Application Of Decision Support System Research Articles

Decision Support System to Determine Scholarship Recipients using Analytical Hierarchy Process Method

Every year, the Faculty of Engineering, State University of Jakarta, holds the registration for BBM and PPA scholarships. Each scholarship has certain criteria to determine prospective scholarship recipients. The number of determining criteria and the large number of applicants raises the problem of how to determine prospective scholarship recipients with a large number of criteria for a very large number of applicants. To assist the determination in determining eligible students to receive scholarships, a decision support system is needed. This study aims to produce a decision support system application for determining scholarship recipients using a web-based Analytical Hierarchy Process method. This research was conducted at the Faculty of Engineering, State University of Jakarta from March 2015 to October 2015. The method used in making this decision support system uses the Prototype development method. This web-based decision support system for determining scholarship recipients is made using the PHP programming language and MySQL database with XAMPP as the local server. Functional testing of the website was tested by 1 expert (Head of Subdivision for Student Affairs, Faculty of Engineering) by inputting 20 sample data for BBM scholarship applicants and 20 sample data for PPA scholarship applicants in 2015 with 15 students quota for BBM scholarship recipients and 14 students quota for PPA scholarship recipients. Based on the results of the functional test on the sample data entered on the website, 15 students received BBM scholarships and 15 students were not accepted as recipients of BBM scholarships and in the PPA scholarship, 14 students were accepted as recipients of PPA scholarships and 16 students were not accepted as recipients of PPA scholarships. Therefore, it can be concluded that the decision support system using the AHP method functions well and can be used in the process of determining scholarship recipients at the Faculty of Engineering, State University of Jakarta

Decision Support System for Giving Annual Bonus at PT. Vizta Pratama by Using the Analytical Hierarchy Process (AHP) Method

PT Vizta Pratama Bengkulu is a branch of a franchise company engaged in family karaoke entertainment services, founded by a well-known dangdut singer, Inul Daratista and starting its first operation in 2005 in Kelapa Gading area. PT. Vizta Pratama Bengkulu has not used the Decision Support System Application. The decision to determine the recipient of the annual bonus is only to calculate the total value based on 3 criteria, namely responsibility, discipline, honesty without using a decision support method, therefore sometimes it is felt that the giving of employee annual bonuses is not right on target. Decision support system for giving annual bonus at PT. Vizta pratama using the analytical hierarchy process (AHP) method is a desktop-based application that has implemented the AHP (Analytical Hierarchy Process) method, this application runs on a Windows operating system created using the Visual Basic .NET programming language and SQL Server 2008r2. This application can be used to assist in the assessment process in determining the annual bonus at PT. Vizta Pratama Bengkulu where this application uses 4 predetermined criteria and then processed using the AHP (Analytical Hierarchy Process) method so as to produce values that will be ranked. Based on the results of the Blackbox testing that has been carried out, it can be concluded that the decision support system for providing annual bonuses at PT. Viztapratama by using the analytical hierarchy process (AHP) method is able to run well and can overcome data input errors by users and the SPK application with the Analytical Hierarchy Process method has provided effective results in accordance with the results of calculations using paired comparisons of 4 criteria where the comparison of pairs of criteria must produce consistent weighting criteria.

Implementation of the Additive Ratio Assessment (ARAS) Method for Employee Performance Assessment in the Office of Perum Bulog

Employee Performance Appraisal is very important, especially for employees in the scope of Perum BULOG Divre Bengkulu to encourage motivation and professionalism of employees in improving work quality. Constraints faced in conducting performance appraisals are due to the diversity of educational backgrounds, experiences, competencies and employee portfolios, so we need a system that can assist in the performance appraisal process so that the Employee Performance Appraisal does not become slow and experience difficulties. In the process of designing an employee performance appraisal decision support system application design uses the ARAS approach. The ARAS (Additive Ratio Assessment) method is one of the multicriteria decision-making methods based on the ranking concept using the utility degree, namely by comparing the overall index value of each alternative to the overall index value of the optimal alternative. The system implementation uses the Visual Basic 2010 programming language and the method used in this research is the waterfall method. From the results of the tests carried out, it can be concluded that this decision support system can provide selected employee decisions which later can be used as a reference for determining the quality of employee performance.

