Simple Additive Weighting Research Articles

Assessment of Circular Economy Development in the EU Countries Based on SAW Method

The transition to a circular economy is important in achieving sustainability, promoting resource efficiency, and reducing environmental impact. This paper aims to assess the development of a CE in EU countries and highlight the use of environmentally friendly practices for its development. Decision-making methods based on various criteria provide a solid basis for evaluating complex and multidimensional circular economy (CE) initiatives. Simple Additive Weighting (SAW), the widely used MCDM method, facilitates sorting and selection according to the generalised results obtained according to weighted criteria. Due to its simplicity and ease of use, this method is particularly useful for assessing CE development in different countries. The evaluation will be based on a comprehensive overview of the available literature and empirical data, allowing for a comprehensive assessment of the CE’s development initiatives in the European context using the SAW method. The results show that while significant progress has been made in the EU’s transition to a circular economy (CE), disparities among Member States and data limitations hinder a comprehensive assessment. Italy, Germany, France, the Netherlands, and Spain are among the most advanced countries in achieving a circular economy’s objectives. The study proposes a novel MCDM-based framework that effectively evaluates CE performance, identifying key strengths and weaknesses across countries. By focusing on competitiveness and innovation indicators and incorporating environmental factors, the framework offers valuable insights for policymakers and stakeholders.

PSSN: a novel cache placement method based on adapted Shannon entropy and simple additive weighting method in named data networking

PSSN: a novel cache placement method based on adapted Shannon entropy and simple additive weighting method in named data networking

Upscaling and downscaling approaches for early season rice yield prediction using Sentinel-2 and machine learning for precision nitrogen fertilisation

Early season yield prediction could support rice farmers in adopting precision agriculture for nitrogen fertilisation management. Remote sensing and machine learning (ML) can be used to predict and map crop yield during phenological stages relevant to nitrogen application, like tillering in rice, at both within-field and field scales. This study evaluated the transferability of ML models in early season yield prediction through upscaling and downscaling approaches. The effects of two prediction times (tillering and ripening stages) and training/testing set sizes on ML models performance were evaluated over five rice growing seasons (from 2018 to 2022) in northern Italy, using whole-field-average yields and yield maps. Vegetation indices from Sentinel-2 imagery using the Google Earth Engine platform fed five ML algorithms (Cubist-CUB, Gaussian Process Regression-GPR, Neural Network-NNET, Random Forest-RF, and Support Vector Machines-SVM). ML algorithms were trained with yield maps and tested with whole-field-average yields to obtain a downscaling approach, while the opposite was done to obtain an upscaling approach. The downscaling approach showed higher accuracy than upscaling approach. Ripening stage predictions were more accurate than tillering stages, although the downscaling approach showed small differences between tillering and ripening stages. The highest tillering stage accuracy was achieved by SVM for both downscaling and upscaling approaches with 20 % and 27.8 % of Normalized Root Mean Square Error (NRMSE), and 0.99 and 0.99 of Simple Additive Weighting (SAW) score, respectively. Set size and data distribution effected ML models accuracy, with the highest performance achieved by RF and GPR with 0.80 and 1.00 of SAW score for the downscaling and upscaling approaches, respectively. This study demonstrated how ML models and downscaling approach could support rice farmers to calculate the nitrogen dose using the predicted yield at the tillering stage, enabling them to apply a site-specific nitrogen fertilisation based on the within-field yield prediction variability.

Decision Support System Design To Determine The Feasibility of Students Staying In The Dormitory Using The Simple Additive Weighting Method

The research aims to analyze the feasibility of students staying in the dormitory using the Simple Additive Weighting (SAW) method. The process of admitting residents is currently done manually; therefore, a system is needed to facilitate dormitory management, supported by the SAW method as a systematic approach to identify and evaluate factors influencing the feasibility of staying in the dormitory. In the SAW method, criteria weights are assigned to each factor based on their importance according to the feasibility level determined by the dormitory management. Subsequently, calculations are performed using the SAW formula to obtain the final feasibility score for each student. Based on the test results, the developed system can facilitate and expedite the dormitory management in determining the selection process for students who wish to stay in the dormitory, as well as improve decision-making accuracy.

