Web-based Decision Support System Research Articles

Web-based spatial decision support system for optimum route to forest fires: A case of Viphya plantations

Efficient access to fire incidents is crucial for successful firefighting operations. This study aimed at developing a web-based spatial decision support system (SDSS) to determine optimal routes to forest fires and risk zones in the Viphya Plantations, Malawi. The system integrates remote sensing analysis to identify fire risk zones and a web-based SDSS to suggest optimal response routes. Remote sensing data was used to map areas prone to forest fires based on factors such as land use/cover type, terrain, and anthropogenic activities. These risk zones were incorporated into the GIS routing decision support system, enabling the generation of optimal routes from fire stations to fire risk zones and reported fire cases. System testing demonstrated the SDSS's capability to provide optimum routing options targeting fire risk hotspots and reported incidents within the plantations. The SDSS facilitated the identification of optimal routes to mitigate transportation costs and provided insights into spatial patterns of fire vulnerability, revealing areas that may be inaccessible within the optimal timeframe. This highlighted the necessity of establishing additional fire stations in high-risk regions to enhance rapid response times. The web-based SDSS proved to be an effective decision support tool for optimizing resource allocation and improving emergency response coordination for fighting forest fires in the Viphya Plantations.

Development of a material selection decision support system for an automotive application

This study presents the development of a material selection decision support system for an automotive rooftop tent. The system uses five parameters of material cost, formability, corrosion resistance, tensile strength and hardness to optimize material choice from a list of aluminium alloy options. This was done before production via the deep drawing process can commence. The parameters were quantified using the average market prices for each alloy, product requirements obtained from the case study and the performance data that was obtained from the uniaxial tensile and hardness tests. These inputs were combined with the developed material selection framework and then programmed into a web-based decision support system for automated, data-driven material selection. The output presents the recommendation for the optimum material that balances cost-effectiveness and performance. The decision support system was successfully used to select the optimum alloy for the rooftop tent. Results show that AA1050 is the optimum material, providing weight reduction at the minimum achievable cost without compromising the product requirements for the rooftop tent. The decision support system is also scalable, and this allows it to be used with larger datasets for different products and processes in the future.

Optimizing Career Choices in the World of Programming: A Web-Based Decision Support System with the Simple Additive Weighting (SAW) Method

Studi ini mengusulkan pengembangan Sistem Pendukung Keputusan (SPK) berbasis web menggunakan metode Simple Additive Weighting (SAW) untuk membantu mahasiswa dalam memilih karir di bidang pemrograman. Dengan mengintegrasikan data dari survei kuesioner online dan observasi, penelitian ini menyoroti kompleksitas pemilihan karir di dunia pemrograman. Kriteria-kriteria seperti gaji, lokasi kerja, dan persyaratan pendidikan diidentifikasi sebagai faktor utama dalam pengambilan keputusan. Metode SAW dipilih karena kemudahan pemahaman, fleksibilitas, dan kemampuannya menangani masalah kompleks. Proses implementasi sistem melibatkan pengumpulan data, observasi, perancangan sistem berbasis web, dan pengembangan website. Hasil akhir menunjukkan bahwa alternatif A3 (Pengembangan perangkat lunak) mendapatkan bobot preferensi tertinggi, menegaskan sebagai pilihan terbaik berdasarkan kriteria yang ditetapkan. Penggunaan SPK diharapkan dapat memberikan panduan yang efektif bagi mahasiswa dalam membuat keputusan karir yang lebih terinformasi.

Implementasi Algoritma Multi-Factor Evaluation Process Pada Website Sistem Pendukung Keputusan Minat Siswa

After graduating from high school, students often have difficulty in determining the right major.The challenges faced include the lack of clear guidelines and criteria in choosing a major, as wellas the selection process which is still traditional and subjective. To overcome these obstacles, thisarticle suggests the implementation of a website-based Decision Support System (DSS) using theMulti-Factor Evaluation Process (MFEP) algorithm. This DSS was developed to help studentschoose a major that suits their interests and potential. The methods used in this study includeliterature studies, observations, interviews, and questionnaires. The results of the study indicatethat the use of a web-based DSS with the MFEP algorithm is able to provide more effective andobjective recommendations in helping students choose a major.