Acceptance of clinical decision support systems in Saudi healthcare organisations

Applications of clinical decision support systems (CDSS) have become essential for physicians seeking to make appropriate decisions. The implementation of CDSS, however, is complicated if the factors affecting physician’s acceptance are not recognised. This study aims to explore the various factors that may influence the acceptance of CDSS in Saudi Arabia. A qualitative method was used to collect data from interviews with 54 GPs, with interviews conducted in three stages. The study then integrated the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-Technology Fit (TTF) models to communicate the findings. It is suggested that all factors of both UTAUT and TTF influence acceptance of CDSS by GPs, with the sole exception of the social influence factor. Some additional factors were also discovered by means of in-depth interviews, including accessibility, patient satisfaction, informativeness (increased knowledge), connectedness (informing patients), communication and shared knowledge, privacy and security, and perceived risk (functional performance risk and time risk). The study thus offers a new insight of the factors influencing GPs’ acceptance of CDSS.

THE USE OF GEOSPATIAL INFORMATION BY PUBLIC AUTHORITIES TO SUPPORT THE DECISION MAKING OF MANAGEMENT

The article proposes the use of geospatial information to support managerial decision-making by public authorities in the field of reintegration of temporarily occupied territories in Donetsk, Luhansk regions and Crimea. Variants of application of decision support systems in the management of immovable military property of the Armed Forces of Ukraine, the existing algorithms and methods of the decision support system in land relations are analyzed. Proposals are presented to support the adoption of managerial decisions by public authorities on the basis of Earth remote sensing data. The algorithm for the functioning of the decision support system in solving the problems of reintegration of temporarily occupied territories has been improved. The proposed sequence of actions of the method of the process of supporting the adoption of administrative decisions by public authorities in the field of reintegration of temporarily occupied territories using geospatial information, mathematical constructions of category theory and predicate logic. The order of implementation of the sequence of actions of this method is given. By improving and detailing the proposed method, it is possible to form a more effective system for supporting the adoption of managerial decisions by public authorities using geospatial information.

Application of Clinical Decision Support System to Assist Breast Cancer Patients with Lifestyle Modifications during the COVID-19 Pandemic: A Randomised Controlled Trial.

Clinical decision support systems (CDSS) are data aggregation tools based on computer technology that assist clinicians to promote healthy weight management and prevention of cardiovascular diseases. We carried out a randomised controlled 3-month trial to implement lifestyle modifications in breast cancer (BC) patients by means of CDSS during the COVID-19 pandemic. In total, 55 BC women at stages I-IIIA were enrolled. They were randomly assigned either to Control group, receiving general lifestyle advice (n = 28) or the CDSS group (n = 27), to whom the CDSS provided personalised dietary plans based on the Mediterranean diet (MD) together with physical activity guidelines. Food data, anthropometry, blood markers and quality of life were evaluated. At 3 months, higher adherence to MD was recorded in the CDSS group, accompanied by lower body weight (kg) and body fat mass percentage compared to control (p < 0.001). In the CDSS arm, global health/quality of life was significantly improved at the trial endpoint (p < 0.05). Fasting blood glucose and lipid levels (i.e., cholesterol, LDL, triacylglycerols) of the CDSS arm remained unchanged (p > 0.05) but were elevated in the control arm at 3 months (p < 0.05). In conclusion, CDSS could be a promising tool to assist BC patients with lifestyle modifications during the COVID-19 pandemic.

Computing Competency for Civil Engineering Graduates: Recent Updates and Developments in Saudi Arabia and the US

This paper discusses recent updates and developments of computing-based courses in the civil engineering discipline. Competency in computing is one of the most important capabilities for university graduates to obtain given the rapid development of computer technology in professional work. Civil engineering is no exception. In fact, many contemporary civil engineering projects require a high degree of computing skills, ranging from performing basic office work to programming for decision support system application in controlling flood water gates to executing construction automation via digital printing technology. However, the curriculum content for computing in civil engineering has been developmentally stagnant in the past several decades. This could be partly due to learning outcomes for civil engineering graduates, which do not explicitly mention a certain degree of achievement with respect to computing skills. Several computing-based courses offered in various civil engineering programs across Saudi Arabia and the US were examined, and their contents were compared to recent survey results administered by the American Society of Civil Engineering Technical Committee on Computing and Information Technology. The discussion is extended by examining technical courses offered in the Civil Engineering Program in Prince Mohammad Bin Fahd University with respect to computing skills. The outcomes of this study are expected to give input and suggestions for future upgrades of computing-based courses offered within the civil engineering curriculum.

Decision Support System Applications for Scheduling in Professional Team Sport. The Team's Perspective.