Utilization Method Simple Additive Weighting in Decision Support Systems to Determine Outstanding Students

Utilization Method Simple Additive Weighting in Decision Support Systems to Determine Outstanding Students

Metode Simple Additive Weighting (SAW) pada Pemilihan Jenis Lampu Penerang Jalan Berbasis Photovoltaic

The simple additive weighting method is a decision support system method for various decision selection problems. Many research topics use the SAW method as a reference method in a decision support system. The street lighting control system is very useful for residents of the village of Karanganyar, Paiton, Probolinggo. This lighting is the main spotlight for residents' activities at the village office. Such as August competitions, routine monthly recitations, competitions to commemorate Isra' Mi'raj and the Prophet's birthday. There are many types of lamps in stores. The criteria for lamps are that they have high light illumination, long-lasting light, large bulb size, so that they can help village residents carry out activities at night. This lamp also uses photovoltaic as an additional source of electrical energy so it can save electricity costs to PLN. The solar panel measures 550 x 360 x 25 mm, 20 volts and has a peak power of 20 watts

Practical drought risk assessment and management framework: A step toward sustainable modernization in agricultural water management

A proposed framework to assess and manage risks associated with Agricultural Water Off-farm Conveyance and Distribution Systems (AWOCDS), quantify potential failure due to drought-induced scenarios, and provide short to long-term recovery plans to mitigate drought impacts. It makes an intellectual contribution by creating a new proactive risk assessment focusing specifically on AWOCDS as a crucial part of agricultural water management. The risk assessment comprises two components − risk probability and consequence. The former is calculated by analyzing droughts via the streamflow drought index using the DrinC calculator. The latter is determined through AWOCDS’ performance evaluation using hydraulic simulation via HEC-RAS. Additionally, water distribution is assessed spatiotemporally using adequacy and equity indicators, and an integrated consequence is developed by applying the simple additive weighting method. AWOCDS’ rehabilitation and modernization projects worldwide include three practical practices in its risk management component. These practices involve modifying standard operating procedures (SOPs) by updating maintenance, upgrading manual-based operations, and developing a centralized Model Predictive Controller (MPC) for AWOCDS automatic operation. The proposed framework underwent testing in an arid region. Based on the risk assessment results, the AWOCDS operating system failure rate ranges from 70% to 96% during extreme-severe drought scenarios and 53% to 65% during moderate-mild drought scenarios. Risk management analysis shows that a short-term recovery plan reduces the drought risk by 4% monthly and 3% yearly. However, the risk of failure ranges from 50 to 94% in mild to extreme drought scenarios. Upgrading SOPs decreases impact by 4–11% in extreme, 4–7% in moderate-severe and 7–9% in mild-moderate drought. Automating the operating system with MPC reduces impact by 40–43% and 30–56% in mild-moderate and severe-extreme drought scenarios. This proactive-based strategy can help water managers plan for rehabilitation and improve surface water distribution reliability.

Optimization of U-23 futsal player selection through a simple additive weighting approach

Futsal playing skills are the main support in successfully achieving the goals of the game. There are several underlying techniques that every player needs to master, including passing, dribbling, controlling, chipping and shooting. This study aims to optimize the selection process for the best futsal players using the Simple Additive Weighting (SAW) method. The SAW method was chosen because of its ability to combine various selection criteria into one composite score, which makes decision-making easier. This research involves analyzing the needs of a futsal group to determine the relevant criteria and weights in selecting a group of players, such as passing, control, dribbling, chipping, and shooting. These indicators provide a more comprehensive picture of the capabilities and potential of the player group. Potential futsal group data are collected and processed using the SAW method with a weighted sum of the performance ratings for each alternative from all attributes. The SAW method requires a matrix normalization process on a scale that can be compared with all existing alternative ratings to produce objective and transparent ratings for the player groups. Based on the results of calculations using the SAW method, the assessment results for the prospective group of futsal players were obtained based on the specified criteria and weights. The highest score was achieved by Banyumas 1 with a score of 0.85. The research results show that the application of the SAW method in the selection process for futsal players increases the efficiency and accuracy of selecting new players. By using this approach, Porprov can more easily identify the best candidates to meet their needs.

