Analytic Network Process Method Research Articles

Application of the analytic network process method in the selection of raw material suppliers for yarn

Application of the analytic network process method in the selection of raw material suppliers for yarn

An investigation of waqf-based Islamic micro financial institution models to identify the most effective model for Indonesia

Purpose This study aims to determine the best waqf-based Islamic microfinancial institution (IMFI) model by first determining various viable waqf-based IMFI models and then evaluating them based on certain criteria to obtain the best model. Design/methodology/approach A combination of Delphi and analytic network process (ANP) methods was used. The Delphi method was used to determine various waqf-based IMFI models and validate them, whereas the ANP method was used to evaluate those models to prioritize and find the best model. Findings The Delphi results show nine proposed waqf-based IMFI models that have commercial, social or integrated commercial-social orientation, where each could be in the form of a micro bank, micro venture capital (MV) or micro cooperative (MC). Delphi and ANP then determined the strategic, commercial and social criteria to evaluate the models. Finally, the ANP results show that the best waqf-based IMFI models are the integrated waqf-based micro bank, integrated waqf-based MV and integrated waqf-based MC. Integrated waqf-based IMFI provides Islamic microfinance services as well as Islamic social finance services, including waqf, zakat and infaq. Research limitations/implications The adoption of waqf-based IMFI could solve the structural problems of IMFIs, such as funding, low capital, mismatch, liquidity, outreach and sustainability. Practical implications The conceptual framework and method used in this study can be applied to determine and evaluate waqf-based IMFI models in other countries. Originality/value This study begins by determining various viable waqf-based IMFI models and then evaluating them to determine the priority and best waqf-based IMFI model.

EXTRACTING AND PRIORITIZING THE ATTRACTIVENESS PARAMETERS OF SHOPPING CENTERS UNDER INTUITIONISTIC FUZZY NUMBERS

Shopping center plays an important role in distribution system and marketing. These canters provide an appropriate atmosphere for customers; so that, the customers achieve the best service within a short time. However, there is an intense competition among shopping centers to attract more customers for increasing the profit. Therefore, a powerful model assists authorities in identifying the critical competitive aspects and directing their efforts toward performance improvement. However, a number of strategies have been developed to identify the most relevant components. The Delphi technique under intuitionistic fuzzy environment, called intuitionistic fuzzy Delphi method (IFDM) study, is a group-based technique that can simply formulate the uncertainty imposed by decision making circle. On the other hand, multi criteria decision making (MCDM) method such as analytical network process (ANP) is a mathematical tool for taking into account mutual relationships in order to rank a number of criteria. Nonetheless, the ANP is unable to account for the uncertainty involved in the decision-making process. Similarly, the intuitionistic fuzzy set (IFS) can express ambiguity and vagueness by utilizing the given scale. Because the IFS is robust in dealing with complexity and ambiguity, the IFS-GANP (an integrated model of the IFS and ANP methods under group decision) can result in a more specific description of the situation. As a result, the IFS-GANP approach outperforms both conventional ANP and fuzzy ANP. To demonstrate the model’s feasibility, a case study rating the essential aspects impacting the attractiveness of retail centers is shown. The result demonstrates factor C31 (Location) with value of 0.202 plays the greatest role in attracting customers.

A study on the improvement of bicycle transportation in Sivas city using hybrid multi-criteria model based network analysis

AbstractThe bicycle stands out as a sustainability-friendly vehicle due to its benefits for health, the environment, and the economy. However, the deficiencies and inadequacies in the cycling infrastructure prevent a safe and comfortable riding environment, in addition to indirectly preventing the widespread use of bicycles. This study aims to integrate a few disconnected bicycle routes in a city and create a bicycle road network that will allow the efficient use of bicycles in the urban area by using a Hybrid Multi-Criteria Model-Based Network Analysis. In the study, considering the physical, social, and visual criteria that should be used when determining bicycle paths, the suitability weight of each road line for bicycle transportation was determined. In this step, the bicycle path network was created using the weighted roads between the important points of the city in terms of tourism, trade, education, health, culture, transportation, and recreation areas. The most suitable bicycle routes were generated by network analysis considering the weighted roads that were determined by a model hybridized with the analytic hierarchy process (AHP) and analytic network process (ANP) methods and minimum distances. When the eligibility checks of the obtained routes were made, it was determined that while 99.7% of the roads passed through moderately suitable, suitable, and very suitable roads, only 0.3% of the new routes passed through unsuitable roads. The findings revealed that both efficient and less costly bicycle lines can be created using the proposed method.