Background: Periodization implies the systematic planning of training and competition with the goal of reaching the best possible performance in the most important competition. In team sports, this consists of finding a flight-and-practice schedule that maximizes the opportunities to perform the periodized contents (e.g., trips, practices, games, and days off). This process is conducted whilst considering known constraints (e.g., competitive schedule, roster availability, weather, especial events, holidays, or emotional effect of days away). The way a scheduling decision support system (DSS) leads users to make a decision should allow for flexibility, whilst minimizing users' confusion and facilitating the understanding of the recommendation given by the scheduling decision support system. Traditional approaches to solving scheduling problems use either simulation models, analytical models, heuristic approaches or a combination of these methods. When it comes to evaluate how the scheduling DSS is performing, three overarching aspects need to be reviewed: context satisfaction, process efficiency, and output quality. Appropriate training periodization and scheduling of trips and training sessions are critical for teams to optimize training and recovery processes in order to maximize health and performance. This article presents a methodological framework for designing decision-support systems for scheduling in professional team sports.

Sistem Pendukung Keputusan Menentukan Pengangguran Untuk Pembinaan Kerja Pada Desa Menggunakan Metode (SAW)

Social assistance for the community is the main task and mission of the government to improve the welfare of the nation and state. Therefore, the government continues to innovate about social assistance in the community, especially in Gumukrejo Village. In running the social assistance program, the local government and Gumukrejo Village work together to minimize the distribution of assistance that is not on target. This research was motivated when the author conducted observations and interviewed one of the Gumukrejo Village staff, it was concluded that the lack of knowledge of residents about the conditions for providing assistance and the absence of definite criteria from Gumukrejo Village when providing assistance, therefore, a decision support system was needed to assist village staff in determining recipients of social assistance, a Decision Support System application was made about Determining recipients of social assistance based on 4 criteria. Namely Income, Marital Status, Number of dependents, and age. The decision support system method used is the Simple Additive Weighting (SAW) method. Where the results of this decision support system are in the form of ranking prospective recipients of social assistance according to the final value of the results obtained. With the creation of this social assistance recipient decision support system, it is hoped that it will be able to facilitate the distribution of aid recipients in Gumukrejo Village and in other villages.

Patient-Tailored Decision Support System Improves Short- and Long-Term Glycemic Control in Type 2 Diabetes.

The increasing prevalence of type 2 diabetes mellitus (T2D) and specialist shortage has caused a healthcare gap that can be bridged by a decision support system (DSS). We investigated whether a diabetes DSS can improve long- and/or short-term glycemic control. This is a retrospective observational cohort study of the Diabetiva program, which offered a patient-tailored DSS using Karlsburger Diabetes-Management System (KADIS) once a year. Glycemic control was analyzed at baseline and after 12 months in 452 individuals with T2D. Time in range (TIR; glucose 3.9-10 mmol/L) and Q-Score, a composite metric developed for analysis of continuous glucose profiles, were short-term and HbA1c long-term measures of glycemic control. Glucose variability (GV) was also measured. At baseline, one-third of patients had good short- and long-term glycemic control. Q-Score identified insufficient short-term glycemic control in 17.9% of patients with HbA1c <6.5%, mainly due to hypoglycemia. GV and hyperglycemia were responsible in patients with HbA1c >7.5% and >8%, respectively. Application of DSS at baseline improved short- and long-term glycemic control, as shown by the reduced Q-Score, GV, and HbA1c after 12 months. Multiple regression demonstrated that the total effect on GV resulted from the single effects of all influential parameters. DSS can improve short- and long-term glycemic control in individuals with T2D without increasing hypoglycemia. The Q-Score allows identification of individuals with insufficient glycemic control. An effective strategy for therapy optimization could be the selection of individuals with T2D most at need using the Q-Score, followed by offering patient-tailored DSS.

Three-Way Image Classification with Evidential Deep Convolutional Neural Networks

The farfetched certain classification of uncertain data suffers serious risks. Three-Way Decision (3WD) theory is utilized to implement uncertain data classification methods. Three-way uncertain data classification methods facilitate reducing decision risk and involving human–machine coordination through finding out uncertain cases for abstaining identification. Due to the limitation of traditional classifiers in feature learning, most existing three-way uncertain data classification methods are not good at handling the unstructural data of digital images. This shortage hinders the applications of three-way uncertain data classification in image-based decision support systems, such as the medical decision support systems based on radiographs. In this paper, we adopt deep convolutional neural networks (DCNNs) for feature learning and Dempster–Shafer (D-S) evidence theory as uncertainty measure to implement a three-way method for image classification. We utilize evidence theory to measure the uncertainty of the predictions produced by DCNNs and construct a novel evidential deep convolutional neural network (EviDCNN). Based on this, we propose a Three-Way Classification method with EviDCNN (EviDCNN-3WC). The experiments on massive medical image data sets validate that the proposed three-way classification method with EviDCNN is effective to identify uncertain images and reduce the risk in image classification. The superiorities of the proposed method facilitate its applications in image-based medical decision support systems.

