Analysis of Anthracnose Disease in Curly Chilli Using Fuzzy Logic Method

Abstract

Curly chilli (Capsicum annuum L.) is one of the horticultural products that has a high economic value and is often consumed by the people of Indonesia, both as a flavour enhancer for dishes and as a source of nutrition. However, until now, the production of chilli peppers has not been able to meet demand, one of which is caused by anthracnose disease that attacks plants through fungi of the genus Colletotrichum, potentially causing yield losses of 50 to 90%. Until now, there have not been many disease risk prediction systems that consider environmental variables adaptively. This research aims to develop an anthracnose disease risk prediction system based on the Mamdani fuzzy logic method that is able to handle the uncertainty of environmental data such as temperature, humidity, and soil pH. Data are obtained from trusted literature sources and have undergone a validation process before being used in modelling. The system was developed using MATLAB because it supports various features in the implementation of fuzzy logic. Simulation results show high consistency between manual calculations and software results, indicating that the system has a good level of accuracy and potential to be applied in agricultural management.