Decision Support System Approach Research Articles

Towards a knowledge-based decision support system to foster the return to work of wheelchair users

Accidents at work may force workers to face abrupt changes in their daily life: one of the most impactful accident cases consists of the worker remaining in a wheelchair. Return To Work (RTW) of wheelchair users in their working age is still challenging, encompassing the expertise of clinical and rehabilitation personnel and social workers to match the workers’ residual capabilities with job requirements. This work describes a novel and prototypical knowledge-based Decision Support System (DSS) that matches workers’ residual capabilities with job requirements, thus helping vocational therapists and clinical personnel in the RTW decision-making process for WUs. The DSS leverages expert knowledge in the form of ontologies to represent the International Classification of Functioning, Disability, and Health (ICF) and the Occupational Information Network (O*NET). These taxonomies enable both workers’ health conditions and job requirements formalization, which are processed to assess the suitability of a job depending on a worker’s condition. Consequently, the DSS suggests a list of jobs a wheelchair user can still perform, exploiting his/her residual abilities at their best. The manuscript describes the theoretical approach and technological foundations of such DSS, illustrating its development, its output metric, and application. The developed solution was tested with real wheelchair users’ health conditions provided by the Italian National Institute for Insurance against Accidents at Work. The feasibility of an approach based on objective data was thus demonstrated, providing a novel point of view in the critical process of decision-making during RTW.

Analisis Metode SAW-WP-TOPSIS Dan Borda Count Pada Sistem Pendukung Keputusan Pemilihan Supervisor

A supervisor is a person who is responsible or has the authority to regulate the procedures for carrying out tasks in a company. The supervisor is the expert of all experts. Due to the important role of a supervisor, the selection of a supervisor must be appropriate, this can sometimes be a problem, if there are many candidates with the same abilities. To solve this problem, a Decision Support System (DSS) approach is used. The criteria used are: age, length of work, performance and absenteeism. This research uses 4 SPK methods, namely the SAW, WP, TOPSIS and borda count methods. Of the four methods, we will compare which method is more relevant for solving this problem using the Hamming Distance method. The results of this research show that the WP method is the most relevant method with the smallest percentage, namely, 47.15%, which means the WP method has the smallest level of nonconformity compared to the other 3 methods, namely SAW 56.81%, TOPSIS 82.95% and borda count 52.72%.

Investigating obstacles to the development of rural knowledge-based and technological systems in the agricultural sector of Sistan Region under the Decision Support System (DSS) approach

Investigating obstacles to the development of rural knowledge-based and technological systems in the agricultural sector of Sistan Region under the Decision Support System (DSS) approach

Contextual relationships in Juran’s quality principles for business sustainable growth under circular economy perspective: a decision support system approach

Contextual relationships in Juran’s quality principles for business sustainable growth under circular economy perspective: a decision support system approach

Unveiling groundwater potential zones as catalyst for multidimensional poverty reduction using analytical hierarchical process and geospatial decision support systems (S-DSS) approach in the semiarid region, Jigawa, Nigeria

Integrating agricultural production with the identification and use of groundwater resources has been shown to reduce multidimensional poverty in semi-arid regions. Poverty reduction and socioeconomic growth depend on sustainable water supply, especially in developing countries with limited rainy seasons. Poverty eradication is a top priority among the 17 Sustainable Development Goals (SDGs), and its reduction in the 21st century has led to significant advances in research. This study used remote sensing, geographic information system (GIS), and geospatial decision support system (S-DSS) approaches to uncover potential groundwater zones. The Analytic Hierarchy Process (AHP) integrates geospatial data to create a groundwater potential zone map and suggests the best land requirements for groundwater abstraction for poverty alleviation programs. The groundwater potential zone maps indicate that the majority of the region was in the high-potential zone, covering 59.75% of the total area, followed by a moderate-potential zone at 23.21%, an extremely high-potential zone at 14.6%, a low-potential zone at 2.44%, and an extremely low-potential zone at 0%. In addition, the study emphasizes the need for alternative water sources and infrastructure development in dry seasons in areas with fewer drainage systems and proposes measures such as rainwater harvesting structures and small reservoirs. Diversifying income sources by promoting alternative livelihoods can help reduce poverty and vulnerability to fluctuations in agricultural productivity. The integration of socioeconomic data into the S-DSS framework will provide a comprehensive understanding of the complex relationship between groundwater resources, poverty, and socioeconomic development, enabling informed decision-making in water resource management for poverty reduction initiatives and the achievement of the 2030 Agenda for Sustainable Development Goals.

