Rank Order Centroid Research Articles

Applying MCDM to evaluate benchmark scores in the logistics sector for the period 2021–2023: Application to universities in Vietnam

Choosing a university is a crucial decision for each field of study, as it significantly influences the quality of graduates. An important factor in this decision is the university’s annual benchmark scores. The benchmark score represents the minimum score required for admission. This study evaluates the benchmark scores in the logistics sector for several prominent universities in Vietnam during the period 2021–2023. The research process utilized data on the benchmark scores for the years 2021, 2022, and 2023. The weights of these benchmark scores were calculated using the Rank Order Centroid (ROC) method, and the Probability method was employed to compare the benchmark scores of the universities. The analysis identified C3 as the criterion with the highest importance, while U3 emerged as the top-ranked alternative. The two-stage comprehensive sensitivity analysis revealed that universities consistently ranked high or low regardless of the method used to calculate benchmark score weights or the method employed for ranking. Additionally, the smallest weight change that affected the overall Probability ranking was 4.61%. This study provides significant guidance for students in selecting a university for logistics studies and serves as a foundational reference for universities to assess their capabilities in logistics education, thereby fostering healthy competition among institutions.

PENERAPAN METODE WASPAS DAN ROC DALAM PEMILIHAN BANK TERBAIK UNTUK PELAYANAN MOBILE BANKING

Technological developments encourage increased use of banking services via mobile devices. Choosing the optimal bank for mobile banking services is an important challenge in meeting customer needs. This research uses a Decision Support System with the application of the Weighted Aggregated Sum Product Assessment (WASPAS) and Rank Order Centroid (ROC) methods. The WASPAS method helps find positive and negative ideal solutions in solving problems. The ROC method was chosen to reduce the level of subjectivity and uncertainty in determining weights. The weights in ROC are determined based on priority criteria. In this research, 5 alternatives are used, namely BCA Mobile, Livin' by Mandiri, BSI Mobile, BNI Mobile Banking, BRImo BRI, and apply criteria such as security, many enthusiasts, user friendly, rating, and cost. This research aims to provide a comprehensive picture of the quality of mobile banking services provided by various banks so as to help customers choose mobile banking according to the criteria they need. The research results show that BCA Mobile owned by BCA bank is the best alternative with the highest value of 0.940, followed by BRImo with a value of 0.613, BNI Mobile with a value of 0.612, Livin' by Mandiri 0.611, and the lowest value of 0.323 for BSI Mobile. Thus, BCA Mobile is declared the best choice for mobile banking services.

Evaluation of Determining the Best Product Promotion Media Decisions for MSMEs with ROC Ranking Technique and SAW Ranking Method

Micro, Small, and Medium Enterprises (MSMEs) face challenges in determining effective promotional media to increase sales of their products. This research aims to evaluate and determine the best promotional media for MSMEs using the ROC (Rank Order Centroid) ranking technique and the SAW (Simple Additive Weighting) method. The criteria used include Advertising Costs, Target Market, Promotion Time, and Brand Image. Based on the calculation of criteria weights with the ROC technique and evaluation of alternatives with the SAW method, Social Media was found to be the best promotional media, followed by Search Engines and Product Collaboration. Social Media has advantages in low cost, wide target market reach, and promotional flexibility and effectiveness. Search Engines and Product Collaboration also showed good results in reaching the target market and promotional flexibility. In contrast, Print Media ranked the lowest due to limited reach and high costs. This research provides guidance for MSMEs in choosing the right promotional media and optimizing resources for maximum promotional results.

Decision Support System for Determining the Best School Extracurricular Activities by Combining the ROC and MAUT Methods

The various extracurricular activities at school make students confused and difficult to choose which extracurricular activities are more suitable for participation. However, sometimes there are also students choosing extracurricular activities based on many of their friends. Therefore, determining the best school extracurricular activities is the best solution for students as a reference to find which is the best extracurricular activity. The criteria used in this study in choosing the best extracurricular activities are Regional Event Activities, Allocation, Creativity and Talent Channeling. By utilizing SPK, decision makers can make more systematic decisions, based on a deeper understanding of the various alternatives available and relevant criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. In the context of extracurricular school selection, combining the ROC (Rank Order Centroid) and MAUT (Multi-Attribute Utility Theory) methods in a Decision Support System is an interesting approach. The ROC method is used to cluster and rank schools based on certain criteria, while MAUT helps in the calculation of appropriate weights for these criteria. By integrating these two methods, the SPK can provide a more structured guideline in the selection of extracurricular activities that suit students' interests and needs. The research results obtained show that the Futsal alternative is the first recommendation as the best extracurricular with a final value of 0.655086.

