Application of Case Base Reasoning Algorithm in Detecting Disease in Pineapple Fruit

  • Nurhaeka Tou Information Technology, Bangka Belitung University
  • Putri Mentari Endraswari Information Technology, Bangka Belitung University
  • Nur Annisa Informatics, Cokroaminoto Palopo University

Abstract

Pineapple fruit is a type of horticultural plant that has the potential to be developed. In the process of pineapple cultivation, it is very susceptible to pests and diseases. Diseases that often attack pineapples such as; wilt disease, stem base rot, fusariosis, bacterial rot, and urethral disease. The process of identifying pineapple diseases is often done manually so it takes a long time. In addition, in the process of controlling pests and diseases, farmers only spray pesticides or other handling techniques that are not suitable for the pests and diseases that attack them. Thus, the treatment is not optimal and has an impact on the emergence of new pests and diseases in pineapple. Currently, computer technology can be used in various branches of science, one of which is artificial intelligence. The expert system is a scientific branch of artificial intelligence that can solve problems. The purpose of this research is to assist farmers in identifying pests and diseases in pineapples so that the control process can be carried out optimally, quickly, and on target. The implementation of an expert system uses the Case Base Reasoning (CBR) method which will produce a diagnostic similarity value and provide recommendations for diseases that attack. This research processes data in the form of symptoms seen in pineapple plants. The test results obtained a percentage of 100%. Thus, the application of the CBR method is very relevant in identifying pests and diseases of pineapple plants.

Keywords: expert system, CBR, pineapple frit

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References

T. Oviana, T. N. Aeny, and J. Prasetyo, “Isolasi dan Karakterisasi Penyebab Penyakit Busuk Buah pada Tanaman Nanass (Ananas Comosus [L.] Merr.),” J. Agrotek Trop., vol. 3, no. 2, pp. 220–225, 2015.

F. S. Sihombing, “Sistem Pakar Mendiagnosa Penyakit Pada Tanaman Nanas Dengan Menggunakan Metode Clustering,” Inf. dan Teknol. Ilm., vol. 7, no. 2, pp. 198–202, 2020.

Nurmayanti and R. Saputra, “Implementasi Sistem Pakar Berbasis Mobile Untuk Mendiagnosa Hama Dan Penyakit Tanaman Nanas,” Sist. Inf. dan Komputerisasi Akunt., vol. 04, no. 02, pp. 12–16, 2018.

S. Rodliyatun, S. Triyanti, S. H. Suseno, and D. A. Nugroho, “Standar Operasional Prosedur Budi Daya Nanas sebagai Upaya Penanggulangan Serangan Hama dan Penyakit pada Tanaman Nanas,” J. Pus. Inov. Masy., vol. 1, no. 1, pp. 13–20, 2019.

R. Rachman, “Implementasi Case Based Reasoning Mendiagnosa Penyakit Stroke Menggunakan Algoritma Probabilistic Symmetric,” J. Inform., vol. 8, no. 1, pp. 10–16, Feb. 2021.

E. Simatupang, “Jaringan syaraf tiruan menggunakan metode perceptron untuk menentukan penyakit pada tanaman buah nanas,” Maj. Ilm. INTI, vol. 6, no. 2, pp. 55–60, 2019.

Y. S. R. Nur, A. Burhanuddin, D. Aldo, and W. Lelisa Army, “Sistem Pakar Deteksi Penyakit Bawang Merah dengan Metode Case Based Reasoning,” J. MEDIA Inform. BUDIDARMA, vol. 6, no. 3, p. 1356, Jul. 2022.

Z. Nenova and J. Shang, “Chronic Disease Progression Prediction: Leveraging Case?Based Reasoning and Big Data Analytics,” Prod. Oper. Manag., vol. 31, no. 1, pp. 259–280, Jan. 2022.

A. R. Saraswati, Y. Saintika, A. N. A. Thohari, and A. R. Iskandar, “Sistem Pakar Diagnosis Penyakit Ikan Gurami (Osphronemus Goramy) Menggunakan Case Based Reasoning,” J. Teknol. Inf. dan Ilmu Komput., vol. 7, no. 4, p. 779, Aug. 2020.

A. Alwendi and K. Samosir, “Perancangan Aplikasi Sistem Pakar dalam Mendiagnosa Penyakit Infertilitas pada Pria Menggunakan Metode Certainty Factor Berbasis Web,” J. Inform. dan Rekayasa Perangkat Lunak, vol. 4, no. 1, p. 24, Mar. 2022.

E. Krisnanik, K. Kraugusteeliana, and V. Indriasari, “Desain Model Sistem Pakar Menu Sehat Wanita Hamil Berdasarkan Gizi Menggunakan Metode Cooper,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 6, p. 643, Nov. 2018.

P. Wahyuningsih and S. Zuhriyah, “Sistem Pakar Diagnosa Penyakit Campak Rubella pada Anak Menggunakan Metode Certainty Factor Berbasis Website,” J. Teknol. Inf. dan Ilmu Komput., vol. 8, no. 1, p. 85, Feb. 2021.

Asmira and Syamsul Alam, “Aplikasi Sistem Pakar Pengidentifikasi Penyakit Dan Hama Pada Tanaman Padi Berbasis Android,” SIMKOM, vol. 5, no. 2, pp. 19–27, Jul. 2020.

R. Adawiyah, “Case Based Reasoning Diagnosis Hama dan Penyakit Tanaman Nilam,” INTENSIF, vol. 2, no. 1, p. 57, Feb. 2018.

R. Adawiyah and F. Handayani, “Rancang Bangin Case Based Reasoning untuk Diagnosis Hama dan Penyakit Tanaman Nilam menggunakan Nearest Neighbor Kombinasi Certainty Factor,” J. Teknol. Inf. dan Ilmu Komput., vol. 7, no. 3, p. 477, May 2020.

Published
2023-04-19
How to Cite
[1]
N. Tou, P. Endraswari, and N. Annisa, “Application of Case Base Reasoning Algorithm in Detecting Disease in Pineapple Fruit”, JurnalEcotipe, vol. 10, no. 1, pp. 22-31, Apr. 2023.
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