Distribution Channel Selection Using FUCOM-ADAM: A Novel Approach

The selection of the appropriate distribution channel is crucial for the success of any business dealing with physical goods. When dealing with this selection, it is crucial to have an effective decision support system (DSS) that can assist with such decisions. While various DSS approaches exist in the literature, not all are suitable for real-world applications. This research aims to address this gap by developing practical DSS tools that can aid decision-makers in making optimal decisions even in situations of uncertainty. The paper explores six different distribution channels (retailer’s warehouse, wholesaler’s warehouse, manufacturer’s warehouse, cross-dock, 3PL services, and direct delivery) in order to select the optimal one based on nine established criteria (inventory costs, distribution costs, delivery speed, service level, market coverage, product availability, order consolidation capability, reverse logistics, and order tracking) by using the FUCOM (Full Consistency Method) and ADAM (Axial-Distance-Based Aggregated Measurement) methods. After applying the FUCOM method, C1 (inventory costs) had the highest value when observing criteria weights, whereas C9 (order tracking) had the lowest. The results of the ADAM method showed that A5 (3PL services) was the best-ranked alternative, whereas A4 (cross-dock) was ranked as the worst. Based on the results, a model validation, and sensitivity analysis was conducted to determine whether the final ranking of the alternatives will change. This research provides decision makers with the necessary tools for better decision making, leading to improved distribution operations and increased profitability for the business.

Thyroid Nodule Detection and Region Estimation in Ultrasound Images: A Comparison between Physicians and an Automated Decision Support System Approach.

Thyroid nodules are very common. In most cases, they are benign, but they can be malignant in a low percentage of cases. The accurate assessment of these nodules is critical to choosing the next diagnostic steps and potential treatment. Ultrasound (US) imaging, the primary modality for assessing these nodules, can lack objectivity due to varying expertise among physicians. This leads to observer variability, potentially affecting patient outcomes. This study aims to assess the potential of a Decision Support System (DSS) in reducing these variabilities for thyroid nodule detection and region estimation using US images, particularly in lesser experienced physicians. Three physicians with varying levels of experience evaluated thyroid nodules on US images, focusing on nodule detection and estimating cystic and solid regions. The outcomes were compared to those obtained from a DSS for comparison. Metrics such as classification match percentage and variance percentage were used to quantify differences. Notable disparities exist between physician evaluations and the DSS assessments: the overall classification match percentage was just 19.2%. Individually, Physicians 1, 2, and 3 had match percentages of 57.6%, 42.3%, and 46.1% with the DSS, respectively. Variances in assessments highlight the subjectivity and observer variability based on physician experience levels. The evident variability among physician evaluations underscores the need for supplementary decision-making tools. Given its consistency, the CAD offers potential as a reliable "second opinion" tool, minimizing human-induced variabilities in the critical diagnostic process of thyroid nodules using US images. Future integration of such systems could bolster diagnostic precision and improve patient outcomes.

Optimization of Inventory Ordering Decision in Retail Business using Exponential Smoothing Approach and Decision Support System

In the context of a challenging retail business, optimizing inventory ordering decisions is crucial to maintain product availability and avoid excessive storage costs. Decision Support System (DSS) approach with the application of exponential smoothing method has emerged as an effective solution to integrate data analysis and more precise decision making. This abstract discusses how exponential smoothing is used in optimizing inventory ordering decisions in retail businesses. We explain the concept of exponential smoothing as a forecasting technique that integrates historical data and future predictions. We also analyze the steps of implementing exponential smoothing in DSS, including smoothing parameters, initialization of initial levels, and forecast calculation. The benefits and challenges in the use of exponential smoothing are discussed in the context of inventory optimization and ordering decision making. The results show that exponential smoothing can provide forecasts that are more adaptive and responsive to changes in demand, with the potential to improve operational efficiency and customer satisfaction. Nonetheless, an understanding of the product characteristics and limitations of the method needs to be considered. This research illustrates how the use of exponential smoothing in DSS can provide valuable guidance for retailers in optimizing inventory and making inventory decisions.