Analisis Produktivitas Data Center dengan Menggunakan Metode Objective Matrix dan Analytical Network Process di Dinas Kominfo Kaltim

Measurement of productivity in the Diskominfo Kaltim data center is crucial for several reasons. One of these reasons is the significant energy consumption associated with data centers. Furthermore, there has been no prior measurement of productivity in the Diskominfo Kaltim data center. In efforts to measure and analyze data center productivity, the Objective Matrix (OMAX) method can assist in identifying factors influencing productivity improvement. Besides utilizing the OMAX method for productivity measurement, the Analytical Network Process (ANP) method is employed for weighting. ANP can accommodate the interdependencies among criteria and sub-criteria. In August 2023, a performance indicator of -47.48% was obtained, indicating a decrease in productivity by 47.48% compared to the standard performance. In September 2023, the performance indicator was 23.342%, signifying an increase in productivity by 23.342% compared to the standard performance. In October 2023, the performance indicator was 127.809%, indicating a significant increase in productivity by 127.809% compared to the standard performance. Keywords: Analytical Network Process, Objective Matrix, Productivity

Integrating Sustainability into Risk Management through Analytical Network Process

Sustainable risk management is becoming widely accepted, making the incorporation of environmental, social, and governance (ESG) issues into strategic planning areas crucial to a responsible business philosophy. This article aims to rank organizational sub-risks with a focus on sustainability, offering a methodology based on the analytical network process (ANP) method to improve decision-making and reduce misrepresentation in qualitative evaluation criteria. An integrated approach is presented, starting with the characterization of five risk typologies based on global reports and then prioritizing risks and sub-risks using the ANP method. The sustainability sub-risks with the highest level of prioritization for each risk typology are (1) massive data fraud or theft incident (technological risk), (2) deficit in economic growth (economic risk), (3) water depletion (environmental risk), (4) lack of ethics in the conduct of business (geopolitical risk), and (5) chemical safety (social risk). Finally, a cosine similarity analysis is developed to compare the results obtained with the results of a risk prioritization performed with the analytical hierarchy process (AHP) method. The differences between the methods generate a similar risk prioritization; the high similarity indicates the consistency of the relationships and the prioritization of the criteria showing convergence. It is essential to mention that the results should be interpreted cautiously, considering the specific context in which this methodology is developed, and we recommend a periodic verification of risks and sub-risks.

Investigating the Human Reliability in the Healthcare Sector Using the Fuzzy Analytic Network Process and the Success Likelihood Index Method.

We aimed to identify the factors contributing to human error in hospital emergency departments using scientific methods. We used the Fuzzy Analytical Network Process (FANP) and Success Likelihood Index Method (SLIM) to investigate human reliability in 54 hospital emergency departments in 15 provinces of Iran from 2021 to 2022. The study classified 17 general factors affecting human errors in hospital emergency departments. Organizational (0.349), occupational (0.330), and personal factors (0.320) had the most significant impact on human error. Based on a matrix of paired comparisons for nine emergency tasks using the probability of success index method, "checking test results and diagnosis" had the highest probability of error when referring patients to intensive care or discharge. Although the study prioritized patients, there was still a cumulative probability of human error before disease diagnosis at 0.01332, highlighting the need for further training to minimize these risks. The FANP and SLIM were effective in identifying the factors contributing to human error in hospital emergency departments. Doctors and nurses working in these departments require more knowledge, experience, and responsibility to avoid errors. By identifying factors influencing the occurrence of human error and finding solutions to reduce risks, hospitals can improve the quality of their care and prevent errors.