Implementasi Kombinasi Metode ROC dan MAUT Dalam Menentukan Aplikasi Chatting Terbaik

The rapid development of technology makes it easier for humans to communicate with each other more easily by using the best chatting applications. The purpose of this research is to help users who have just used a smartphone to choose the chatting application that suits their needs. The method used in this study is a Decision Support System with Rank Order Centroid (ROC) as the weight value and Multi Attribute Utility Theory (MAUT) as a solution. The alternatives used are Whatsapp, Messager, Discord, Telegram, Line, WeChatting and the criteria used are Security, Storage Media, Network Usage, application features, Display / Interface. The results obtained indicate that the Whatsapp alternative is the first recommendation as the best chatting application with a final value of 0.929456. The Telegram alternative became the second recommendation with a final value of 0.847485 and Line became the third recommendation with a final value of 0,624656.

Medicinal Plants Recommendation System using ROC and MOORA

Kalimantan has extraordinary biodiversity, including medicinal plants. Medicinal plants are a type of plant that certain parts, such as roots, leaves, bark, stems, and the results of their excretions. However, people sometimes need help choosing plants that suit their needs because of the many types of medicinal plants and the need for knowledge regarding their use. Decision support systems (DSS) combine computer capabilities with data processing or manipulation that utilizes unstructured models or solution rules. Furthermore, the method of documenting knowledge of traditional medicine is through the media of information systems. This system helps select medicinal plants according to user needs. This research developed a DSS using Rank Order Centroid (ROC) and Multi-Objective Optimization by Ratio Analysis (MOORA) methods to select medicinal plants for fungal and skin infections, including Furuncles, Tinea corporis, Tinea versicolor, and Acne. ROC method for determining criteria weight values. This research has four criteria: plant part, processing method, use method, and habitus. Determining recommendations for alternative ranking results using the MOORA method. This study aims to help the public get recommendations for medicinal plants in human skin disease treatment. This study aims to increase the preservation of biodiversity, particularly sustainable medicinal plants in the tropical rainforest of East Kalimantan.

Combination of Multi-Objective Optimization on The Basis of Ratio Analysis and ROC in The Selection of Extracurricular Activities

The selection of extracurricular activities for students often involves several challenges and problems. Some problems in the selection of extracurricular activities include limited time, interests and talents, limited facilities and infrastructure, and awareness of choices. Problems in the selection of extracurricular activities include limited time, interests and talents, limited facilities and infrastructure, and awareness of choices. The purpose of this study is to provide recommendations for a decision support system model for students in the selection of extracurricular activities by applying the ROC method as a method of weighting criteria and the MOORA method as an alternative ranking tool for extracurricular activities that become recommendations for students. The combination of MOORA and Rank Order Centroid (ROC) methods is an approach that can be used in complex multi-criteria decision analysis. This method combines the strengths of both methods to provide more comprehensive and effective solutions in decision-making. The results of the study on the selection of extracurricular activities using a combination of MOORA and ROC methods, recommendations for extracurricular activities for Futsal extracurricular activities with a value of 0.444 as recommendations based on the final calculation results with the MOORA method got rank 1, for rank 2 recommended extracurricular activities Basketball with a final value of 0.437, and rank 3 recommended extracurricular activities Karate with a final value of 0.426.

Scenario mapping for critical infrastructure failure under typhoon rainfall: A dependency and causality approach

The critical infrastructure system exhibits a high degree of instability because of the frequent occurrence of extreme natural disasters. This study proposes a method for exploring the cascading failures of critical infrastructure systems under such impacts, based on dependency relationships for importance analysis and probability assessment. With this method, a cascading failure scenario graph of critical infrastructure is established and empirical research is conducted using typhoon rainfall events as a case study. The main contributions of this study are summarized as follows: it proposes a method for the causal identification of the interrelationships among critical infrastructures; it sorts and evaluates the importance and cascading failure probability of critical infrastructure by using the Interpretative Structural Modeling (ISM) and Rank-order Centroid method (ROC); and it generates scenario graphs of critical infrastructure cascading failures to visualize event states, environmental characteristics, and evolutionary paths. This study provides a new method and tool for disaster risk management of complex systems involved in critical infrastructure.