An Integrated Approach for Development of a Decision Support System for Early Surveillance of Japanese Encephalitis: a Remote Sensing-based study in Conjunction with Epidemiological Scenario in Assam, India

Abstract. Japanese Encephalitis (JE) is one of the serious mosquito borne viral diseases mostly prevalent in India and many of the South Asian countries. A comprehensive study was conducted in Dibrugarh, a JE endemic district of Assam taking into the account of the environmental and social factors that determine the outbreak of the disease. Effect of environmental and climatic factors on mosquito vector densities was investigated using geospatial tools and techniques. Wetlands were found to be the most preferred habitat type for most of the JE-transmitting mosquitoes followed by paddy-growing areas and ponds. The villages abundant with these habitats or located nearby were found to be more vulnerable to JE risk. Based on the spatial distribution of habitat types, villages in the district were divided into three categories of vector abundance and hence the risk of JE. It is found that rainfall (intensity as well as duration) is the most significant determinant in the modulation of mosquito density followed by temperature. It is also observed that the derived models could explain about 61% to 73% variation in mosquito density due to change in weather variables as indicated by R2 values of the Models. Among socio-economic determinants, pig rearing habit of the villagers was found to be most significant. JE risk map was prepared by integrating vector abundance map with the map of host abundance in GIS domain. Attempts were also made to forecast the intensity of JE cases based on a time series analysis of historical morbidity pattern, whereas forecast for onset of the disease was based on the modulation of weather variables in the study area. A web-based decision support system (DSS) developed by integrating the forecasts of JE onset, intensity and JE prone villages has been provided to the concerned health authorities to take timely intervention measures. The JE early warning system developed for Dibrugarh district was extended to two more JE prone districts viz, Sibsagar and Tinsukia as validation sites and observed that the accuracy of forecast was within the range of 69% to 77%. DSS on JE has opened up new opportunities to study similar vector-borne diseases of the JE serogroup viz., West Nile.

ROC and COPRAS Algorithms in a Decision Support System for Employee Career Assessment

PT. Union Confectionery, a long-established company in the confectionery production industry, had encountered significant challenges in managing employee career progression, including transfers, demotions, and promotions. The primary issue faced was the difficulty in conducting objective employee performance assessments and determining the appropriate criteria for career development. These assessments involved various complex factors such as work experience, discipline, education level, age, job performance, attendance, teamwork, and work ethics. To address these challenges, this study proposed the implementation of a web-based Decision Support System (DSS) utilizing the Rank Order Centroid (ROC) method for criteria weighting and the Complex Proportional Assessment (COPRAS) method for ranking decisions. The implementation of this system was expected to assist the management of PT. Union Confectionery in making more accurate and transparent decisions, while also improving employee satisfaction and operational efficiency. This research also compared previous studies that used similar methods for performance assessment, albeit with a narrower focus, specifically at the supervisory level. The findings from this study were anticipated to provide a comprehensive and innovative solution for employee career management across all levels of PT. Union Confectionery’s organization, as well as contribute to the development of more effective human resource management practices.

A Web-based Decision Support System for Managing Course Timetabling in Online Education

The COVID-19 pandemic precipitated an abrupt transition from traditional face-to-face instruction to online learning, posing significant challenges in managing course timetabling and ensuring efficient bandwidth utilization. This paper presents the development and implementation of a web-based Decision Support System (DSS) that employs a simulated annealing algorithm to optimize course scheduling in an online education context. Seamlessly integrated with the university's Student Information System (SIS) and Learning Management System (LMS), the DSS enables automated timetable generation and real-time data synchronization. Program coordinators can make necessary adjustments, while students and instructors access their schedules through a user-friendly interface. Experimental results demonstrate a substantial improvement in the distribution of concurrent connections compared to manually generated timetables, significantly reducing peak server loads by up to 66% and standard deviations. The proposed DSS addresses the immediate challenges of the shift to online education while offering a scalable solution for future needs, thereby enhancing the online learning experience for both students and instructors.