Application of risk-based fuzzy decision support systems in new product development: An R-VIKOR approach

Innovative manufacturing firms strive to sustain and enhance their competitive advantages by running a range of new product development (NPD) projects in a consistent manner. The capital and time required to execute the NPD projects have substantially increased over the past years. This magnified the risk-aversion behavior of R&D managers and has increased their sensitivity towards the underlying risk of NPD projects. In particular, the R&D departments have recently started to proactively assess the accuracy of ambiguous information that is extensively used in preliminary market study and customer requirements analysis. Thanks to its high performance in dynamic environments, the R-numbers method can be employed to capture and analyze the risk of fuzzy numbers in a variety of decision making models. To tackle the complexity of such analysis, this paper proposes a novel risk-based fuzzy VIKOR (R-VIKOR) methodology. Using the interpretive structural modeling, the risk factors are first classified to identify and rank the existing critical risk factors of NPD projects. The ultimate goal of this study is to develop a practical yet simple decision support system tool that enables the R&D managers to effectively examine the riskiness of fuzzy information and assess the relevant risk factors. A real-world case study is presented to test and examine the accuracy and effectiveness of the proposed risk management method.

Decision Support System for Determining Employee Bonus Using Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Method At Spin Warriors Indonesia

Spin Warriors Indonesia has a number of employees who help in its development, employees are the main factor in the smooth running, progress and success of a company. Therefore, the provision of employee bonus allowances is carried out so that it affects all aspects of employee work. In general, the appraisal process for each employee takes a long time and is not necessarily accurate. All that happened because it used manual calculations. Based on the problems, a decision support system application was create which aims to simplify and perform a fast calculation process. This application uses the AHP and SAW methods which can provide accurate result because these methods have their respective advantages that complement each other. To test the system that was made then 7 users were distributed and filled out a questionnaire. Based od questionnaires that have been distributed and filled out by users, the results show that about 67.1% of respondents said they were quite satisfied with this application. Based on this data, it can be said that this application is useful for users to assist and facilitate companies in determining employee bonuses

Decision Support System for Diagnose Hepatitis Type using Expert System Method

In the medical world, there are five types of Hepatitis, namely Hepatitis A, B, C, D, and E. However, the five types of hepatitis have similar symptoms, including yellowing of the skin color, yellowing of the eyeball, loss of appetite, etc. Thus, many of the Medical Personnel often misdiagnose the patient for the type of hepatitis or not suffer from hepatitis.Therefore, previous diagnostic data ware collected from Medical Specialists which will be processed and developed into the Java-based Decision Support System Application with Expert System method with the percentage output of the likelihood of patients from each type of hepatitis along with the possibility of patients not suffering from hepatitis.With the output of this application, the percentage of the possibility of each type of hepatitis or the possibility of not suffering from hepatitis can help Medical Personnel to make diagnostic decisions based on alternatives provided by the application.

Penerapan Metode Profile Matching untuk Pendukung Keputusan Pemilihan Manajer Information Technology

The selection of an IT manager in a company has an important role in a decision, because a manager occupies a managerial level position who will make decisions later. The current process of selecting IT managers is still being carried out conventionally, resulting in several problems. Among them, the assessment is carried out manually so that the calculation process can occur errors and take longer, then which alternative is the best according to the recommendation of the decision support system (DSS) application. To overcome some of these problems, a DSS was designed which resulted in more precise and effective decisions. The method used is the Profile Matching method which is used to determine alternative rankings, where the criteria and weight values ??have been determined and are contained in the assessment document. This research produces a web-based DSS application that helps decision making in selecting IT managers. This DSS application will simplify the calculation of the assessment thereby reducing calculation errors. The end result of implementing DSS for the selection of IT managers is that the selection process becomes more precise, effective and objective

Sistem Penunjang Keputusan Penerimaan Karyawan Baru Dengan Metode Profile Matching