Implementation of Simple Additive Weights To Determine Priorities For The Resolution of Information Technology Problems

The Regional Secretariat of West Java Province (Setda Jabar) is a government agency within the local government environment in West Java Province. Along with the development of information technology, using technology such as computers and the internet in a government agency is very important to support work. There are times when devices and systems do not work correctly, such as internet disturbances and computer software and hardware problems handled by technicians. Technicians not only manage information technology infrastructure at the West Java Regional Secretariat but also manage information technology infrastructure in three (3) official houses. Technicians are also faced with an organizational structure with many bureaus and sections. There is yet to be a definite procedure in the complaint reporting process. There is no helpdesk system as a reporting medium. With the many bureaus, the number of information technology facilities served so that technicians find it difficult to determine the priority of the work that must be served first. Given these problems, a Decision Support System approach uses the Simple Additive Weight method by using determining criteria and weights. The criteria used include Work Units, Positions, Types of Complaints, and Official Notes. The system development method used is Object Oriented Analysis Design (OOAD). This system is expected to assist technicians in determining services that match their needs and situations.

A Machine Learning-Based Decision Support System for Predicting and Repairing Cracks in Undisturbed Loess Using Microbial Mineralization and the Internet of Things

Recent years have seen a significant increase in interest across several sectors in the application of learning techniques to extract ground object information, such as soil cracks, from remote sensing high-resolution images. Out of the many technologies, the microbial-induced carbonate deposition (MICP) technology is used to inject bacteria and cementation liquid containing specific bacteria into the cracks of soil to be repaired. Calcium carbonate types of cement are produced by bacterial metabolism so that cracks in the soil could be repaired for disaster management. However, detection of cracks and taking appropriate decisions for repairing are the most fundamental issues that researchers’ attention. Machine learning algorithms can be trained to detect and predict cracks in undisturbed loess using various data sources, such as images captured using the internet of things (IoT), devices, drones, and/or ground-based sensors. These algorithms can be designed to identify different types of cracks based on their shapes, sizes, and orientations, and can be trained on large datasets of labelled crack images to improve their accuracy over time. In this paper, we propose a decision support system (DSS) that detects and predicts cracks and recommends a suitable crack repair methodology. Our results show that our system is highly accurate. Our system provides real-time recommendations to engineers working on crack repair projects in undisturbed loess, guiding them on where and how to apply microbial mineralization treatments based on the predicted crack locations and treatment effectiveness. We noted that the accuracy of the crack detection and prediction can be increased significantly (up to 9.57%) when the proposed DSS approach is considered. Moreover, if PSO is implemented as the optimization model, then we can see that the accuracy can be significantly improved by as much as 21.67% to no DSS approach and 11.32% to the DSS approach.

DAAR: Drift Adaption and Alternatives Ranking approach for interpretable clinical decision support systems

Diagnosing allergy comorbidities is challenging because the comprehensive studies on the prevalence of each allergy and the relation with other diseases are scarce. Moreover, there is a chance for uncertainty in the intradermal skin test results due to poor administration, manual observation and interpretation. Hence this work aims to develop a Decision Support System (DSS) for enhancing the diagnosis of allergy comorbidities. The DSS framework consists of a knowledge engineering phase and decision-making phase. The former focuses on detecting the concept drift, pre-processing the data, and extracting the knowledge, whereas, the latter focuses on the DAAR approach for adapting the concept drift and ranking the alternatives. The intradermal skin test data collected from allergy testing centre in India during 2012 and 2019 is used for developing and evaluating the DSS. The three techniques of concept drift adaption, namely, replacement, ensemble, and incremental are experimented on both balanced and unbalanced datasets. It can be observed from results that the incremental adaption technique has achieved an accuracy of 70.28% and 54.94% with complete decision, and 91.42% and 76.37% with partial decision on query data of 2012 and 2019 respectively. Moreover, the accuracy of the incremental technique is above the average of the accuracies of state-of-art machine learning algorithms. This implies that the framework is capable of supporting clinicians in choosing an optimal decision from the preference order of alternatives. Moreover, the interpretable knowledge provided by the system about all possible combinations of alternatives aids clinicians in understanding the reasoning behind their choice.

