Expert System for Pest Diagnosis on Local Black Rice Plant in East Kalimantan Using the Naive Bayes Method

Authors

  • Novianti Puspitasari Universitas Mulawarman, Samarinda, Indonesia
  • Anindita Septirini Universitas Mulawarman, Samarinda, Indonesia
  • Rian Bintang Paripurna Universitas Mulawarman, Samarinda, Indonesia
  • Lalu Delsi Samsumar Universitas Teknologi Mataram https://orcid.org/0000-0001-8471-6003

DOI:

https://doi.org/10.56873/jitu.6.2.5271

Keywords:

Black Rice; Expert System; Naive Bayes; Pest

Abstract

Rice plant is a food crop that produces rice as the staple food for the majority of Indonesian people. Local rice which significantly contributes to fulfill the national rice consumption is black rice produced in East Kalimantan. However, local black rice often experiences crop failure due to pest attacks and environmental factors. The amount of local black rice production also continues to decrease due to limited human resources who have the skills and knowledge to diagnose pests in black rice plants. Therefore, one effort that can be made to overcome this problem is to create an expert system that can diagnose pests and diseases in black rice plants. The expert system in this research uses the Naive Bayes method, which identifies 11 types of pests that attack black rice plants and 34 symptoms caused by these pest attacks. Naive Bayes can provide information about the percentage of pests that rice plants might experience. Based on the results of the test cases, an accuracy value of
80% was obtained, so the expert system built in this research can diagnose pests on black rice plants quite well.

Author Biography

Lalu Delsi Samsumar, Universitas Teknologi Mataram

Teknologi Informasi

References

A. Syuhada, M. E. Armanto, A. Siswanto, M. Yazid, and E. Wildayana, “Food security and environmental sustainability on the South Sumatra Wetlands, Indonesia,” Syst. Rev. Pharm., vol. 11, no. 3, pp. 457–464, 2020.

A. Hasbianto, R. D. Ningsih, M. Amin, M. Yasin, and A. Noor, “Performance of six new superior varieties of rice on tidal swamp-land in South Kalimantan Province,” in IOP Conference Series: Earth and

Environmental Science, 2021, vol. 911, no. 1, p. 12030.

V. E. Aristya and T. Taryono, “Pemuliaan Tanaman Partisipatif untuk Meningkatkan Peran Varietas Padi Unggul dalam Mendukung Swasembada Pangan Nasional,” Agrotechnology Innov., vol. 2, no. 1, pp. 26–35, 2019.

D. Rahmawati, P. Santika, and D. R. R. Fauzi, “Characterization of five local varieties of rice (Oryza sativa L.) in east java, Indonesia,” in IOP Conference Series: Earth and Environmental Science, 2023, vol. 1168, no. 1, p. 12013.

B. Thanuja and R. Parimalavalli, “Role of Black Rice in Health and Diseases,” Int. J. Heal. Sci. Res, vol. 8, pp. 241–248, 2018.

M. B. Ulum and V. Tundjungsari, “Designing Fuzzy Expert System to Identify Child Intelligence,” TELKOMNIKA (Telecommunication Comput.

Electron. Control., vol. 16, no. 4, pp. 1688–1696, 2018.

D. N. Mhawi, A. Aldallal, and S. Hassan, “Advanced Feature-Selection-Based Hybrid Ensemble Learning Algorithms for Network Intrusion Detection Systems,” Symmetry (Basel)., vol. 14, no. 7, p. 1461, 2022.

N. Puspitasari, H. Hamdani, H. R. Hatta, A. Septiarini, and Sumaini, “Penerapan Metode Teorema Bayes untuk Mendeteksi Hama Pada Tanaman Padi Mayas Kalimantan Timur,” SINTECH (Science Inf. Technol.

J., vol. 4, no. 2, pp. 155–162, 2021, doi: 10.31598/-sintechjournal.v4i2.919.

L. Pasaribu, “Sistem Pakar Mendiagnosa Hama dan Penyakit Tanaman Mentimun Menggunakan Metode Naïve Bayes,” Pelita Inform. Inf. dan Inform., vol. 7, no. 3, pp. 416–420, 2019.