Sistem Pendukung Keputusan Penilaian Kinerja Aparatur Desa Berbasis Web Menggunakan Metode Profile Matching (Studi Kasus: Desa Wee Limbu)

The problem raised is how to build a web-based decision support system for village apparatus performance assessment using the profile matching method, Kashus study at the Wee Limbu village office, southwest Sumba district. help carry out assessments using the profile matching method which is carried out to determine the apparatus' recommendations in the assessment system based on behavioral aspects, this decision making process is assisted by a decision support system. One of the methods used is Profile Matching, which is a method that compares the criteria for which alternative candidate places are selected. The road is suitable to be built according to the criteria determined by the Verification Body so that a difference value is obtained which is usually called the gap value. The decision support system designed is a web-based decision support system for assessing apparatus performance using the profile matching method

A Web-based decision support system for sustainable urban planning and management

Urban and territorial planning processes are characterized by a high level of complexity that makes tools management dif?cult. This research presents a Web-GIS prototype for supporting urban planning and management decision-making processes towards social, economic and environmental sustainability. It is designed according to open-source technology and aims to de?ne new planning top-down and bottom-up approaches. The design criteria of this innovative platform respond to the essential principles of transferability, modularity, scalability, and data interoperability. This new tool is applied to a case study to demonstrate how it can support planners and local authorities in urban planning and management processes.

Web-Based Decision Support System for Budget Prediction Using the SAW Method for Tourism Recommendations

Tourism plays a crucial role in regional and national economies, with local tourism in Indonesia, particularly in Jombang Regency, East Java, offering substantial development potential. However, tourists often face difficulties in planning trips that align with their budgets due to inadequate integration of information on costs, trip duration, and participant numbers. This study develops a web-based Decision Support System (DSS) utilizing the Simple Additive Weighting (SAW) method to enhance trip planning for tourism in Jombang. The DSS integrates data on budget, trip duration, and the number of participants to provide optimal recommendations based on user preferences and constraints. The SAW method facilitates a systematic and objective evaluation process for recommending tourist destinations. The research follows the ADDIE development model, encompassing Analysis, Design, Development, Implementation, and Evaluation stages. Key objectives include creating a system that consolidates cost, duration, and participant data, applying SAW for accurate recommendations, and ensuring an objective evaluation process. The system aims to improve trip planning efficiency, provide accurate recommendations, and enhance user satisfaction. The scope of this study is limited to applying the SAW method for budget prediction in tourism recommendations for Jombang. The developed system is a prototype that may require further refinement for comprehensive implementation.

Exam scheduling under pandemic conditions: A mathematical model and decision support system

The scheduling of university exams is a complex task that involves various constraints such as administrative limits, pedagogical needs, student volume, and different courses. The emergence of Covid-19 and future pandemics has added new constraints related to infection prevention and contact tracing. To address these challenges, this study proposes a multi-objective mathematical model that considers university resources, reduced classroom occupancy, and minimized student interaction. The model aims to minimize violations of pandemic-related constraints and categorize exams by difficulty. To facilitate scheduling for entire faculties or universities, a Genetic Algorithm based web-based decision support system is developed. With these tools, the study successfully created an optimal schedule for eight departments simultaneously.

Rancang Bangun SPK Kualitas Air Sungai Metode Fuzzy Tsukamoto (Studi Kasus: 4 Kecamatan Karawang)

Research reveals that the Citarum River in West Java is seriously polluted, causing problems for humans and the environment, so monitoring of river water quality is necessary. This research proposes the development of a web-based Decision Support System with the SDLC Waterfall model, using the Fuzzy Tsukamoto method based on seven water parameters (EC, TDS, Salinity, pH, ORP, SG, Temperature) to simplify the determination of water quality. This research uses the Research and Development methodology with the SDLC Waterfall model software development approach, which includes the stages of analyzing data requirements and fuzzy logic systems, designing system architecture and features, implementing technology and process results, functional manual testing and model accuracy, and maintenance in the form of documentation and storage. The results showed that the developed DSS can classify water quality based on 7 parameters with a value scale divided into five categories, namely Good, Poor, Medium, Good, and Very Good. Testing was conducted using data from 8 river points in 4 sub-districts in Karawang Regency on April 1, 2024. The accuracy of the DSS model reached 80%. The development of this DSS is expected to provide an initial overview of water quality in a location without requiring an in-depth technical understanding of the water parameters used. This data can also be an initial indicator to determine whether further action or further investigation is required. Suggestions for future research are to integrate the system with IoT to improve its performance and benefits.

