Application of sugeno's fuzzy inference system (FIS) in determining palm oil production - Maristella; Sinaga, Marlina Setia (Jurnal Absis: Jurnal Pendidikan Matematika dan Matematika, 2025)
Palm oil is an important export commodity in Indonesia, and factors such as palm oil prices, production, and palm oil prices influence palm oil production. In this research, the fuzzy logic method is used to overcome uncertainty in predicting palm oil production. Various fuzzy methods, including Mamdani, Tsukamoto, and Sugeno, are used to model production based on certain factors. The type of research carried out in this research is a literature study and this research uses secondary data or data obtained by other parties. Secondary data taken is CPO price data, palm oil prices and palm oil production data. The prediction results for palm oil production using the Sugeno fuzzy method for several months are based on factors such as CPO prices and palm oil prices in the fuzzy system. The final results of MAPE provide information about the level of accuracy of the model in predicting palm oil production, which is 7.09%. FIS Sugeno connects input-output with fuzzy rules. The steps include variable selection, membership functions, rules, inference, defuzzification, evaluation, optimization, and implementation. The predicted MAPE is 7.09%, indicating the accuracy of the model in estimating palm oil production compared to the actual value.