field ◽  
Decision Making Process ◽  
Operations Planning ◽  
Oilfield Development

The article discusses process of decision support in oilfield development. The algorithm of geological and engineering operations planning, based on the principal stages of the decision-making process to perform GEO, is proposed.

Research on Agent-Based Energy Saving System of Civil

2013 ◽  
Vol 816-817 ◽  
pp. 1220-1224
Author(s):  
Shou Cai Ma
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Energy Saving ◽  
Decision Making Process ◽  
Agent Based ◽  
Adjustment Mechanism ◽  
Building Systems ◽  
System Components ◽  
System Energy ◽  
The City

This paper deeply analyzes the urban civil system, energy-saving decision-making mechanism, the system components and the related energy-saving anti-adjustment mechanism based on the proposed energy-saving urban civil system's basis. It also presents the classification decision-making and decision-making process for the civil on various components on building systems in decision-making energy-saving features on the system proposed civil heat, urban heating network and the energy saving civil monomer decision making. It also builds the decision support for the city civil agent-based energy-saving system, realizing the basic institutions of the agent to propose the energy-saving urban civil decision.

The Full Knowledge of Big Data in the Integration of Inter-Organizational Information

2017 ◽  
Vol 9 (1) ◽  
pp. 16-31 ◽  
Author(s):  
Thiago Poleto ◽  
Victor Diogho Heuer de Carvalho ◽  
Ana Paula Cabral Seixas Costa
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Decision Making Process ◽  
Data Repositories ◽  
Modeling And Analysis ◽  
Incremental Change ◽  
Working Together ◽  
Full Knowledge ◽  
Using Data

Big Data is a radical shift or an incremental change for the existing digital infrastructures, that include the toolset used to aid the decision making process such as information systems, data repositories, formal modeling, and analysis of decisions. This work aims to provide a theoretical approach about the elements necessary to apply the big data concept in the decision making process. It identifying key components of the big data to define an integrated model of decision making using data mining, business intelligence, decision support systems, and organizational learning all working together to provide decision support with a reliable visualization of the decision-related opportunities. The concepts of data integration and semantic also was explored in order to demonstrate that, once mined, data must be integrated, ensuring conceptual connections and bequeathing meaning to use them appropriately for problem solving in decision.

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