Evaluasi dan Perancangan User Interface Website Klikdokter.com Berbasis Mobile untuk Lansia

Abstract

- Several factors cause low quality and productivity of coffee in Indonesia. Pests and diseases are considered as two of the main reason for these factors. Most coffee farmers in Indonesia, particularly in Province of Lampung are undereducated farmers. They still use traditional practices to identify pests and diseases. Using an expert system, we hope that farmers can accurately diagnose coffee pests and diseases. The main goal of this research is to develop a web-based expert system to diagnose coffee pests and diseases. To identify the pests and diseases Breadth First Search (BFS) technique was implemented. The data consist of 5 pests, 5 diseases, 28 symptoms of pest, and diseases the coffee plant. Certainty factor is used to weight the symptoms and it was determined by experts and the user. Then the certainty factor is iteratively computed the system to measure the likelihood of the diagnosis. To evaluate this system, 30 users were chosen and grouped into three clusters (the coffee experts, farmers, and agriculture students, computer science students). They were asked to assess this expert system by fulfilling questionnaires. They inferred that this system runs well with percentage respectively 75.56%, 73.78%, and 83.39%.