Application of Fuzzy AHP and Fuzzy TOPSIS methods for the new normal problem

Abstract

The government have new program to deal with the pandemic impact of the Coronavirus, which is said with the new normal. The implementation of the new normal itself requires more attention in terms of the readiness of a region to implement the program. Determination of these areas can be done using the Fuzzy Analytical Hierarchy Process(AHP) and fuzzy technique for Order Performance by Similarity to Ideal Solution(TOPSIS) methods. Fuzzy AHP is used to determine the weight of the existing criteria, while Fuzzy TOPSIS is used to determine the safest area and is ready to implement the new normal. The case study for the problem in this paper is Central Java Province, with alternatives districts and cities. The influencing criterias are the number of People Under Surveillance (PeUS), the number of Patient Under Surveillance (PaUS), the number of patients being treated, the number of positive patients who died, and positive patients who recovered. Triangular fuzzy number approach both methods. The results of this study found that 30% of the total number of districts or cities are ready to implement the New Normal program. This study also explain that the higher of the patient number being treated, the less safe an area will be. While the patients number who recover is increasing, then an area will be ready to implement a New Normal program.