IMPLEMENTASI METODE CERTAINTY FACTOR DALAM SISTEM PAKAR UNTUK MENGIDENTIFIKASI PENYAKIT TANAMAN LADA
DOI:
https://doi.org/10.31598/sintechjournal.v4i2.865Keywords:
Certainty Factor, Expert System, Pepper CropsAbstract
Pepper is an agricultural commodity that has a high selling value and is resistant to disease. Identifying the disease in pepper requires knowledge from agricultural experts to evaluate the symptoms of the disease being experienced. Involving an agricultural expert certainly has drawbacks in terms of slow handling, less effective management of large amounts of data. So we need a system that can accommodate these problems. Expert system is one of the sub-branches of science in the field of artificial intelligence, where expert knowledge is expressed in a model with an intelligent-based system. The expert system serves as an interactive consultant media in diagnosing pepper plant diseases based on symptoms. In producing the right decision, a process model is needed in the form of tracing rules and knowledge preference values based on input values in the form of probabilistic data / uncertainty for each symptom. Certainty factor modeling method has the ability to evaluate the preference value of expert knowledge. Based on the model and the weight value of each measure and level of symptoms, it can produce a high level of accuracy decision analysis. Expert systems have advantages that can accommodate expert knowledge in diagnosing pepper plant diseases in time series. This research can help farmers, researchers, experts or agencies in the field of agriculture to identify common diseases of pepper, so that it can provide basic knowledge about various types of diseases and treatment solutions to support the growth of pepper plants.
Downloads
References
M. Bhagat, D. Kumar, R. Mahmood, B. Pati, and M. Kumar, “Bell pepper leaf disease classification using CNN,” 2nd Int. Conf. Data, Eng. Appl. IDEA 2020, 2020.
F. Jobin, S. D. Anto, and B. K. Anoop, “Pepper Plants Using Soft Computing Techniques,” 2016.
S. A. Pasaribu, P. Sihombing, and S. Suherman, “Expert System for Diagnosing Dental and Mouth Diseases with a Website-Based Certainty Factor (CF) Method,” Mecn. 2020 - Int. Conf. Mech. Electron. Comput. Ind. Technol., pp. 218–221, 2020.
Y. Wu, “Rule-based Expert System for Chinese Patent Law,” pp. 191–195, 2020.
M. B, “Implementasi Sistem Pakar Dalam Mendiagnosis Penyakit Mata Menggunakan Metode Backward Chaining Dan Demster Shafer,” Metik, vol. 1, no. 2, pp. 34–40, 2017.
R. N. Pranata, A. B. Osmond, and C. Setianingsih, “Potential level detection of skin cancer with expert system using forward chaining and certainty factor method,” Proc. - 2018 IEEE Int. Conf. Internet Things Intell. Syst. IOTAIS 2018, pp. 207–213, 2019.
Nunsina, Tulus, and Z. Situmorang, “Analysis Optimization K-Nearest Neighbor Algorithm with Certainty Factor in Determining Student Career,” Mecn. 2020 - Int. Conf. Mech. Electron. Comput. Ind. Technol., pp. 306–310, 2020.
J. A. Widians, N. Puspitasari, and A. Febriansyah, “Disease Diagnosis System Using Certainty Factor,” ICEEIE 2019 - Int. Conf. Electr. Electron. Inf. Eng. Emerg. Innov. Technol. Sustain. Futur., pp. 303–308, 2019.
G. Konstantinopoulou, K. Kovas, I. Hatzilygeroudis, and J. Prentzas, “An Approach using Certainty Factor Rules for Aphasia Diagnosis,” 10th Int. Conf. Information, Intell. Syst. Appl. IISA 2019, pp. 1–7, 2019.
W. Yulianti, D. Arisandi, and A. Syaf, “Comparison of the effectiveness of certainty factor vs dempster-shafer in the determination of the adolescent learning styles,” Proc. - 2018 2nd Int. Conf. Electr. Eng. Informatics Towar. Most Effic. W. Mak. Deal. with Futur. Electr. Power Syst. Big Data Anal. ICon EEI 2018, no. October, pp. 46–50, 2018.
Hairani, M. N. Abdillah, and M. Innuddin, “An Expert System for Diagnosis of Rheumatic Disease Types Using Forward Chaining Inference and Certainty Factor Method,” Proc. 2019 4th Int. Conf. Sustain. Inf. Eng. Technol. SIET 2019, pp. 104–109, 2019.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Muslimin B, Putu Sugiartawan
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright in each article belongs to the author.
- The authors admit that SINTECH Journal as a publisher who published the first time under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.
- Authors can include writing separately, regulate distribution of non-ekskulif of manuscripts that have been published in this journal into another version (eg sent to respository institution author, publication into a book, etc.), by recognizing that the manuscripts have been published for the first time in SINTECH Journal