SISTEM PAKAR MENGIDENTIFIKASI PENYAKIT TANAMAN KACANG PANJANG DENGAN MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS WEB

Penulis

DOI:

https://doi.org/10.31000/jika.v5i3.4157

Abstrak

Penyakit pada tanaman senantiasa dijumpai pada setiap tanaman tidaklah asing lagi bagi petani, tetapi masalahnya adalah apakah penyakit tersebut menimbulkan kerugian yang berarti atau tidak. Kadang - kadang petani tahu kalau tanamannya diserang penyakit, tetapi petani tidak tahu penyakit apa yang sedang menyerang tanaman mereka. Selain itu hal lain yang menyebabkan kegagalan panen adalah karena kesalahan dalam penanganannya dan memilih obat.

Sistem pakar mengidentifikasi penyakit tanaman kacang panjang adalah suatu aplikasi yang memungkinkan pengguna untuk mengidentifikasi penyakit tanaman kacang panjang­­­­­. Pengguna juga mengetahui jenis penyakit tanaman kacang panjang yang sedang dialami beserta keterangan dan solusinya, berdasarkan gejala yang dialami tanaman kacang panjang.Berdasarkan pada hasil pengujian program, sistem pakar mengidentifikasi penyakit tanaman kacang panjang dengan menggunakan metode certainty factor berbasis web ini cukup membantu untuk mengidentifikasi penyakit tanaman kacang panjang berdasarkan pada gejala-gejala yang dialami tanaman tersebut. Berdasarkan 10 data hasil uji didapatkan hasil bahwa kesesuaian aplikasi sistem akar dan hasil pakar yaitu 90%

Referensi

Darmiati, Ni Nengah, dkk., (2015), “Kisaran Inang Bean Common Mosaic Virus (Bcmv) Penyebab Penyakit Mosaik Pada Tanaman Kacang Panjang (Vigna sinensis L.)â€, Vol. 4, No. 4, hal. 274-281.

Hariyanto, Eko, (2001), Budi Daya Kacang Panjang, PT Penebar Swadaya, Depok.

Kusrini, (2008), Sistem Pakar Teori dan Aplikasi, Andi, Yogyakarta.

Kusumadewi, Sri, (2003), Artificial Intelligence, Graha Ilmu, Yogyakarta.

T. Sutojo, S,Si. M.Kom, Edy Mulyanto, S, Si, M.Kom, dan DR. Vincent Suhartono, (2011), Kecerdasan Buatan, Yogyakarta : Andi Yogyakarta.

Annisa R.(2018) Sistem Pakar Metode Certainty Factor Untuk Mendiagnosa Tipe Skizofrenia JCIT (Indonesian Journal on Computer and Information Technology) Vol.3 No.1, Mei 2018, pp. 40~46 . ISSN: 2527-449X. E-ISSN:2549-7421.

Arifin M, Slamin, Retnani WEY . 2017. Penerapan Metode Certainty Factor Untuk Sistem Pakar Diagnosis Hama Dan Penyakit Pada Tanaman Tembakau. BERKALA SAINSTEK 2017, V (1): 21-28. ISSN : 2339-0069

Dian R, Sumijan, Yunus Y. 2020. Sistem Pakar dalam Identifikasi Kerusakan Gigi pada Anak dengan Menggunakan Metode Forward Chaining dan Certainty Factor. Jurnal Sistem Informasi dan Teknologi Vol.2 No. 3(2020) 65-70.

Indriani AF , Rachmawati EY, Fitriana JD. 2018. Pemanfaatan Metode Certainty Factor dalam Sistem Pakar Diagnosa Penyakit pada Anak. Techno.COM, Vol. 17, No. 1, Februari 2018 : 12-22.

Unduhan

Diterbitkan

2021-10-06

Terbitan

Vol 5 No 3 (2021): JIKA (Jurnal Informatika)

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Articles

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