Investigation of rank order centroid method for optimal generation control.

Multi-criteria decision-making (MCDM) presents a significant challenge in decision-making processes, aiming to ascertain optimal choice by considering multiple criteria. This paper proposes rank order centroid (ROC) method, MCDM technique, to determine weights for sub-objective functions, specifically, addressing issue of automatic generation control (AGC) within two area interconnected power system (TAIPS). The sub-objective functions include integral time absolute errors (ITAE) for frequency deviations and control errors in both areas, along with ITAE of fluctuation in tie-line power. These are integrated into an overall objective function, with ROC method systematically assigning weights to each sub-objective. Subsequently, a PID controller is designed based on this objective function. To further optimize objective function, Jaya optimization algorithm (JOA) is implemented, alongside other optimization algorithms such as teacher-learner based optimization algorithm (TLBOA), Luus-Jaakola algorithm (LJA), Nelder-Mead simplex algorithm (NMSA), elephant herding optimization algorithm (EHOA), and differential evolution algorithm (DEA). Six distinct case analyses are conducted to evaluate controller's performance under various load conditions, plotting data to illustrate responses to frequency and tie-line exchange fluctuations. Additionally, statistical analysis is performed to provide further insights into efficacy of JOA-based PID controller. Furthermore, to prove the efficacy of JOA-based proposed controller through non-parametric test, Friedman rank test is utilized.

Ranking voting systems and surrogate weights: Explicit formulas for centroid weights

One of the most important issues in the field of ranking voting systems is the choice of the weighting vector. This issue has been addressed in the literature from different approaches, and one of them has been to obtain the weighting vector as a solution to a linear programming problem. In this paper we analyze some models proposed in the literature and show that one of their main shortcomings is that they cannot guarantee the uniqueness of the solution, so the winner or the final ranking of the candidates may depend on the chosen weighting vector. An alternative to these models is the use of surrogate weights, among which rank order centroid (ROC) weights stand out as the centroid of a specific simplex. Following this idea, in this paper we show the explicit expression for the weights that form the centroid of diverse simplices utilized in ranking voting systems, and we also see that certain surrogate weights frequently employed in literature can be derived as extreme cases where the simplices collapse into a single vector. Moreover, we argue that averaging two weighting vectors can be a valid approach in some cases and, in this way, we can get weighting vectors that closely resemble those used in some sports competitions.

Analysis comparison model of ROC-TOPSIS, ROC-WP, and ROC-Electre methods for supporting the funding decision to micro-enterprises Indonesia

Micro-business is an essential business unit that supports the economies of countries in the world, including Indonesia. Unfortunately, micro-entrepreneurs often find difficulties to obtain financial assistance from government to develop their businesses. In Indonesia, the smallest number of micro industries can be found in West Papua Province, where one of the underdeveloped areas in the province is the Sorong City. Therefore, a study was conducted to determine the application of decision support methods in selecting micro-enterprises in Sorong that are eligible for business funding. The decision support method chosen is the collaboration between the Rank-Order Centroid (ROC) method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Weight Product (WP), and Elimination Et Choix Traduisant la Realite (Electre). With the analysis conducted on 10 samples of micro-enterprises in Sorong City, it was found that the micro-enterprises that were most eligible to receive assistance is Raya Helm based on ROC-TOPSIS, ROC-WP, and ROC-Electre. Then, sensitivity analysis results the ROC-Electre as the best method with the highest sensitivity percentage. Therefore, the implementation of these methods for supporting the funding decision to micro-enterprises in Sorong was successfully carried out with the output being the micro-enterprise rating results.

Rank Order Centroid as a Method to Weight Dimensional Variables for Developing a Composite Index on Policing Activities in Mining and Quarrying Areas

Objective: Dimensional variable weighting is required to calculate the composite index of policing activities in mining and quarrying activities. The purpose of weighting is to determine the Ranking and priority of each indicator and dimension, considering that each indicator does not necessarily have the same value in the actual situation. The weighting method used in this study uses a subjective method using expert opinion. Method: The Ranking carried out by experts is then calculated using rank order centroids. The results of this weighting show that expert opinion can be used to aggregate weights with specific values that can be used as weights for each dimension. Conclusion: The results of this study show that weighting by Ranking by experts through subjective methods can be used to compile rankings or weights of variables for index preparation.