Use of a Socio-Ecological Framework and MFA to Assess the Resilience of Local Food Chain Systems

This paper proposes the basic procedures to examine the biodiversity of food chain systems using cross-disciplinary methods based on social, ecological, and material dimensions. The application of SES and MFA methods to track internal and external disturbances in the food chain highlights some of the flaws and gaps in this decision support system approach. In contrast to the single method, this SES-MFA overlapping approach contributes more information, including the literature on local food governance. Furthermore, the SES-MFA method would offer recommendations to researchers and policy practitioners to manage changes in the food chain system to attain uninterrupted biodiversity sustainability.

Decision Support System to Determine Higher Education Resource Needs Using Accreditation Assessment Standards

Accreditation is an activity to evaluate the eligibility of programs and academic units based on predetermined criteria. In an educational institution, accreditation is an important thing to do to improve quality in the field of education because the aim is to improve quality which includes all aspects of education in the form of science, administration, as well as teaching, and educational staff. College managers really need a decision support system that can produce several alternative strategic decisions quickly and accurately. The existence of decision support system tools used to make strategic decisions makes the manager's work lighter and the results are more accurate. In this study, a decision support system approach was applied to determine the resource requirements of tertiary institutions using accreditation assessment standards consisting of a management subsystem model, data management subsystem, and user interface management subsystem. The result of the research is a design of a decision support system that can be used in an educational institution for determining the need of higher education resources.

Decision Support System For Selecting The Best Practical Work Students Using MOORA Method

This research aims to solve the problem of selecting the best practical work students at the Politeknik Bisnis Indonesia. The current selection of the best practical work students at PBI does not yet use a decision support system approach. This problem is solved by building a Decision Support System using Multi-Objective Optimization based on Ratio Analysis (MOORA) method. The criteria used in this DSS consist of discipline, teamwork, skills, quality of work, and attendance. As for the results of data processing from this study, the three best alternative data were obtained, namely alternative Vivi (A6) as the 1st best Practical Work Students with a score of Yi = 36.5954, Hafiz (A1) as the 2nd best Practical Work Students with a score of Yi = 34.5339, Cahaya (A3) as the 3rd best PKL student with a score of Yi = 33.4767. Through this decision support system that has been built, the selection of the best practical work students can be made quickly and effectively.

Effectiveness of Interventions to Reduce Potentially Inappropriate Medication in Older Patients: A Systematic Review.

Background: Age-related multiple comorbidities cause older adults to be prone to the use of potentially inappropriate medicines (PIM) resulting in an increased risk of adverse events. Several strategies have emerged to support PIM prescription, and a huge number of interventions to reduce PIM have been proposed. This work aims to analyze the effectiveness of PIM interventions directed to older adults. Methods: A systematic review was performed searching the literature in the MEDLINE PubMed, EMBASE, and Cochrane scientific databases for interventional studies that assessed the PIM interventions in older adults (≥65 years). Results: Forty-seven articles were included, involving 52 to 124,802 patients. Various types of interventions were analyzed such as medication review, educational strategies, clinical decision support system, and organizational and multifaceted approaches. In the hospital, the most successful intervention was medication review (75.0%), while in primary care, the analysis of all included studies revealed that educational strategies were the most effective. However, the analysis of interventions that have greater evidence by its design was inconclusive. Conclusion: The results obtained in this work suggested that PIM-setting-directed interventions should be developed to promote the wellbeing of the patients through PIM reduction. Although the data obtained suggested that medication review was the most assertive strategy to decrease the number of PIM in the hospital setting, more studies are necessary. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233484], identifier [PROSPERO 2021 CRD42021233484].

