Abstract

This research focuses on issues within the agricultural sector, specifically in cocoa farming. The associated problem is the lack of agricultural extension workers, which results in farmers' limited understanding of cocoa plant diseases and their management. As a consequence, disease identification in cocoa plants has traditionally relied on mere estimates, often proving inaccurate and inefficient in taking appropriate actions. The primary objective of this research is to design and develop an Android-based application utilizing the Certainty Factor method for diagnosing diseases in cocoa plants. The application is envisioned to function as an intelligent consultant for providing disease diagnoses in cocoa plants. The research employs the Research and Development methodology, gathering data from both primary and secondary sources through observations and interviews. The application is tested using both whitebox and blackbox methodologies. Whitebox testing results demonstrate that the system can operate effectively, as indicated by calculations of V(G) and Cyclomatic Complexity (CC). Blackbox testing, conducted with sample tests, also indicates that the system functions as expected and efficiently. In conclusion, the system developed in this research can significantly assist users, particularly farmers, in diagnosing diseases in cocoa plants. The expert system for diagnosing cocoa plant diseases can be relied upon and operates effectively.

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