Integrasi Sistem Pakar Deteksi Penyakit Tanaman Bawang Merah Pada E-Commerce Untuk Pemberian Rekomendasi Obat

Abstract

The problem of disease in shallot plants is a major challenge for farmers because it has a direct impact on decreasing crop yields. One of the contributing factors is the mistake in choosing the right medicine or pesticide to overcome pest attacks. This study was designed to develop a web-based system that can help farmers detect diseases in shallots while providing appropriate treatment recommendations. This system utilizes a forward chaining algorithm combined with the certainty factor method to identify the type of disease based on symptoms entered by the user. The research data comes from the experience of farmers in Madiun Regency and relevant literature studies, and has been verified by local farmer groups. Evaluation of the system quality was carried out using the black box testing method and System Usability Scale (SUS) measurement. As a result, the system obtained an average SUS score of 81.6, indicating that this system is easy to use and well accepted by users.