Application of Fuzzy Logic in Predicting Grocery Store Revenue
Penerapan Logika Fuzzy Dalam Memprediksi Penghasilan Toko Sembako
DOI:
https://doi.org/10.21070/ups.8367Keywords:
Grocery store, income prediction, fuzzy logic, Mamdani, MatlabAbstract
Grocery stores face income uncertainty due to price fluctuations and unpredictable market conditions. This study applies the Mamdani fuzzy logic method to improve the accuracy of income prediction. Data were collected through one-month direct observation at a grocery store in Sidoarjo, including the number of items sold, item prices, and operational costs. The variables were represented as fuzzy sets using triangle and shoulder-shaped membership functions. A fuzzy rule system consisting of 27 if-then rules was developed, and the final output was calculated using the Weighted Average defuzzification method. Based on input data of 1,004 items sold, a total sales value of Rp14,124,500, and operational costs of Rp4,500,000, the system predicted an income of Rp10,000,000. Evaluation using Mean Absolute Percentage Error (MAPE) showed an error rate of 0%, indicating very high accuracy. This model proves useful for supporting decision-making in small-scale retail businesses under uncertainty.
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