Applying IROC Method in Patent Submission Evaluation in Indonesia: A Comparison with MAGIQ and AHP

This study applies the Improved Rank Order Centroid (IROC) to the Indonesian patent submission process within a Multi-Criteria Decision Making (MCDM) framework. The study evaluates four primary elements in patent assessment: "Patent Description," "Illustration," "Inventor's Ownership Statement," and "Rights Assignment Declaration." Preliminary findings indicate the importance of "Patent Description," followed by the other elements in descending order of significance. The evaluation also encompasses three applicant alternatives, with the Second Applicant emerging as the most favorable. The study further contrasts IROC outcomes with MAGIQ and AHP methodologies. While rank-based techniques like ROC and IROC generally produce similar weight distributions, the AHP method, which employs pairwise comparisons, often displays variations. The research underscores the potential of IROC in determining criterion weights, its comparison within the MAGIQ framework, and its validation through AHP. These insights aim to deepen our understanding of decision-making processes and analysis. The conclusion from comparing IROC results with MAGIQ and AHP indicates that the applicant rankings remain consistent. Therefore, further research is needed to understand the differences between evaluation methods and their impacts and explore the influence of cultural or regional factors in the patent submission process

Decision Support System for Selection of Internet Services Providers using the ROC and WASPAS Approach

Along with the growth of the internet service provider industry, selecting an Internet Service Provider (ISP) has become an important decision to ensure optimal internet access. However, with so many ISP options available, consumers often face difficulties in choosing the service that best suits their needs. The aim of this research is to produce a decision support system that can help users choose the ISP that best suits their needs and preferences using the ROC (Rank Order Centroid) approach as a weighting technique and the WASPAS (Weighted Aggregated Sum Product Assessment) approach to determine the best alternative. The ROC approach is used to obtain criteria weights based on the ranking order of the importance of the criteria. On the other hand, the WASPAS method is used to determine the best alternative through weighted addition and multiplication, producing a final value that reflects the extent to which each alternative meets the specified criteria. The outcomes of the case study reveal a ranking of alternatives from highest to lowest scores, as follows: First Media (A2) achieving 0.8629, Indihome (A3) at 0.8416, MyRepublic (A5) with 0.7954, Biznet (A1) scoring 0.7844, and Oxygen (A4) at 0.7469. The usability testing yields an average score of 89%, suggesting that the system is apt for utilization, as it aligns with the functionalities users are seeking.

Penerapan Metode EDAS dan ROC Dalam Rekomendasi Objek Wisata Pantai Terbaik

Indonesia's natural diversity, cultural heritage and history have given rise to attractive tourism destinations, including Central Java Province. Central Java offers a diversity of beaches, attracting millions of tourists every year. However, many tourists have difficulty choosing a beach tourist destination that suits their wishes. Decision Support Systems (DSS) are a solution with various methods, one of which is the Evaluation Method based on Distance from Average Solution (EDAS) which is currently used together with Rank Order Centroid (ROC) weighting. This method has been proven to be effective in complex decision situations. In this context, using 13 Alternative Beaches was taken by taking into account the highest number of visitors in each Regency/City in Central Java Province and applying criteria such as cleanliness, facilities, popularity, rating and ticket prices used for evaluation. This research aims to examine the relationship and integration of the ROC and EDAS weighting methods in recommendations for the best beach tourist attractions in Central Java. It is hoped that this study will be able to provide a better interpretation and obtain a ranking ranking of alternative beach tourist attractions in Central Java, thereby contributing to tourists making more accurate decisions according to the criteria in the context of selecting beach tourist locations. The results of the research show that Jatimalang Beach is the best alternative with the highest score of 1,000. Thus, Jatimalang Beach is declared as the best choice for the best tourist attraction.

