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dc.contributor.advisorSitepu, Suryati
dc.contributor.authorSelviani, Yunitasia
dc.date.accessioned2025-02-12T04:34:11Z
dc.date.available2025-02-12T04:34:11Z
dc.date.issued2024
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/101164
dc.description.abstractThe fuzzy inference system in making daily decisions is usually based on assumptions, ensuring that every decision always produces results that are uncertain and ambiguous. Decision-making in production planning has become one of the important things every businessperson must do to avoid losses due to unstable production. Fuzzy sets enhance decision-making by defining membership values between true (1) or false (Ο). Fuzzy logic in this reaserch helps in drawing conclusions for determining onion production and producing crisp output values. One factor influencing the ouput values is the input variable and the fuzzy set. The input variables used in this study are the inventory of onion raw materials (x) and the number of orders (y) while the output variable will use the inventory amount variabel (z), where the values of x and y will affect the instability of the output value z. This research will employ the Mamdani fuzzy logic method, whereas previous research using prediction calculation with the Sugeno fuzzy logic method achieved an accuracy level of 14,2%. The prediction calculations using the Mamdani method show that the accuracy level 10%. The Mean Absolute Percentage Error (MAPE) method is used to calculate the accuracy level of predictions. Althought the difference in calculation between the Mamdani and Sugeno methods are relatively small, the analysis indicate the production prediction calculations using the Mamdani method are more accurate and can be used to determine the quantity of fried onion production.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectFuzzy Inference Systemen_US
dc.subjectMamdani Methoden_US
dc.subjectProduction predictionen_US
dc.subjectMAPEen_US
dc.titlePenerapan Logic Fuzzy Inference System Metode Mamdani untuk Menentukan Jumlah Produksien_US
dc.title.alternativeApplication of Fuzzy Logic Inference System Using Mamdani Method to Determine Production Quantityen_US
dc.typeThesisen_US
dc.identifier.nimNIM200803111
dc.identifier.nidnNIDN0011115911
dc.identifier.kodeprodiKODEPRODI44201#Matematika
dc.description.pages50 Pagesen_US
dc.description.typeSkripsi Sarjanaen_US
dc.subject.sdgsSDGs 9. Industry Innovation And Infrastructureen_US


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