Strategi Usaha Mikro Pengolahan Salak dalam Meningkatkan Perekonomian Desa Wedi Kecamatan Kapas Kabupaten Bojonegoro

The research focuses on the growth of snake fruit processing micro-businesses in Wedi Village, Kapas District, Bojonegoro Regency, aiming to develop sustainable strategies for their development. The success of these enterprises hinges on a comprehensive understanding of internal and external factors. The study analyzes the pivotal factors influencing the growth of salak processing micro-enterprises. It prioritizes development strategies, particularly emphasizing the interplay between product quality (an internal factor) and market demand (an external factor). Utilizing the Analytic Network Process (ANP) method via Super Decision Software, the research assesses development factors comprehensively. The pairwise comparison analysis highlights the priority of internal and external factors in influencing the growth of snake fruit processing micro-enterprises. The findings underscore the significant impact of external factors, exceptionally high market demand, which scored 0.52276, indicating its crucial role in driving microenterprise growth. Meanwhile, product quality, though scoring lower at 0.09885, remains a strategic focus for long-term sustainability. The WT strategy, involving strategic raw material procurement and price adjustments, emerged as the most effective alternative strategy with a score of 0.35614. This underscores companies' need to optimize procurement processes and adapt pricing strategies to capitalize on market demand fluctuations. The research contributes valuable insights into the dynamics of salak processing micro-enterprises at the local level. The formulated strategy guides micro-businesses, local governments, and research institutions to foster sectoral growth. By considering both internal and external factors, the strategy aims to impact regional economic development positively and sustainably. In conclusion, the research highlights the critical role of understanding internal and external dynamics in fostering the growth of snake fruit processing micro-enterprises. The strategy prioritizes leveraging market demand while maintaining product quality for sustained growth and economic development in the region.

Sustainable management model and ecosystem services of mangroves based on socio-ecological system on the coast of Batu Bara Regency, Indonesia

The coastal areas of Batu Bara Regency, Indonesia, face significant challenges due to the conversion of mangrove ecosystems into ponds and tourist destinations. This transformation not only results in the loss of natural coastal protection but also disrupts hydro-oceanography patterns, necessitating comprehensive management solutions that address ecological, economic, and social aspects. To this end, a research was carried out during June to August 2023 developing an integrated management model for sustainable preservation of mangrove ecosystems in Batu Bara Regency. The research aims to evaluate the economic benefits of mangrove ecosystems, particularly emphasizing on regulating, provisioning, and cultural services. The Analytic Network Process (ANP) method is employed to determine priority management strategies by considering the interrelationships between ecological, economic, social, and institutional factors. The model construction incorporates insights from literature reviews and expert interviews, facilitating the formulation of solutions for various aspects of mangrove ecosystem management. The economic value of mangrove ecosystems is estimated in three districts of Batu Bara Regency, with significant contributions to both provisioning and regulating services. In conclusion, the research underscores the importance of strategies such as mangrove area rehabilitation, ecotourism development, outreach and assistance, and community involvement in ensuring the sustainable management of mangrove ecosystems. These strategies hold the potential to preserve these valuable ecosystems, benefiting the environment and local communities alike.

Analyzing Urban Drinking Water System Vulnerabilities and Locating Relief Points for Urban Drinking Water Emergencies

Urban water is known as a critical sector of urban environments which significantly impacts the life quality and wellbeing of reinstates. In the context of developing sustainable urban drinking system it is critical to analyze network events and develop sufficient systems of water supply. To the best of our knowledge, fewer studies have examined the potential of automated-based approaches such as deep learning convolutional neural network (DL-CNN) for analyzing urban water network events and identifying the optimal location of urban drinking water relief posts. Therefore, the current study aims to propose an efficient approach for Geospatial based urban water network events analyze and determine the optimal location of urban drinking water relief posts in Zanjan. For this goal, first, we prepared and preprocessed various predisposing variables for analyzing the urban water network events and determining the optimal location of urban drinking water relief posts. We then applied an integrated approach of analytical network process (ANP) and DL-CNN methods to locate the best location of urban drinking water relief posts. Finally, intersection over union and accuracy assessment were employed to evaluate the performance of the results. Our findings show that the DL-CNN performed well with an accuracy of 0.942 compared to the ANP (0.895) for determining the optimal location of urban drinking water relief posts. According to the results, the best place to build a relief post is in the city center, and the surrounding areas may not be suitable, which is in accordance with field work analysis. The results of the study also reveal that areas 5 and 3 are at high risk from the number of urban water network events perspective, which requires the construction of urban water relief stations.