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.

M. M. Amalia, E. Ernawati, and A. Wijanarko, “Implementasi Metode Naïve Bayes dalam Sistem Pakar Diagnosis Hama dan Penyakit pada Tanaman Hias Aglaonema SP.,” J. Rekursif, vol. 10, no. 1, pp. 23–39, 2022, doi: 10.33369/rekursif.v10i1.18953.

Y. V. Via, H. Maulana, and S. Miftakhoneki, “Penerapan Metode Naive Bayes Sebagai Diagnosa Hama Penyakit Tanaman Belimbing,” J. Ilm. Teknol. Inf. dan Robot., vol. 2, no. 2, pp. 27–32, 2020, doi:

33005/jifti.v2i2.35.

B. B. Suherman, “Sistem Pakar Diagnosa Penyakit dan Hama pada Tanaman Jagung Menggunakan Metode Naive Bayes,” J. Inform. dan Rekayasa Perangkat Lunak, vol. 2, no. 3, pp. 390–398, 2021, doi: 10.33365/jatika.v2i3.1251.

Y. E. P. Yulian, “Rancang Bangun Menggunakan Metode Naive Bayes dalam Sistem Pakar Penentuan Penyakit Tanaman Nanas Berbasis Web,” J. Portal Data, vol. 1, no. 1, 2021.

Y. Yuliana, P. Paradise, and K. Kusrini, “Sistem Pakar Diagnosa Penyakit ISPA Menggunakan Metode Naive Bayes Classifier Berbasis Web,” CSRID (Computer Sci. Res. Its Dev. Journal), vol. 10, no. 3, pp. 127–138, 2021.

R. H. Restari, S. Sinurat, and S. Suginam, “Rancangan Aplikasi Sistem Pakar Diagnosa Penyakit Mononukleosis dengan Metode Naive Bayes,”

JURIKOM (Jurnal Ris. Komputer), vol. 7, no. 3, pp. 403–408, 2020, doi: 10.30865/jurikom.v7i3.2179.

Aristoteles, K. Adhianto, R. Andrian, and Y. N. Sari, “Comparative Analysis of Cow Disease Diagnosis Expert System using Bayesian Network and DempsterShafer Method,” Int. J. Adv. Comput. Sci. Appl., vol. 10, no. 4, pp. 227–235, 2019, doi: 10.14569/ijacsa.-2019.0100427.

J. A. Widians, N. Puspitasari, and A. A. M. Putri, “Penerapan Teorema Bayes dalam Sistem Pakar Anggrek Hitam,” Inform. Mulawarman J. Ilm. Ilmu Komput., vol. 15, no. 2, 2020, doi: 10.30872/-jim.v15i2.4604.

F. T. Zohra, “Prediction of Different Diseases and Development of a Clinical Decision Support System using Naïve Bayes Classifier,” Int. J. Res. Appl. Sci. Eng. Technol., vol. 8, no. 5, pp. 8–13, 2020, doi: 10.22214/ijraset.2020.5002.

R. Yuliza, “Sistem Pakar Akurasi dalam Mengidentifikasi Penyakit Gingivitis pada Gigi Manusia dengan Metode Naive Bayes,” J. Sistim Inf.

dan Teknol., vol. 5, no. 1, pp. 27–32, 2022, doi: 10.37034/jsisfotek.v5i1.157.

T. R. S. Hari and S. Sumijan, “Sistem Pakar dengan Menggunakan Metode Naive Bayes dalam Mengidentifikasi Penyakit Karies pada Gigi Manusia,” J. Sistim Inf. dan Teknol., vol. 3, no. 4, pp. 233–238, 2021, doi: 10.37034/jsisfotek.v3i4.71.

Downloads

Published

2023-12-25

How to Cite

Puspitasari, N., Septirini, A., Paripurna, R. B., & Samsumar, L. D. (2023). Expert System for Pest Diagnosis on Local Black Rice Plant in East Kalimantan Using the Naive Bayes Method. Journal of Information Technology and Its Utilization, 6(2), 71–78. https://doi.org/10.56873/jitu.6.2.5271