Recommendation for Prospective Permanent Employees using the Simple Additive Weighting Method

The rapid development of technological progress has made the use of personal computer technology increase significantly, where this use has made computers into branches that can still be developed, one of which is creating a decision-making system. Decision Support System is a computer-based system that is intended to assist decision making by utilizing certain data and models to solve various semi-structured problems. The application of Decision Support Systems can be found in various fields, one of which is a decision support system for prospective employees. This study aims to design a system that can provide the best decision in determining permanent employees at J&T Express Kotanopan. The method used in this study is the SAW (Simple Additive Weighting) method, with a website-based decision support system that can be used without time and place constraints, it can help J&T Express in selecting permanent employees. The results of testing this method have an accuracy level of more than 90% based on the data tested. Based on the results of the highest value obtained using the SAW method, this study was successful in determining permanent employees at J&T Express Kotanopan

Decision Support System for Determining Recipients of Subsidized Foodstuffs for Poor Families Using the Simple Addictive Weighting Method

Technology is increasingly becoming a necessity that must be met, both in the world of education and in the world of business and social, especially information technology is used not only as a support but also as a primary need that can be used to provide information quickly. In accordance with what has been determined to obtain Subsidized Food, criteria are needed to determine who will be selected to receive subsidized food. The distribution of subsidized food is distributed to underprivileged or poor citizens. To assist in determining who is eligible to receive subsidized food, a decision support system is needed. One method that can be used for Decision Support Systems is by using Simple Additive Weighting (SAW). In this study, a case will be raised, namely finding the best alternative based on predetermined criteria by using the SAW method to calculate the method in the case. This method was chosen because it is able to select the best alternative from a number of alternatives, in this case the intended alternative is those who are entitled to receive subsidized food based on the specified criteria. The study was conducted by finding the weight value for each attribute, then a ranking process was carried out which would determine the optimal alternative, namely the poor. After the study was conducted, the results obtained were that there were 4 alternatives receiving Subsidized Food and the one with the highest value was alternative 5 with the name Yuhel Fentri with a value of 0.875.

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.

Penentuan mahasiswa berprestasi menggunakan algoritma FP-Growth dan SAW

This research discusses the importance of utilizing technology in inventory management and student achievement determination. The transformation from manual systems to computerized systems has proven to increase efficiency and accuracy. In determining outstanding students, the criteria used often focus solely on academic aspects, neglecting other skills such as leadership and creativity. This study proposes the use of the FP-Growth and Simple Additive Weighting (SAW) algorithms to address this issue. FP-Growth is used to identify high-frequency patterns in student achievement data, while SAW assigns weights to each criterion variable for more accurate decision-making. The criteria for assessment include GPA, student achievements, study duration, and activity participation. The implementation is expected to provide a more effective solution in determining outstanding students and managing inventory. The FP-Growth method helps identify significant patterns in transaction data, while SAW assists in ranking alternatives based on specified criteria. This research demonstrates that the combination of these two algorithms can improve accuracy and efficiency in inventory management and student achievement determination, providing a competitive advantage for institutions. Based on the research results, the ranking of outstanding students is led by student C, followed by student B, with respective scores of 0.8875 and 0.825.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LAPTOP DENGAN MENERAPKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)

This research aims to develop a Decision Support System (SPK) using the Simple Additive Weighting (SAW) method in selecting the best laptop based on various criteria. The criteria used in this research include price, RAM, internal memory, screen size, and processor. The SAW method was chosen because of its ability to handle multi-criteria decision making by giving weights to each criterion and calculating the final score of each alternative through data normalization. The results showed that the five best laptop alternatives with the highest scores were HP SPECTRE X360 with a score of 75.00, Xiaomi RedmiBook 15 with a score of 72.50, ASUS Zenbook S 13 OLED with a score of 67.50, Lenovo Thinkbook 14 with a score of 67.00, and Huawei MateBook D14 with a score of 67.00. From these results, HP SPECTRE X360 was declared the best choice. This study concludes that the SAW method is effective in helping decision making involving many criteria and alternatives. The weights of criteria such as price and processor show a significant influence on the final result. For further research, it is recommended to evaluate more deeply the determination of weights and normalization formulas to improve decision accuracy. Thus, this method can be adapted to a wider context and relevant in complex decision making

Examining thedrivers of forest cover change and deforestation susceptibility in Northeast India using multicriteria decision-makingmodels.