Designing the Curriculum of the Islamic Banking Study Program towards Higher Education Sustainable Learning

The acceleration of change with the COVID-19 pandemic has made a leap in all aspects, including the banking industry. Islamic banking, which is only a few decades old, has shown a significant increase in assets and institutions that need to be supported by the presence of human resources who understand the characteristics of these institutions so that they do not only focus on domestic affairs but develop overseas. Redesigning the Islamic banking curriculum is urgent in order to prepare the students to become graduates who can be in line with the needs of industrial world. This study aims to redesign the Islamic banking curriculum through in-depth study of stakeholders, namely study program administrators, industry associations (Islamic banking), graduate users, and scientific associations. The method used in this research is a combination by first mapping using the Strength, Weakness, Opportunity and Threat (SWOT) method and then deepening and matching it with the Analytic Network Process (ANP) method to produce priority strategy. The priorities generated based on the SWOT and ANP matrices are : (1) Increasing stakeholder links and matches, (2) Increasing graduate competence, (3) Periodic review and evaluation of the curriculum, (4) Increasing Lecturer capacity. Therefore, Sustainable learning in Islamic banking must be supported by stakeholders by linking and matching in order to fill the need with the availability of competent human resources.

An Effective Selection of Memory Technologies for TCAM to Improve the Search Operations: Demonstration of Memory Efficiency in SDN Recovery

Ternary Content-Addressable Memory (TCAM) is used for storing the flow tables in software-defined networking (SDN)-based OpenFlow switches. However, the TCAM can store only a certain number of flow tables (8000). Moreover, when the switch flow tables need to be updated due to the link failure in the SDN, further updates may be lost due to the flow tables limit of the TCAM space. Hence, to resolve this issue, other memories need to be used in conjunction with TCAM to enhance the memory operations of TCAM. When considering which flash memory technology is to be used in conjunction with TCAM, we need to balance several factors to ensure optimal performance, speed, endurance, reliability, integration complexity, and cost-effectiveness. Hence, it leads to a multi-criteria decision-making problem regarding the selection of other memory technologies such as 3D XPoint, Magnetoresistive RAM, Resistive RAM, and Ferroelectric RAM. In this paper, we use the analytical network process (ANP) method to select the suitable technology in conjunction with TCAM, considering the features of the memory technologies for Software-Defined Internet-of-Things (SD-IoT). We provide a comprehensive numerical model leveraging the ANP to rank the memory technologies regarding their weights. The highest weights identify the most suitable technology for TCAM. We perform simulations to show the effectiveness of the mathematical model utilizing the ANP. The results show that the suggested methodology reduces the recovery delay, improves the packets received ratio (PRR), decreases the jitter, and increases the throughput.

Optimizing electric vehicles charging for enhancing environmental sustainability and reducing carbon emissions of freight transport: case of Czech Republic

The limited infrastructure of charging stations, which is crucial in route planning and total journey time and creates uncertainty in efficiency and operating costs, calls for new economic and statistical methods in sustainability development and environmental economics. This paper aims to examine the challenges of integrating electric vehicles into freight transport to improve distribution logistics’ environmental sustainability, which represents one of the pathways for reducing environmental risk. The analysis results underscore the inadequacy of the truck charging station network in the Czech Republic. This insufficiency presents an opportunity to enhance environmental sustainability and reduce carbon emissions through strategic analysis and optimizing charging station locations. The difficulty of identifying optimal locations for these stations, given truck availability, requires using multi-criteria decision-making techniques such as the Analytical Network Process (ANP). Municipalities with limited access to existing logistics facilities were considered during the simulation. This way, 15 new locations were identified for municipalities with insufficient distance to a charging station.By implementing the ANP method, the study contributes to a more environmentally sustainable transportation infrastructure, highlighting the potential for significant reductions in carbon emissions through improved charging station networks. These results apply to other countries and can provide novel insights on optimizing charging station locations for sustainable economic development and reducing freight transport’s carbon emissions and environmental risks.

