DISEASE DIAGNOSIS SYSTEM IN APPEL PLANT USING BACKWARD CHAINING METHOD

Zainal, Rifki Fahrial and Purbaningtyas, Rani and fadhilah, Dina Zahrotul (2019) DISEASE DIAGNOSIS SYSTEM IN APPEL PLANT USING BACKWARD CHAINING METHOD. JEECS (Journal of Electrical Engineering and Computer Sciences), 4 (2). pp. 641-654. ISSN 2579-5392 P.ISSN: 2528-0260

Text Disease diagnosis_Jeccs_2019_140-577-1-PB.pdf Download (1MB)

Abstract

Apples are one type of food that contains nutrients, vitamins and minerals that are very good for consumption because it has antioxidants that are good for the body. However, in cultivating these apple plants there are many obstacles, especially when the plant is attacked by disease. Diseases that attack apple plants greatly affect fruit production, because it can produce bad fruit and can result in the death of apple trees. The disease attack can be resolved quickly if it is able to identify the type of disease that attacks it quickly and precisely based on the symptoms that appear. So that the impact can be minimized as early as possible. The purpose of this research is to build an expert system of diagnosing diseases in apple plants by using the backward chaining method that can facilitate in providing information about the causes of the emergence of diseases and how to deal with apple plants quickly and accurately. From the application trial results with the Expert Diagnosis System in Apple Plant Diseases Using the Backward Chaining Method, users can find out the symptoms of diseases experienced by apple plants and test results by making comparisons using the forward chaining method the results are the same as backward chaining accuracy level of 100 % input from backward chaining is the same as output from forward chaining

Item Type:	Article
Uncontrolled Keywords:	Apple, Apple Desease,
Divisions:	Faculty of Engineering > Bachelor of Informations Technology
Depositing User:	Perpus Ubhara Surabaya
Date Deposited:	06 Sep 2022 04:06
Last Modified:	06 Sep 2022 04:35
URI:	http://eprints.ubhara.ac.id/id/eprint/1364

Actions (login required)

View Item