Main Article Content

Abstract

Development expert system for diagnosis of pepper plant diseases using certainty factor and naïve bayes methods. Pepper is one type of plant that has long been traded on the European market. So that increasing the quality and quantity of pepper production is the main demand. However, diseases in pepper plants are also familiar to be found so that they can be detrimental to farmers and besides that, agricultural workers who are experts in the field of pepper plant diseases are still limited. Therefore, to overcome this problem, an expert system application is designed where this system can provide information about diseases that attack pepper plants, then provide suggestions or solutions to deal with these diseases. The purpose of this research is to build and design an expert system that is useful for determining pepper plant diseases and to apply certainty factor and nave Bayes methods in providing answers to the results of the consultation. The results of this study are expected to make it easier for users, especially farmers or farm workers in overcoming diseases in pepper plants.

Keywords

certainty factor nave bayes pepper plant disease

Article Details

How to Cite
Karmila, Maria, E., & Annafi’ Franz. (2021). Expert System for Diagnosis of Pepper Plant Diseases Using Certainty Factor and Naïve Bayes Methods. TEPIAN, 2(4), 174-181. https://doi.org/10.51967/tepian.v2i4.744

References

  1. Agus, F., Wulandari, H. E., & Astuti, I. F. (2018). Expert System With Certainty Factor For Early Diagnosis Of Red Chili Peppers Diseases. Journal of Applied Intelligent System, 2(2), 52–66. https://doi.org/10.33633/jais.v2i2.1455
  2. Ferdiansyah, W. R., Muflikhah, L., & Adinugroho, S. (2018). Sistem Pakar Diagnosis Penyakit Pada Kambing Menggunakan Metode Naive Bayes dan Certainty Factor. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(2), 451–458. http://j-ptiik.ub.ac.id
  3. Hariyanto, R., & Sa’diyah, K. (2018). Sistem Pakar Diagnosis Penyakit dan Hama Pada Tanaman Tebu Menggunakan Metode Certainty Factor. JOINTECS (Journal of Information Technology and Computer Science), 3(1), 1–4. https://doi.org/10.31328/jointecs.v3i1.500
  4. Kasus, S., Digital, K., Negeri, P., & Jaya, T. S. (2018). Pengujian Aplikasi dengan Metode Blackbox Testing Boundary Value Analysi s. 03(02), 45–48.
  5. Mulyani, Y., & Komarudin, M. (2020). Seminar Nasional Ilmu Teknik dan Aplikasi Industri Sistem pakar diagnosis hama dan penyakit pada tanaman lada menggunakan metode backward chaining berbasis android. 3.
  6. Munif, A., & Sulistiawati, I. (2014). Pengelolaan Penyakit Kuning pada Tanaman Lada oleh Petani di Wilayah Bangka. Jurnal Fitopatologi Indonesia, 10(1), 8–16. https://doi.org/10.14692/jfi.10.1.8
  7. Rositasari, D. S., Hidayat, N., & Bachtiar, F. A. (2018). Implementasi Naive Bayes Dengan Certainty Factor Untuk Diagnosis Penyakit Anjing. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(11), 4491–4497.
  8. Sihotang, H. T. (2019). Sistem Pakar Untuk Mendiagnosa Penyakit Pada Tanaman Jagung Dengan Metode Bayes. 3(1). https://doi.org/10.31227/osf.io/dguhb
  9. Syahrawardi, A., Hidayat, N., & Sihombing, D. (2018). Sistem Pakar Diagnosis Hama-Penyakit Pada Tanaman Sedap Malam Menggunakan Metode Naïve Bayes-Certainty Factor Berbasis Android. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(1), 153–160.
  10. Tosa, C., Mahmudi, A., & Dedy Irawan, J. (2020). Sistem Pakar Diagnosis Hama Dan Penyakit Tanaman Vanili Menggunakan Metode Certainly Factor. JATI (Jurnal Mahasiswa Teknik Informatika), 4(2), 73–80. https://doi.org/10.36040/jati.v4i2.2677
  11. Yuliyana, Y., & Sinaga, A. S. R. M. (2019). Sistem Pakar Diagnosa Penyakit Gigi Menggunakan Metode Naive Bayes. Fountain of Informatics Journal, 4(1), 19. https://doi.org/10.21111/fij.v4i1.3019