Expert System to Diagnose Diseases in Durian Plants using Naïve Bayes
- Narantyo Maulana Adhi Nugraha Institut Teknologi Telkom Purwokerto, Jawa Tengah, Indonesia
- Reva Rahardian Institut Teknologi Telkom Purwokerto, Jawa Tengah, Indonesia
- Adam Nur Kridabayu Institut Teknologi Telkom Purwokerto, Jawa Tengah, Indonesia
-
Faisal Dharma Adhinata
*
Institut Teknologi Telkom Purwokerto, Jawa Tengah,
Indonesia
- Nur Ghaniaviyanto Ramadhan Institut Teknologi Telkom Purwokerto, Jawa Tengah, Indonesia (*) Corresponding Author
Abstract
Durian is a fruit that is very popular and very easy to find throughout Indonesia. Durian fruit is a thorny fruit with a very pungent smell with a distinctive taste, and for some durian fans, the distinctive taste of durian is what makes durian unique compared to other fruits. However, it is unfortunate that the production and quality of durian fruit in Indonesia is currently still low due to the limited knowledge of farmers in caring for and maintaining durian plants from pests and diseases on durian plants. So far, in detecting pests and diseases, farmers still carry out pest and disease detection manually, and of course, this is very dependent on pest and disease observers/experts. For this reason, so that later the level of production and quality of durian in Indonesia can increase, we create an expert system to diagnose a disease in durian plants to help farmers overcome problems around pests and diseases commonly occur in durian plants. This study uses the Naïve Bayes method as a determinant of durian disease. The experimental results yield an accuracy of 82%, which indicates the proposed method is quite good in diagnosing durian disease.
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References
S. Aldy and P. Suryadarma, “Peningkatan Nilai Tambah Durian Afkir melalui Produksi Dodol Durian di Kuala Selangor Malaysia Increasing Rejected Durian Added Value through Durian Dodol Production in Kuala Selangor Malaysia,” Jurnal Pusat Inovasi Masyarakat, vol. 1, no. November, pp. 92–98, 2019.
P. J. Santoso, “Indonesia Berpotensi Produksi Durian Sepanjang Tahun (Indonesia’s Potential for Durian Production Year-round),” SinarTani: Agroinovasi, vol. 19, no. 3487, pp. 10–16, 2012.
B. P. Statistik, “Produksi Tanaman Buah-buahan 2020,” www.bps.go.id, 2020. https://www.bps.go.id/indicator/55/62/1/produksi-tanaman-buah-buahan.html (accessed Nov. 13, 2021).
A. Handoko, A. L. Abadi., and L. Q. Aini, “Karakterisasi Penyakit Penting Pada Pembibitan Tanaman Durian di Desa Plangkrongan, Kabupaten Magetan dan Pengendalian dengan Bakteri Antagonis Secara In Vitro,” Jurnal Hama dan Penyakit Tumbuhan, vol. 2, no. 2, pp. 15–22, 2014.
H. Triwidodo, S. Wiyono, and P. B. Ayuwati, “Teknik Pembibitan dan Organisme Pengganggu Bibit Durian Menoreh Kuning di Kecamatan Kalibawang, Kulon Progo,” Agrovigor: Jurnal Agroekoteknologi, vol. 13, no. 1, pp. 43–50, 2020, doi: 10.21107/agrovigor.v13i1.6061.
“Seminar Nasional Program dan Strategi Pengembangan Buah Nusantara,” no. Bps 2001, pp. 176–189, 2005.
H. Listiyono, “Merancang dan Membuat Sistem Pakar,” Jurnal Teknologi Informasi DINAMIK, vol. XIII, no. 2, pp. 115–124, 2008.
Y. A. Fitrianingtyas and C. Rahmad, “Sistem pakar deteksi hama dan penyakit pada tanaman cabai dengan metode naïve bayes,” Jurnal Prosiding Seminar Informatika Aplikatif Polinema, vol. 2015, no. 1, pp. 68–72, 2015.
S. Syarli and A. Muin, “Metode Naive Bayes Untuk Prediksi Kelulusan (Studi Kasus: Data Mahasiswa Baru Perguruan Tinggi),” Jurnal Ilmiah Ilmu Komputer, vol. 2, no. 1, pp. 22–26, 2016.
T. Rosandy, “PERBANDINGAN METODE NAIVE BAYES CLASSIFIER DENGAN METODE DECISION TREE (C4.5) UNTUK MENGANALISA KELANCARAN PEMBIAYAAN (Study Kasus : KSPPS / BMT AL-FADHILA),” Jurnal Teknologi Informasi Magister Darmajaya, vol. 2, no. 01, pp. 52–62, 2016.
E. Sudaryanto and A. Suryanto, “Sistem Pakar Diagnosa Hama Dan Penyakit Tanaman Durian Dengan Metode Naive Bayes,” Teodolita, vol. 21, no. 1, pp. 59–64, 2020.
R. M. Napitupulu, Bertanam Durian Unggul. PT Niaga Swadaya, 2010.
A. Furqon and N. I. Fadlilah, “Sistem Pakar Untuk Mendiagnosa Hama Dan Penyakit Pada Pohon Durian,” Konferensi Nasional Ilmu Sosial & Teknologi (KNiST), pp. 105–109, 2016.
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Copyright (c) 2021 Narantyo Maulana Adhi Nugraha, Reva Rahardian, Adam Nur Kridabayu, Faisal Dharma Adhinata, Nur Ghaniaviyanto Ramadhan
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