Sistem Pendukung Keputusan Pemilihan Tenaga Hononer Terbaik Menggunakan Metode Additive Ratio Assessment (ARAS) Dengan Pembobotan Rank Order Centroid (ROC)

Honorary workers are employees who have not been appointed as permanent employees who receive an honorarium every month from the agency or company where they work. SMK N 1 Balige is one of the schools that still needs honorary teachers. Each school certainly makes policies to create a teaching and learning process between teachers and students that is more conducive and optimal. One of the policies of SMK N 1 Balige is to select the best honorary teachers. This policy can encourage honorary teachers to work more professionally. However, this assessment is still carried out manually so that it affects the results of decisions that are not objective. Then a decision support system is needed by applying two methods, namely the Additive Ratio Assessment (ARAS) and Rank Order Centroid (ROC) methods to produce accurate decisions and get the best alternative from the input matrix. The ARAS method is used as the ranking for the final results and the ROC method is used for weighting. The application of a decision support system using the ROC method is able to give weight to each criterion that will be used in the ARAS method calculation process. By applying the ARAS method, the best alternative was produced in the name of Donna Napitupulu with alternative code A3 with a result of 0.976 followed by alternative A1 in the name of Anita Teresia Sianipar with a result of 0.929.

Efficient Human Resource Allocation in Projects Using Centralized Data Envelopment Analysis

Human resource allocation is a critical component of project management, especially for projects that rely on the knowledge and expertise of skilled personnel. Data Envelopment Analysis (DEA) is a suitable method for this allocation since teams working for different tasks of a project can be considered as Decision Making Units (DMUs) that produce valuable outputs using different types and levels of personnel (inputs). We use Centralized DEA models for efficient allocation of human resources of the overall project among several teams. Using the software teams of a project undertaken in a large technological defense company as DMUs, we define appropriate outputs that measure effort, importance of work, and schedule performance. Factors relevant to the importance of work are aggregated using Rank Order Centroid weights according to expert evaluations. We differentiate between the permanent personnel of the company by their expertise level, and also subcontractors as different inputs. We define staffing policies with varying flexibilities that can be applied in different time periods, and suggest the transfer or removal of some personnel. Our results demonstrate that a centralized view on human resource allocation can bring noteworthy savings, especially in the long term when there is higher flexibility in staffing decisions.

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance: A Case Study in Lung Cancer Patient Preferences.

Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. A total of 307 patients with non-small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen's weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Most respondents (>65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P < 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P < 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53-0.55). Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability.Most respondents found the DCE and SW tasks very easy or easy to understand and answer.A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.

Relaxed Rank Order Centroid Weighting MCDM Method With Improved Grey Relational Analysis for Subcontractor Selection: Photothermal Power Station Construction

This article addresses the problem of subcontractor selection in an uncertain decision-making environment by proposing a new hybrid method and improving a classical multicriteria decision-making (MCDM) method. First, the proposed hybrid method combines subjective and objective weighting methods to estimate the weights of criteria that are represented as grey numbers. The subjective weighting method is the PA weighting method. The objective weighting method is the rank order centroid with slacks (ROCS) weighting method used to compensate for the limitation of the rank order centroid weighting method. Second, grey relational analysis (GRA) is improved by introducing both positive and negative reference (PNR) alternatives instead of a single reference alternative as in the classical GRA. Subsequently, the proposed hybrid grey-point allocation-ROCS weighting method and the GRA-PNR evaluation method are applied to select the most suitable subcontractor for the supply of heliostats for photothermal power station construction. Sensitivity analysis is conducted to verify the robustness of the results. Finally, the technique for order preferences by similarity to an ideal solution with grey values, simple additive weighting with grey relations, and additive ratio assessment with grey criteria scores is applied to validate the participation of the selected subcontractor in the project.

Material Selection for PMEDM Process

Powder Mixed Electro-Discharge Machining (PMEDM) is a non-traditional machining process. This method is used more and more to machine complex surfaces, parts made from materials with high hardness. Three indispensable components in PMEDM are powder, dielectric fluid and electrode. These components have a great influence on the efficiency of the machining process. This study was conducted to choose the best types for all three components mentioned above. The numbers of powder types, dielectric fluid types and electrode material types considered were ten, three and seven, respectively. The weight of each criterion in each product category was calculated using the two methods Rank Order Centroid (ROC) and Rank Sum (RS). In each case, the two methods were used to rank the alternatives are Faire Un Choix Adéquat (FUCA) (in French) and Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS). The optimal option will be found from the results of ranking the alternatives. The results of ranking the alternatives were also subjected to sensitivity analysis by using Sperman coefficient. This study discovered that the best option found when using the FUCA method is also the best option found when using the MARCOS method, and the best option that was found does not depend on the used weighting method.