Systematic risk ranking of microbiological hazards in infant foods

Ensuring food safety, particularly for vulnerable groups, like infants and young children, requires identifying and prioritizing potential hazards in food chains. We previously developed a web-based decision support system (DSS) to identify specific microbiological hazards (MHs) in infant and toddler foods through a structured five-step process. This study takes the framework further by introducing systematic risk ranking (RR) steps to rank MH risks with seven criteria: process survival, recontamination, growth opportunity, meal preparation, hazard-food association evidence, food consumption habits of infants and toddlers in the EU, and MH severity. Each criterion is given a semi-quantitative or quantitative score or risk value, contributing to the final MH risk calculation via three aggregation methods: semi-quantitative risk scoring, semi-quantitative risk value, and outranking multi-criteria decision analysis (MCDA). To validate the criteria and ranking approaches, we conducted a case study to rank MH risks in infant formula, compared the results of the three risk ranking methods, and additionally evaluated the ranking results against expert opinions to ensure their accuracy. The results showed strong agreement among the three methods, consistently ranking Salmonella non-Typhi and Cronobacter spp. and Shiga-toxin-producing Escherichia coli as the top MH risks in infant formulae, with minor deviations. When MHs were ranked after an initial hazard identification step, all three methods produced nearly identical MH rankings, reinforcing the reliability of the ranking steps and the selected criteria. Notably, the risk value and MCDA methods provided more informative MH rankings compared to the risk scoring method. The risk value and risk scoring methods were implemented into an online tool, called the MIcrobiological hazards risk RAnking decision support system (Mira-DSS), available at https://foodmicrobiologywur.shinyapps.io/MIcrobial_hazards_RAnking/. In conclusion, our framework enables the ranking of MH risks, facilitating intervention comparisons and resource allocations to mitigate MH risks in infant foods, with potential applicability to broader food categories.

A web-based multi-criteria decision support system for benchmarking marketing decisions alternatives

A web-based multi-criteria decision support system for benchmarking marketing decisions alternatives

Web-Based Decision Support System for Best Employee Selection in Government Institutions using Analytical Hierarchy Process (AHP) Method

Web-Based Decision Support System for Best Employee Selection in Government Institutions using Analytical Hierarchy Process (AHP) Method

Web-based spatial decision support system for precision agriculture: A tool for delineating dynamic management unit zones (MUZs)

Precision agriculture (PA) is a farming management concept that aims to provide agronomic, economic, and environmental benefits. One of the fields of research in PA is the delineation of Management Unit Zones (MUZs). MUZs are the sub-division of fields featuring an inter-zonal variation delineated by agronomists for on-field PA operations. To develop MUZs, three factors typically need to be considered: input multi-dimensional data, procedures to process the information, and the optimal number of zones a field should be divided into. PA uses digital technologies to collect and analyze a large amount of data, outline MUZs, monitor crops, and carry out site-specific crop management. Web-based spatial decision support systems (WB-SDSS) can provide users with tools that ease the complex procedures for PA. The objective of this study is twofold: on the one hand, we developed a free and open source (FOSS) WB-SDSS to facilitate the implementation and use of such tools for delineating MUZs and monitoring crops; on the other, a MUZs outline procedure was developed based on Sentinel-2 and Planetscope time series data, and spatio-temporal dynamic clustering model using fuzzy c-means. Our study highlighted that the WB-SDSS might be a helpful solution for harmonizing data collected from different sources, easing the implementation and use of complex geospatial procedures for PA, and delineating MUZs. We tested the system on a particularly representative farm in the Emilia Romagna region (Northern Italy), with 512 hectares of durum wheat crops. Using the WB-SDSS, we quickly delineated homogeneous zones for 27 fields in the study area during the phenological cycle of durum wheat (November 2018-June 2019).