The increasing rates of forest cover change and heightened vulnerability to deforestation present significant environmental challenges in Northeast India. This study investigates the dynamics of forest cover changeand susceptibility to deforestation in this region from 2001 to 2021, utilizing data from the Hansen Global Forest Change (HGFC) productonthe Google Earth Engine (GEE) platform. A suite of multicriteria decision-making (MCDM) models-including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), and Weighted Aggregates Sum Product Assessment (WASPAS)-was employed to assess changes in forest cover and deforestation susceptibility across varied zones. Multicollinearity tests confirmed the relevance of the factors influencing deforestation. Statistical validations, such as the Wilcoxon Signed Ranks Test, underscored the models' robustness, revealing statistically significant outcomes. Additionally, Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) analysis demonstrated the superior fit of the VIKOR model (AUC = 0.938) compared to SAW (AUC = 0.901), EDAS (AUC = 0.895), and WASPAS (AUC = 0.864) in predicting current deforestation susceptibility. Validation affirmed the reliability of all MCDM methods, with VIKOR displaying high sensitivity (True Positive Rate, TPR = 0.878) and optimal AUC (0.938). Correlation analyses among the models identified significant inter-relationships, notably a positive correlation between EDAS and SAW, and a negative correlation between VIKOR and SAW. The regions of Assam, Nagaland, Mizoram, and Arunachal Pradesh were identified as experiencing significant forest cover loss, indicating a pronounced susceptibility to future deforestation. These findings underscore the need for immediate intervention to address this critical environmental issue.

Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation.

Parkinson disease (PD) is reported to be among the most prevalent neurodegenerative diseases globally, presenting ongoing challenges and increasing burden on health care systems. In an effort to support patients with PD, their carers, and the wider health care sector to manage this incurable condition, the focus has begun to shift away from traditional treatments. One of the most contemporary treatments includes prescribing assistive technologies (ATs), which are viewed as a way to promote independent living and deliver remote care. However, the uptake of these ATs is varied, with some users not ready or willing to accept all forms of AT and others only willing to adopt low-technology solutions. Consequently, to manage both the demands on resources and the efficiency with which ATs are deployed, new approaches are needed to automatically assess or predict a user's likelihood to accept and adopt a particular AT before it is prescribed. Classification algorithms can be used to automatically consider the range of factors impacting AT adoption likelihood, thereby potentially supporting more effective AT allocation. From a computational perspective, different classification algorithms and selection criteria offer various opportunities and challenges to address this need. This paper presents a novel hybrid multicriteria decision-making approach to support classifier selection in technology adoption processes involving patients with PD. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) was implemented to calculate the relative priorities of criteria and subcriteria considering experts' knowledge and uncertainty. Second, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF-DEMATEL) was applied to evaluate the cause-effect relationships among criteria/subcriteria. Finally, the combined compromise solution (CoCoSo) was used to rank the candidate classifiers based on their capability to model the technology adoption. We conducted a study involving a mobile smartphone solution to validate the proposed methodology. Structure (F5) was identified as the factor with the highest relative priority (overall weight=0.214), while adaptability (F4) (D-R=1.234) was found to be the most influencing aspect when selecting classifiers for technology adoption in patients with PD. In this case, the most appropriate algorithm for supporting technology adoption in patients with PD was the A3 - J48 decision tree (M3=2.5592). The results obtained by comparing the CoCoSo method in the proposed approach with 2 alternative methods (simple additive weighting and technique for order of preference by similarity to ideal solution) support the accuracy and applicability of the proposed methodology. It was observed that the final scores of the algorithms in each method were highly correlated (Pearson correlation coefficient >0.8). The IF-AHP-IF-DEMATEL-CoCoSo approach helped to identify classification algorithms that do not just discriminate between good and bad adopters of assistive technologies within the Parkinson population but also consider technology-specific features like design, quality, and compatibility that make these classifiers easily implementable by clinicians in the health care system.

Application of the Simple Additive Weighting (SAW) Method in the Decision Support System for the Selection of Study Programs at the University of Papua

To help prospective students choose a study program that suits their abilities and interests, it is necessary to design a decision support system. This system aims to facilitate the selection process of study programs for prospective students. This research aims to develop a decision support system that can help prospective students in choosing a study program at the Faculty of Engineering, University of Papua in an objective and structured manner. This study applies the Simple Additive Weighting method to facilitate the decision-making process by considering a number of relevant criteria. The evaluation is based on the following criteria: tuition fees, accreditation status, number of teaching staff and staff, and job prospects. The findings of the study revealed that the Informatics Engineering and Civil Engineering Study Programs, both at the S1 level, obtained the highest identical preference value, namely 1, outperforming other study programs. However, the best alternative is the S1 Informatics Engineering Study Program.

