Application of naive Bayes Algorithm in Expert System for Diagnosing Chili Plant Diseases Based on Growth Phase on Peatland
Fatayat1 Wahyu Lestari2 Alfirman3

Kampus Bina Widya Km 12,5 Fakultas FMIPA Simpang Baru Pekanbaru 28293 Riau Indonesia

Abstract

Agricultural development on peatlands has its own challenges, especially in the cultivation of chili plants that are susceptible to various diseases. Therefore, an expert system is needed that can help farmers diagnose chili plant diseases quickly and accurately based on the plant growth phase. This research aims to apply the naive Bayes algorithm to the expert system for diagnosing Capsicum annum L (Chili) plant diseases.The expert system is able to diagnose several types of diseases on chili plants in peatlands, such as anthracnose, fusarium wilt, and leaf curl disease. Each diagnosis is based on symptoms observed in each phase of plant growth, from the vegetative phase to the generative phase. From the results of the calculation of the naive Bayes algorithm classification of trial data, there are 8 symptoms of the disease contained in the sample of disease symptoms: G102, G104, G0112, and G114. To determine the results of classification vi with eight codes, the name of the disease has the largest multiplication result with a value of 2.94 by using the equation two formula on codes P102, P104, and P106 according to the name of the disease. This research can be further developed with other crops grown on peatlands or other soils and using different applications to be developed in the field of agriculture in diagnosing plant diseases and various other crops, especially on peatlands that have characteristics at high soil moisture levels, low soil PH, and a tendency to fire or rapid chemical changes. This research also has prospects for collaboration with agricultural research institutions and the government in order to develop technologies to increase agricultural productivity. using this system as part of a smart agriculture support program for farmers in various regions.

Keywords: Peatland Disease Diagnosis naive Bayes Expert System for Chili Plants

Topic: Computational Science