Design of a Web-Based Decision Support Information System for YMM FI Scholarship Recipients Using the SMART Method

Designing a Web-Based YMM FI Scholarship Recipient Decision Support Information System Using the SMART Method can help YMM FI in the decision-making process to determine the right scholarship recipient. YMM FI is a zakat fund management foundation which has several programs, one of which is still running, the Edu Care Program which focuses on funding education from the lower to upper levels. However, the selection of prospective recipients of higher education scholarships is still done manually, which results in inaccuracies in those who receive them. For this reason, there is a need for a Web-Based Decision Support System using the SMART Method which takes into account several attributes that have weighted values and criteria. From the results found, attribute A2 with the name Wa Marlin is the highest ranking of the other attributes

D3S: Decision support system for sectorization

Sectorization problems refer to dividing a large set, area or network into smaller parts concerning one or more objectives. A decision support system (DSS) is a relevant tool for solving these problems, improving optimisation procedures, and finding feasible solutions more efficiently. This paper presents a new web-based Decision Support System for Sectorization (D3S). D3S is designed to solve sectorization problems in various areas, such as school and health districting,planning sales territories and maintenance operations zones, or political districting. Due to its generic design, D3S bridges the gap between sectorization problems and a state-of-the-art decision support tool. The paper aims to present the generic and technical attributes of D3S by providing detailed information regarding the problem-solution approach (based on Evolutionary Algorithms), objectives (most common in sectorization), constraints, structure and performance.

Nurses' use of an advisory decision support system in ambulance services: A qualitative study.

To illuminate from the perspective of nurses in ambulance services the experiences of using a web-based advisory decision support system to assess care needs and refer patients. Inductive and descriptive approaches. Thirteen semi-structured interviews were conducted in the spring of 2020. The data were analysed through the reflexive thematic analysis. The Swedish web-based advisory decision support system (ADSS) was found to strengthen nurses' feelings of security when they assess patients' care needs, promote their competence and professional pride, and help them manage stress. However, the system also generated difficulties for nurses to adjust to the dynamic ambulance team and revealed a discrepancy between their professional roles and responsibilities to refer patients and provide self-care advice. The nurses thought that the support system facilitated their increased participation and helped them understand patients and significant others by offering transparency in assessment and decision making. Thus, the support system provides nurses with an opportunity to strengthen patients' independence through information and education. However, in the care relationship, nurses worked to overcome patients' expectations. Nurses using the ADSS increased their security while performing assessments and referrals and found new opportunities to provide information and promote understanding of their decisions. However, nursing care values can be threatened when new support systems are introduced, especially as ambulance services become increasingly protocol-driven. These findings have implications for nurses' work environments and help them maintain consistency in making medical assessments and in providing equivalent self-care advice when referring patients to the different levels of care. The findings will also impact researchers and policymakers who formulate decision support systems. Consolidated criteria for reporting qualitative research (COREQ). None.

A web-based interactive decision support system for a multi-objective lot-sizing and production scheduling model

In the course of globalization and the corresponding steadily growing market dynamics, companies are faced with an increasing challenge to remain competitive. Therefore, the efficient use of the available resources, while maintaining a high level of service and customer satisfaction, is a key instrument for ensuring success. Within this framework, production scheduling can be seen as one of the most decisive operational activities of a manufacturing company, with the production orders being sequenced in a way that allows the achievement of an efficient allocation of the available resources. Furthermore, the correlated lot-sizing represents a crucial influencing factor in production scheduling. In this article, a novel methodology to solve multi-objective lot-sizing and production scheduling problems is proposed. Essentially, it provides an interactive three-phase framework that supports a procedure for simultaneous decision-making regarding lot-sizing and production scheduling. The main goal is not only to find an appropriate production schedule that best meets the decision-maker’s preferences but also to gain a deeper insight into the relationship among criteria and a better understanding of possible trade-offs between competing objectives. To guide the user through the whole decision-making process, a web-based interactive application was developed. The proposed methodology was applied to a case study regarding an automotive supplier company, revealing itself as a viable and practical technique able to solve real-world multi-objective lot-sizing and production scheduling problems in the manufacturing industry.