Simplifying Cosplay Costume Selection with a Web-Based Recommendation System

Cosplay is an activity where individuals imitate the dressing style of a character, typically from fictional works such as games, anime, VTubers, and others. Before engaging in cosplay activities, cosplayers need to choose the desired costume according to their individual needs. Therefore, cosplayers often experience confusion in selecting a cosplay costume due to the many costume options and the desired costume criteria. One way to assist in making decisions is through a recommendation system. A recommendation system can help users make decisions based on their preferences. In this study, the design and development of a webbased recommendation system for selecting cosplay costumes using the Simple Additive Weighting method were conducted. This system was then evaluated by 52 respondents. Based on a survey conducted using the EUCS method to measure user satisfaction levels, an average score of 80.65% was obtained.

Optimal Configuration of Modular Strongrooms Using Multi-Attribute Decision Making

In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR type MODULPRIM was developed, integrating the procedures for generating product variants, choosing the optimal configuration, and designing detailed products and technological processes. The developed model’s importance lies in its ability to automatically select the optimal configuration from a set of possible configurations on a multidisciplinary basis. The problem of choosing was solved by integrating the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods from the group of Multi-Attribute Decision Making (MADM). Validation of the proposed model was performed on eight examples of Modular Strongrooms type MODULPRIM 5 and showed great opportunities to improve efficiency and effectiveness in the process of innovative product development, as well as to obtain a product configuration with significantly improved quality. The proposed model has a high degree of flexibility and universality; thus, it can be further upgraded and integrated into a company’s business system.

A reasonable approach to determine structural dimension of FDM fabricated orthopedic orthosis using finite element simulation and simple additive weighting method

A reasonable approach to determine structural dimension of FDM fabricated orthopedic orthosis using finite element simulation and simple additive weighting method

Surface water potential zones delineation and spatiotemporal variation characteristics of water pollution and the cause of pollution formation in Brahmani River Basin, Odisha

Waste water reuse is an effective method for reducing the quantity of wastewater that enters the environment. As a result, the appropriateness was assessed in accordance with its composition and the global criteria for drinking water quality. This study aims to evaluate the quality of surface water of Brahmani River, Odisha, by adapting multivariate statistical approaches, namely Cluster Analysis (CA) and multi-criteria decision-making (MCDM) methods such as Simple Additive Weighting (SAW). Again, Geographical Information System (GIS) is employed to assess the drinking water's quality in relation to its application. Around 15 physicochemical parameters, gathered from seven distinct sites, following a period of 2022 till 2024. The results showed high values of EC, SO42−, NO3−, PO43−, F− and Ca2+, in three stations, while other studied parameters are within the permissible limits defined by WHO standards. The CA three distinct classifications of sites namely, low, medium, and high, based on how comparable the various physicochemical traits and pollutant levels were throughout the sampling locations. Sites H-(4–6) were included in cluster 1, site H-(3) and (7) classified under Cluster 2 and finally, H-(1–2) indicated as Cluster 3. Thus, as stated by CA, 42.86 % of tested water samples were fall into the group of good quality and about 57.14 % of examined locations resides in the poor category of water. The findings indicate which characteristics, as determined by the CA technique, were accountable for the alteration in the water quality and raise the potential of runoff from cities, farms, and industries. Subsequently, MCDM techniques has been implemented to facilitate rapid comprehension of surface water behavior and address problems with water resource management. The obtained SAW index ranges from 0.5 to 0.94. Here, H-(1), (2), and (7) grouped as highly polluted zone, and they seemed to be connected to runoff from farms and untreated industrial and municipal trash as well as local pollution sources. From this innovative study, it is found that even though the water is fit for drinking at 3 places, it is medium to highly suitable for human consumption. Therefore, there needs to be treated in some way before being used in addition to being protected against contamination. Most often, the findings indicate that appropriate management actions are important to restore the water quality of this catchment in order to support a robust and promising aquatic ecosystem. Additionally, the significance of this restoration for objective ecological policy and decision-making processes is underscored.