AVOCADO STOCK PREDICTION IN BANTUL CITY USING MAMDANI FUZZY LOGIC

Abstract

This journal discusses the development of an avocado stock prediction model in Bantul City using the Mamdani fuzzy logic approach. In this context, fuzzy logic is used to address the uncertainty and complexity associated with factors affecting avocado supplies, such as stock variability, demand and price variables. The Mamdani approach is applied to formulate fuzzy rules based on a combination of expert knowledge and historical avocado stock data. This method aims to produce avocado stock predictions that are more accurate and adaptive to market dynamics. Through a series of experiments, the results show that the Mamdani fuzzy logic model has a significant level of accuracy, outperforming traditional stock prediction methods. The results obtained show the potential of this model in improving the efficiency of avocado inventory management at the local level. This research makes an important contribution especially in the context of agribusiness, providing a foundation for a more sophisticated and adaptive prediction approach to avocado fruit stock management. The implications are widely applicable in the agribusiness sector and provide a basis for the development of similar prediction systems for other agricultural commodities.