Application of Certainty Factor Method in Diagnosing Nutrient Deficiency in Coffee and Coconut Plants

Abstract

Plantation Coffee and coconut are superior export commodities that have a high investment value in maintaining the economy and balancing the balance of plantation commodities in Indonesia. One of the obstacles that is often experienced by managers of coffee and coconut cultivation is a lack of understanding in the diagnosis of plants that are deficient in macro and micro nutrients, as the main needs for quality of the results. On the other hand, the number of plantation crop experts is relatively small. Seeing these conditions, this study has built an expert system that is able to diagnose the symptoms of nutrient deficiency in coffee and coconut plants. The expert system is built by applying the certainty factor method, so that it can overcome the problem of uncertainty in diagnosing. The percentage level of certainty is obtained from the MB and MD assessment of an expert. This expert system was built using the Expert System Development Life Cycle method. The results of this study are a web-based expert system that is suitable for use by managers of coffee and coconut cultivation in diagnosing nutrient deficiencies, so that it can be known in detail independently and can reduce production costs.