MABAC under non-linear diophantine fuzzy numbers: A new approach for emergency decision support systems

<abstract><p>The Covid-19 emergency condition is a critical issue for emergency decision support systems. Controlling the spread of Covid-19 in emergency circumstances throughout the global is a difficult task, hence the purpose of this research is to develop a non-linear diophantine fuzzy decision making mechanism for preventing and identifying Covid-19. Fundamentally, the article is divided into three sections in order to establish suitable and correct procedures to meet the circumstances of emergency decision-making. Firstly, we present a non-linear diophantine fuzzy set (non-LDFS), which is the generalisation of Pythagorean fuzzy set, q-rung orthopair fuzzy set, and linear diophantine fuzzy set, and explain their critical features. In addition, algebraic norms for non-LDFSs are constructed based on particular operational rules. In the second section, we use non-LDF averaging and geometric operator to aggregate expert judgements. The last section of this study consists of ranking in which MABAC (multi-attributive border approximation area comparison) method is used to handle the Covid-19 emergency circumstance using non-LDF information. Moreover, based on the presented methods, the numerical case-study of Covid-19 condition is presented as an application for emergency decision-making. The results shows the efficiency of our proposed techniques and give precise emergency strategies to resolve the worldwide ambiguity of Covid-19.</p></abstract>

A new fuzzy decision support system approach; analysis and applications

<abstract> <p>The current study proposes the idea of the N-cubic Pythagorean fuzzy set with their basic arithmetic operations to aggregate these sets. We define the score and accuracy functions for the comparison purpose. Finally, we discuss Chang's extent analysis of AHP under the environment of the N-cubic Pythagorean fuzzy set using the idea of triangular N-cubic Pythagorean fuzzy set. As an application, we discuss the reason for the downfall of international airlines using the developed approach.</p> </abstract>

Personalized Al-Quran Memorization Testing System Using Group Decision Support System

Memorizing Al-Quran is one of the most important acts of worship for Muslims. After memorizing some parts of the Al-Qur’an, the hafiz or Al-Qur’an’s memorizer is recommended to repeat or muraja’ah their memorization to strengthen it. This process is usually done in pairs by listening to each other’s memorization or testing by asking questions about Al-Quran. This study proposes a system that can help memorizers test their memorization independently without a partner. The system will perform a memorization test to support the user’s process of memorizing the Al-Quran. The system records and analyzes user data and uses it to personalize memorization testing from time to time. The system was made using the Group Decision Support System (GDSS) approach with the help of several Al-Quran memorizers as decision-makers. The GDSS algorithm used combines Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Geometric Mean to rank surahs based on provided user data. The evaluation was conducted with the help of human evaluators, and the evaluators showed 78% agreement with the system decision.

SAW and Electre Methods Implementation for Scholarship Awardee Decision

This research was conducted to design a Decision Support System as a tool for decision-makers in distributing Bidik Misi Scholarships at the Indonesian Business Polytechnic. The selection of students who volunteered to become recipients of the Bidik Misi Scholarship required the Decision Support System (DSS) approach which implemented the Simple Additive Weighting (SAW) method by weighting the criteria and sub-criteria of each alternative for all attributes. The criteria used in the SAW method in this study consisted of 2 (two) criteria and each of these criteria had sub-criteria. The first criterion is Parents with sub-criteria consisting of the education level, incomes, parents’ coverage. The second criterion is students with sub-criteria consisting of age, academic potential, ownership of the Indonesia Smart Card (KIP). The output obtained from the 5 data analyzed in this study, the final value of the highest alternative preference is 0.9 and the lowest alternative preference value is 0.55. The output obtained by using the Electre method is that the Student_Mari004 alternative eliminates other alternatives.

Determining Goods Delivery Priority for Transportation Service Companies Using SAW Method

This research was conducted aiming to overcome the problem of the effectiveness of the delivery of goods by the Cendrawasi Expeditionary Company which at this time still does not use a decision support system approach. For the process of delivering goods to customers to be carried out effectively, a decision support system is designed that functions to determine the priority of goods to be delivered first. This problem is solved by designing a decision support system using the Simple Additive Weighting (SAW) method which serves to help the Cendrawasi Expeditionary company get recommendations for priority delivery of goods. The SAW method is very appropriate to be used as a decision support tool where in this study three alternative choices of goods that must be delivered first were obtained, namely plywood with a preference value of 99,6, mattress with a preference value of 83,55, and PVC pipes with a preference value of 79,35.