IMPLEMENTASI METODE CERTAINTY FACTOR DALAM SISTEM PAKAR UNTUK MENGIDENTIFIKASI PENYAKIT TANAMAN LADA

Authors

  • Muslimin B Politeknik Pertanian Negeri Samarinda
  • Putu Sugiartawan STMIK STIKOM Indonesia

DOI:

https://doi.org/10.31598/sintechjournal.v4i2.865

Keywords:

Certainty Factor, Expert System, Pepper Crops

Abstract

Pepper is an agricultural commodity that has a high selling value and is resistant to disease. Identifying the disease in pepper requires knowledge from agricultural experts to evaluate the symptoms of the disease being experienced. Involving an agricultural expert certainly has drawbacks in terms of slow handling, less effective management of large amounts of data. So we need a system that can accommodate these problems. Expert system is one of the sub-branches of science in the field of artificial intelligence, where expert knowledge is expressed in a model with an intelligent-based system. The expert system serves as an interactive consultant media in diagnosing pepper plant diseases based on symptoms. In producing the right decision, a process model is needed in the form of tracing rules and knowledge preference values based on input values in the form of probabilistic data / uncertainty for each symptom. Certainty factor modeling method has the ability to evaluate the preference value of expert knowledge. Based on the model and the weight value of each measure and level of symptoms, it can produce a high level of accuracy decision analysis. Expert systems have advantages that can accommodate expert knowledge in diagnosing pepper plant diseases in time series. This research can help farmers, researchers, experts or agencies in the field of agriculture to identify common diseases of pepper, so that it can provide basic knowledge about various types of diseases and treatment solutions to support the growth of pepper plants.

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Published

2021-10-28

How to Cite

[1]
M. B and P. Sugiartawan, “IMPLEMENTASI METODE CERTAINTY FACTOR DALAM SISTEM PAKAR UNTUK MENGIDENTIFIKASI PENYAKIT TANAMAN LADA”, SINTECH Journal, vol. 4, no. 2, pp. 195-201, Oct. 2021.