Penerapan Metode Forward Chaining Pada Sistem Pakar Untuk Diagnosa Hama Dan Penyakit Padi

  • Khurotul Aeni Universitas Peradaban


So that the computer can act as and as good as a human being, then the computer should be given the lack of knowledge that has the ability to catch. One of them is an expert system, is a system that attempted to adopt human knowledge to a computer that is designed to model the ability to resolve problems such as befits an expert. With this expert system, people who have yet to figure it out at all to resolve the problem or just simply looking for an actual information can only be obtained with the help of experts in their field. Knowledge society in Indonesia about pests and diseases of rice plant is still low, including handling is known only to the extent of the knowledge of fellow farmers, pest and disease if there is a new kind of farmers are not aware of it, on the other hand there are some the expert or experts who know about the pests and diseases of rice plant, but the number of experts or experts with a large number of farmers are not balanced. Therefore, due to the application of the method of forward chaining inference on expert system to diagnose plant pests and diseases of rice can be the information and knowledge that will help the community or individuals to know the types of pests and what diseases that attack the rice plant, without having to wait and expect a straight answer from the experts


A. H. Dadi Rosadi, “Sistem Pakar Diagnosa Penyakit Tanaman Padi Menggunakan Metode Forward Chaining,” Jurnal Computech & Bisnis, Vol-8, No.1, 2014.

B. Tjahjono, Pengendalian Hama dan Penyakit Padi, Jakarta, 2003.

S. Kusumadewi, Artificial Intelligence (Teknik dan Aplikasinya), Yogyakarta: Graha Ilmu, 2003.

M. Arhami, Konsep Dasar Sistem Pakar, Yogyakarta: Andi, 2005.

I. Sommerville, Software Engineering (Rekayasa Perangkat Lunak), Jakarta: Erlangga, 2011.

How to Cite
AENI, Khurotul. Penerapan Metode Forward Chaining Pada Sistem Pakar Untuk Diagnosa Hama Dan Penyakit Padi. INTENSIF, [S.l.], v. 2, n. 1, p. 79-86, feb. 2018. ISSN 2549-6824. Available at: <>. Date accessed: 20 apr. 2018. doi:
Artificial Intelligent

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.