Prediksi Jumlah Produksi Pangan Akibat Pengaruh Penyebaran Covid-19 menggunakan Metode Fuzzy Takagisugeno (Studi Kasus : Global Bakery)
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Khofifah, Putriyani
Subject
T Technology (General)
Datestamp
2021-09-24 08:29:18
Abstract :
Global Bakery is a food company engaged in the production of bread which has difficulty determining how much bread to produce during a pandemic. The issue of determining how much bread to produce requires careful consideration due to the pandemic and the number of confirmed cases as well as the growing spread of Covid-19. Therefore, an effort is needed to help predict the amount of bread that will be produced during a pandemic. The data used in this study were 32 data taken from Global Bakery and the official website of Covid-19 Bekasi Regency in a period of 1 month from March 20, 2020 to April 20, 2020. The data is used as input from fuzzy logic. Fuzzy logic can be used in mapping input values to output precisely. The author uses the Fuzzy TakagiSugeno method in research to predict the amount of bread that must be produced by Global Bakery during a pandemic. Fuzzy Takagi-Sugeno is one of the fuzzy logic that can be used to solve prediction problems, with stages: fuzzification with 3 input variables with 2 fuzzy sets, formation of 8 rules, calculating the αi-predicate value and zi value, then calculating the defuzzification value to get the best result. can be used as an alternative to determining the amount of bread to be produced. Then performed an evaluation using the Mean Absolute Percentage Error (MAPE). In this case, using the Matlab GUI tools in implementing the Predictor program. The results of calculations that have been done with 32 data obtained the results of accuracy with a good category, namely with a MAPE value of 18.6%. Keywords: Production, Food, Sugeno, Covid-19, MAPE
Global Bakery is a food company engaged in the production of bread which has difficulty determining how much bread to produce during a pandemic. The issue of determining how much bread to produce requires careful consideration due to the pandemic and the number of confirmed cases as well as the growing spread of Covid-19. Therefore, an effort is needed to help predict the amount of bread that will be produced during a pandemic. The data used in this study were 32 data taken from Global Bakery and the official website of Covid-19 Bekasi Regency in a period of 1 month from March 20, 2020 to April 20, 2020. The data is used as input from fuzzy logic. Fuzzy logic can be used in mapping input values to output precisely. The author uses the Fuzzy TakagiSugeno method in research to predict the amount of bread that must be produced by Global Bakery during a pandemic. Fuzzy Takagi-Sugeno is one of the fuzzy logic that can be used to solve prediction problems, with stages: fuzzification with 3 input variables with 2 fuzzy sets, formation of 8 rules, calculating the αi-predicate value and zi value, then calculating the defuzzification value to get the best result. can be used as an alternative to determining the amount of bread to be produced. Then performed an evaluation using the Mean Absolute Percentage Error (MAPE). In this case, using the Matlab GUI tools in implementing the Predictor program. The results of calculations that have been done with 32 data obtained the results of accuracy with a good category, namely with a MAPE value of 18.6%. Keywords: Production, Food, Sugeno, Covid-19, MAPE
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