MCGDM with AHP based on Adaptive Interval Value Fuzzy

Madura is one of the regions in East Java Province whose economy is supported by the SME sector. Industrial Revolution 4.0, this refers to the concept of using the internet for various things, as well as cloud-based and smart manufacturing. The agency has difficulty in identifying needs of Batik UKM, so a performance recommendation model for Batik SMEs is needed to assist Dinas and UKM players in making decisions to determine the performance improvement of Batik SMEs. The purpose of this study is to determine recommendations by measuring the performance of MSMEs in facing the industrial revolution 4.0. This performance measurement is based on 9 indicators, namely Employee Training or SME owners, Number of Batik Motif Variations, Number of Consumers, Product Brands or Branding, Owner Education, Number of Information Technology Certified Employees, Owning a Markerplace, Online Marketing, and Online Payment. The method used in this research is the FANP method. Fuzzy has excellent performance, the decision-making process is more flexible, and is able to handle data that contains uncertainty and inaccuracy by making decisions based on many criteria. The advantage of ANP is that there is dependence and feedback between each criterion, so that all criteria are calculated proportionally. The results of this study are the weighting of priority indicators on all indicators that affect the industrial revolution 4.0. Based on the research and consistency ratio tests, the main indicators needed for SMEs in Bangkalan Madura to face the industrial revolution 4.0 are marketplace, online marketing and information technology certified employees.

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The SME performance recommendation system facing the 4.0 industrial revolution uses the Fuzzy ANP method

Kustiyahningsih

Anamisa

Mufarroha

2021

J. Phys.: Conf. Ser.

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MCGDM for selection of OSN participants using integration AHP and MOORA methods

Kustiyahningsih

Sophan

Ummah

et al. 2021

J. Phys.: Conf. Ser.

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The Olympics of Science National (OSN) is one of the government’s efforts to improve quality of education. The many indicators of measurement and decision-making involved in process of selecting prospective OSN participants required a decision support system for selection of prospective participants to make it easier and transparent. Indicators in this assessment are academic grades, skills grades, class rank and absenteeism. The science department, academic grades and skills scores have mathematical, chemical, physical, biological sub-criteria. There are geography and economic majors in social science. The method used in the decision support system is Analytic Hierarchy Process (AHP) Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) integration based on group or Multi Criteria Group Decision Making (MCGDM) with geometric mean aggregation. Based on research that has been done with a CR less than 0.01, the accuracy obtained is for physics 89.7%, biology 92%, mathematics 90%,chemistry 93.7%, geography 93.8%, and economics 86.6%. The highest accuracy is in Geography

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Decision support system for mapping SMEs batik Bangkalan facing industry 4.0 using SMART method

Kustiyahningsih

Anamisa

Mufarroha

2021

J. Phys.: Conf. Ser.

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There are many criteria and alternatives in determining recommendations and mapping of SMEs, so a decision-making method is needed. The SMART method is a multi-criteria decision-making technique where each alternative consists of number criteria that have values and describes how important the criteria are compared to other criteria. This weighting is used to assess each alternative in order to obtain the best alternative. Industry 4.0 criteria used are owner education, production results, information technology certified employees, having a marketplace, online payment facilities, online marketing media, e-commerce systems and information systems for SMEs. The purpose of this study is to map SMEs in Bangkalan into 4 levels in order to carry out work programs in the face of the 4.0 industrial revolution using the adaptive SMART method. The results of this study are 35% entered the mature readiness stage of Industry 4.0, 28% entered the early readiness stage and 37% entered the intermediate readiness stage readiness stage. Accuracy results the feasibility of the system by the SMEs cooperative office and SME players was 91.15 %.

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MCGDM with AHP based on Adaptive Interval Value Fuzzy

Cited by 10 publications

References 15 publications

The SME performance recommendation system facing the 4.0 industrial revolution uses the Fuzzy ANP method

The SME performance recommendation system facing the 4.0 industrial revolution uses the Fuzzy ANP method

MCGDM for selection of OSN participants using integration AHP and MOORA methods

Decision support system for mapping SMEs batik Bangkalan facing industry 4.0 using SMART method

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