Comprehensive evaluation of multi-energy complementary ecosystem based on improved multicriteria decision-making method

Abstract The multi-energy complementary ecosystem is an important form of the modern energy system. However, standardized evaluation criteria and the corresponding method framework have not yet been formed, resulting in unclear standards and irregular processes of its construction. To cope with this issue, a novel comprehensive evaluation framework for multi-energy complementary ecosystems is proposed in this study. First, a 5D comprehensive evaluation criteria system, including environment, economy, technology, safety and systematicness, is constructed. Then, a novel multicriteria decision-making model integrating an analytic network process, entropy and preference-ranking organization method for enrichment evaluation under an intuitional fuzzy environment is proposed. Finally, four practical cases are used for model testing and empirical analysis. The results of the research show that the unit cost of the energy supply and the internal rate of return indexes have the highest weights of 0.142 and 0.010, respectively. It means that they are the focus in the construction of a multi-energy complementary ecosystem. The net flows of four cases are 0.015, 0.123, –0.132 and –0.005, indicating that cases with a variety of energy supply forms and using intelligent management and control platforms to achieve cold, heat and electrical coupling have more advantages.

Analytic Network Process Method On Factors Affecting Increasing The Competitiveness Of The Automotive Industry Sector In Promoting Sustainable Economic Growth In Indonesia

The aim of this research is to determine the factors that influence the growth of the automotive industry sector such as automotive exports, automotive imports, Logistics Performance Index (LPI), monetary policy (rupiah exchange rate), fiscal policy (tax ratio), Total Factor Productivity (TFP ), Inflation, Infrastructure and Automotive Foreign Direct Investment (FDI), on the competitiveness of the automotive industry sector and its implications for economic growth which affects labor absorption, the level of social welfare and people's purchasing power. The research method used is a quantitative data research method with the analytical network process (ANP) method where this method is used to determine the criteria and alternative priority weight values and the results are carried out ranking in determining the influencing factors in this research. The research results show that the factors that influence the competitiveness of the automotive industry sector) and their implications for economic growth affect labor absorption, the level of social welfare and people's purchasing power. So it is concluded that increasing the competitiveness of the automotive industry sector will be able to encourage sustainable economic growth in Indonesia.

Analysis Of The Priority Handling Of Enveromental Drainage Construction Project At Dinas Pekerjaan Umum Dan Penataan Ruang Banjarbaru City

Flood is one of the main problems of big cities in Indonesia, including Banjarbaru City. This is often caused by the not supportive existing drainage capacity when compared to the increasing of crowded urban conditions and reduced green open space. Handling of drainage including rehabilitation is necessary so that drainage can function properly as expected. On the other hand the Banjarbaru City Government has a limited budget each year that can be disbursed for drainage handling. The purpose of this thesis is to analyze criteria and subcriteria that are important in determining the priority of drainage handling. The ANP (Analytic Network Process) method is analyzed using the criteria in the Minister of Public Works regulation number 12/PRT/M/2014 tentang Penyelenggaraan Sistem Drainase Perkotaan to determine priorities for handling environmental drainage with important criteria, namely aspects of inundation, economic loss, social disruption and government facilities, loss of disturbance. transportation, loss to residential areas, and loss of personal property rights. Based on these 6 criteria, priorities for handling environmental drainage in Banjarbaru City are determined. Furthermore, an analysis is carried out to evaluate the priority of the choices that occur. This study suggests to decision makers that ANP can be used to analyze drainage management priorities in Banjarbaru City. This research focuses on variables consisting of criteria or considerations which form the background for priorities in handling the environmental drainage system in Banjarbaru City. The primary data results obtained from the field survey were followed by analysis using the ANP method with data tabulation calculations and assisted by Super Decisions software to determine the priority scale for handling environmental drainage in Banjarbaru City. The treatment priority scale in the Super Decisions software, the data of which is based on field survey results and data tabulation calculations, found that there are several locations that have a large priority scale but treatment has not been carried out due to several factors that are not contained in Minister of Public Works Regulation 12/PRT/M/2014 concerning Implementation of Urban Drainage Systems.

