Prediksi Jumlah Produksi Akibat Penyebaran Covid-19 Menggunakan Metode Fuzzy Takagi-Sugeno - Khofifah Putriyani; Tenia Wahyuningrum; Yogo Dwi Prasetyo (Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2021)
Global Bakery is a food company engaged in bread production that is having difficulty determining how much bread will be produced in the event of a pandemic. This study aims to help predict the amount of bread that will be produced during a pandemic. With the benefit of making it easier for companies to determine the amount of bread to be produced. Data obtained from Global Bakery and the official website of Covid-19 Bekasi Regency from March 20, 2020 to April 20, 2020. The author uses the Fuzzy Takagi-Sugeno method to predict the amount of bread that must be produced by Global Bakery during a pandemic with the following stages: fuzzification, rule formation, calculating ɑ-predicate and zi value, then calculating defuzification. Then an evaluation is carried out using the Mean Absolute Percentage Error (MAPE). This study uses Matlab's GUI tools in implementing the Predictor program. The Fuzzy Takagi-Sugeno method is able to predict the amount of bread production at Global Bakery with optimal results, where if the sales are 180 pieces, the remaining sales are 289, and the number of positive cases of Covid-19 is 6 people with the actual production number of 469 pieces, then The prediction results obtained were 347 units. The results of the calculations that have been done obtained the results of accuracy with a good category, namely with a MAPE value of 18.6%.