Diagnosa Penyakit Tanaman Cabai menggunakan Metode Forward Chaining dan Naïve Bayes
DOI:
https://doi.org/10.35870/jtik.v5i2.208Keywords:
Chili disease, Expert System, Forward Chaining, Naïve BayesAbstract
The purpose of this research is to design a web-based expert system application to provide information about chili plant diseases and to diagnose the symptoms of diseases that attack chili plants and to provide solutions for appropriate handling methods, which can be accessed anywhere and utilized by the wider community and can speed up the time to deal with diseases that attack chili plants. This study uses the Forward Chaining and Naïve Bayes Methods in order to know the facts/signs of chili disease so that you can get the best quality chili. Based on the results of the discussion and calculation of the web-based expert system for diagnosing chili disease using the Forward Chaining and Naïve Bayes methods, it can be concluded that a simple application it can make it easier for users to diagnose chili disease and find out the causes and solutions. And can find out the total number of all comparisons of the 2 methods.
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Samsudin, S., 2018. Perancangan dan implementasi sistem pakar untuk mendiagnosa penyakit pada tanaman cabai rawit menggunakan metode forward chaining. Sistemasi: Jurnal Sistem Informasi, 4(1), pp.36-44.
Muslim, A.A., Arnie, R. and Sushermanto, S., 2016. Sistem Pakar Diagnosa Hama Dan Penyakit Cabai Berbasis Teorema Bayes. Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi, 4(3).
Mahmudi, A., Rokhman, M.M. and Prasetio, A.E., 2016. Rancang Bangun Sistem Pakar Untuk Mendiagnosis Tanaman Cabai Menggunakan Metode Bayes. Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi, 2(2), pp.85-90.
Muhardi, M., 2020. Sistem Pakar Diagnosa Hama Dan Penyakit Tanaman Cabai Menggunakan Metode Forward Chaining Di Desa Langsat Permai. Jurnal Ilmu Komputer, 9(1), pp.27-34.
Fitriani, M.A. and Febrianto, D.C., 2020. Penerapan Sistem Pakar untuk Diagnosa Penyakit dan Hama Tanaman Cabai dengan Metode Forward Chaining. Sainteks, 16(2).
Wijaya, L.K., 2020, May. Web-Based Expert System To Detecte Chili Desease Using Rule Base Reasoning Approach. In Journal of Physics: Conference Series (Vol. 1539, No. 1, p. 012026). IOP Publishing.
Susanti, S. and Manahan, O., 2020. Disease Diagnosis Expert System At Chili Plants Using Bayes Method. Journal of Computer Networks, Architecture, and High-Performance Computing, 2(2), pp.292-296.
Irnaldi, R., 2019. Sistem Pakar Diagnosa Penyakit Tanaman Cabai Menggunakan Metode Forward Chaining Berbasis Android. Jurnal Perencanaan, Sains Dan Teknologi (JUPERSATEK), 2(1), pp.165-174.
Nusantara, D.O., Pamungkas, S.W., Syaifudin, N.R., Kusuma, L.W. and Fikri, J., 2017. Sistem Pakar Analisa Penyakit pada Tanaman Cabai Merah Menggunakan Metode Backward Chaining. Semnasteknomedia Online, 5(1), pp.3-5.
Rusmi, R., Defiariany, D. and Purwanti, S., 2016. Web-Based Expert Systems For Diagnosing Pest And Disease In Chili Plant Using Forward Chaining. Jurnal Sains dan Informatika: Research of Science and Informatic, 2(2).
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