Sistem Pakar Diagnosa Penyakit dan Rekomendasi Pemupukan Tanaman Kopi Menggunakan Metode Cartainty Factor Berbasis Web

Abstract

Coffee is a commodity that plays a strategic role in the economy; however, its productivity often declines due to disease outbreaks and improper fertilization practices. A shortage of agricultural experts in Sumber Tani Village often results in delayed responses by farmers to these issues. This study aims to develop a web-based expert system capable of diagnosing diseases and providing fertilization recommendations for coffee plants quickly and accurately. The system was developed using the Waterfall method, ensuring a structured software development process covering requirements, design, coding, and testing. To handle the diagnosis of disease symptoms, the study employs the Certainty Factor (CF) method. This method processes confidence values from both experts and users to generate a diagnostic conclusion along with a corresponding confidence level. The resulting web-based expert system was tested using the Black Box Testing method to verify proper functionality and assess diagnostic accuracy against real-world field data. Implementation results demonstrate that the expert system effectively replicates expert knowledge, thereby assisting farmers in Sumber Tani Village to independently take preventive measures against coffee plant diseases and optimize fertilization dosages to increase agricultural yields.