One of the most important activities in a company or organization is the human resources. The recruitment process is a strategic stage to identify the appropriate candidates. When the recruitment process is not conducted properly, the new employees will not meet the criteria expected by the company.a decision support system application for a new employee recruitment in this research was built using the Profile Matching Method. In general, the Profile Matching Process is the process of comparing competencies between individuals and jobs or occupations to determine the suitability. The comparison was made by calculating the test scores of the recruits to get the rating scores that would serve as references in determining the decisions in the recruitment process.In applying the Profile Matching Method, determining the weight value for each aspect of the test greatly affects the final calculation of the ranking value of each employee, therefore the determination of the greatest weight value will be given to the priority aspects of the test in order to obtain the results of the selection according to the predetermined priorities according to the company's needs.Keywords: employee selection, profile matching, decision support system

Sine trigonometric spherical fuzzy aggregation operators and their application in decision support system, TOPSIS, VIKOR

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws $\left( STL\right) $ for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

Software and Hardware Decision Support System for Operators of Electrical Power Systems

The transience and unpredictability of processes in electric power systems (EPS) determine complexity of its control. This problem is especially relevant for EPS with renewable energy sources and flexible alternating current transmission systems technologies. Automatic control systems simplify the solution of this problem. Despite this, many issues related to EPS state control are solved by power system operators. Decision support systems (DSS) are applying to increase efficiency of operators work. However, existing algorithms in practice are inoperable in some cases: unrealizable decisions are formed, or decision cannot be found at all, etc. Another important problem is impossibility to preliminarily verify the proposed solution. In this regard, operators can additionally use EPS simulators, which are usually limited either by the size of simulated scheme or by the details of equipment mathematical models. The limitations are a consequence of numerical methods using, which are badly applicable for large-scale power systems simulation. In this article, a novel DSS has been developed based on a hybrid approach to EPS modeling combining properties and capabilities of several simulation techniques: analog, physical and digital. The implicit integration of differential equations in analog way makes possible modeling faster than real time. Such opportunity allows operator to verify more decisions and select the most effective ones. The algorithm for DSS application has been developed and described in the article. The properties and capabilities of the developed DSS are confirmed by experimental studies and tests in a real EPS.

Supporting Brazilian smallholder farmers decision making in supplying institutional markets

Smallholder farmers are amongst the most vulnerable communities in developing countries, lacking a stable income due to inconsistent access to markets. Aiming to tackle rural poverty, the Brazilian government established institutional markets for smallholder farmers to supply their produce to schools through a non-competitive bidding mechanism. However, participation of farmers is still limited due to the challenging decision-making process.Aspiring to contribute towards increasing their participation, this study aims to support farmers into two key decisions they face during sequential stages of the bidding process, namely whether to bid for each available school and product combination and whether subsequently to accept the awarded bids once the bids’ outcome is known. A decision support system, based on two sequential MILP optimisation models, was developed and applied to the case study of Canudos settlement, guiding farmers on the optimal bidding and contract acceptance strategy.This study contributes to the decision support systems field by applying OR methods to a real-life problem within a new context. It is the first application of an OR-based decision support system in the non-competitive bid/no-bid literature, defining an optimal bidding strategy through the application of optimisation methods to maximise profitability while removing subjectivity from the decision-making process. Moreover, it is the first decision support system within the bid/no-bid decision-making field being applied to the agricultural and institutional market context. The proposed approach could have a significant social impact for smallholder farmers in Brazil, improving their living conditions by providing security of income and strengthening inclusive agricultural growth.

Multistakeholder Participation in Disaster Management-The Case of the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic is affecting society’s health, economy, environment and development. COVID-19 has claimed many lives across the globe and severely impacted the livelihood of a considerable section of the world’s population. We are still in the process of finding optimal and effective solutions to control the pandemic and minimise its negative impacts. In the process of developing effective strategies to combat COVID-19, different countries have adapted diverse policies, strategies and activities and yet there are no universal or comprehensive solutions to the problem. In this context, this paper brings out a conceptual model of multistakeholder participation governance as an effective model to fight against COVID-19. Accordingly, the current study conducted a scientific review by examining multi-stakeholder disaster response strategies, particularly in relation to COVID-19. The study then presents a conceptual framework for multistakeholder participation governance as one of the effective models to fight against COVID-19. Subsequently, the article offers strategies for rebuilding the economy and healthcare system through multi-stakeholder participation, and gives policy directions/decisions based on evidence to save lives and protect livelihoods. The current study also provides evidence about multidimensional approaches and multi-diplomatic mechanisms during the COVID-19 crisis, in order to examine dimensions of multi-stakeholder participation in disaster management and to document innovative, collaborative strategic directions across the globe. The current research findings highlight the need for global collaboration by working together to put an end to this pandemic situation through the application of a Multi-Stakeholder Spatial Decision Support System (MS-SDSS).