Adaptive Security Activities Selection Model Using Multi-Criteria Decision-Making Methods

Adaptive security activities are a list of recommended security activities to be integrated smoothly with the software development life cycle (SDLC) to produce a secure application software. Adaptive security activities are needed due to the emergence of factors and constraints which have been determined as one of the reasons for the underutilisation of security activities implementation, especially in the earlier phase of software development process. Security activities selection models were proposed to select and recommend security activities but the models were focused on certain factors or as a solution for specific constraints, and thus the recommended security activities were not adaptive. Consequently, an adaptive security activities selection (ASAS) model was proposed by combining the factors and constraints faced by the development team in selecting security activities. The model consisted of two integrated multi-criteria decisionmaking (MCDM) methods, namely Analytic Network Process (ANP) and Reference Ideal Method (RIM). ANP was used to prioritise and weight the criteria while RIM was used to measure and evaluate the security activities with the value of constraints in regard to each criterion. To validate the model a case study was performed on four inhouse web application development teams in the Malaysian public sector. The proposed model was able to recommend security activities in the requirement and design phase based on different constraints faced by each of the development teams. The model was adaptive due to its flexibility and ability to change and suit different evolved conditions when recommending the security activities.

The Application of Network Analysis for Green R&D Indicators (Case Study of the Home Appliance Industry)

The objective of the present study is to develop a model for green research and development (R&D) in the path towards sustainable development within the home appliance industry. This research is applied in nature and descriptive-survey in terms of data collection method. Initially, through a literature review, 30 factors were identified as indicators for green development and formulation and were categorized into five dimensions: green management, product performance and stakeholders, internal environment management, green innovation, and energy and resource consumption management. To screen and validate the factors extracted from the literature, the fuzzy Delphi method was used by surveying 15 selected experts through purposive sampling, which led to the identification of 25 components across the five dimensions. Subsequently, the importance of each criterion and sub-criterion was determined based on the Analytic Network Process (ANP) method, using a pairwise comparison questionnaire with Super Decisions software. The reliability of the tool was confirmed with a consistency ratio below 0.1. Based on the findings, green management, with a weight of (0.261), has the highest priority among the other criteria. Similarly, the product performance and stakeholders criterion (0.220) ranks second, internal environment management (0.202) ranks third, green innovation with a weight of (0.191) ranks fourth, and energy and resource consumption management with a weight of (0.124) ranks fifth. According to this ranking, it can be concluded that factors related to green management hold the greatest importance in green R&D indicators.

Research on the Evaluation of Higher Vocational Students’ Occupational Literacy in the Context of Big Data

Abstract The current education and evaluation systems for vocational literacy in higher vocational institutions are inadequate, hindering high-quality talent development. This study utilizes the hierarchical-gray correlation method to construct an evaluative framework for assessing vocational literacy, identifying key indices through a judgment matrix scaling method. We further refine our analysis using the Analytic Network Process (ANP) method to calculate the influence between indices, culminating in a comprehensive student vocational literacy evaluation model. Notably, our approach disregards dimensions in index evaluation, computing a final comprehensive score. The quality of our empirical investigation was assured through extreme value and homogeneity tests, revealing a Consistency Ratio (CR) between −26 and −20 (absolute value > 3) and a correlation coefficient (r) between 0.601 and 0.893 (absolute value < 0.4), with a significance level (P value) of 0.000, indicating high survey quality. Analysis of 21 tertiary components yielded an average score of 3.5260, with 42.86% of indices surpassing this average, suggesting generally good vocational literacy among students.

The application of Analytic Network Process (ANP) in selecting the intersection investment between Tran Hung Dao – 3 Thang 2 – Mau Than in Ninh Kieu District, Can Tho City

The analysis and evaluation of construction investment options in Vietnam is still qualitative and subjective, so investment decisions are not truly rational. This study proposes the Analytical Network Process (ANP) method applied to build evaluation models and then selecting criteria to quantify and digitize with specialized software, to analyze and make appropriate decisions. This research was conducted through a survey of 74 construction experts and engineers undertaking different roles in the project (state management agencies, investors, consultants, contractors, etc.). As a result, 29 variables (divided into 06 groups of factors), were established and analysed using Superdecision software. The study shows that option 01 (intersection renovation and expansion) has the highest score; and was proposed to invest and implement in practice.