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All Journal Bulletin of Multi-Disciplinary Science and Applied Technology
Hidayatullah Hidayatullah
STMIK Kaputama, Binjai
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Other

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Sistem Pakar Diagnosa Penyakit Kelapa Sawit Dengan Menggunakan Metode Certainty Factor Hidayatullah Hidayatullah; Budi Serasi Ginting; Achmad Fauzi
Bulletin of Multi-Disciplinary Science and Applied Technology Vol 1 No 5 (2022): Agustus 2022
Publisher : Forum Kerja Sama Penddikan Tinggi (FKPT)

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Abstract

Computer development is very important in information notification and data processing, computer development can also play a role in analyzing the symptoms of problems that occur. Oil palm plantations are currently growing in Indonesia and almost all of oil palm is grown throughout the archipelago. Oil palm plants are very beneficial for humans because oil palm fruit as a palm oil-producing plant and palm kernel is one of the prima donna of plantation crops which is a source of non-oil and gas foreign exchange for Indonesia. Because of the importance of oil palm resulting in increased production. However, there is an imbalance in the production of oil palm fruit due to the lack of understanding of the farmers to overcome the diseases that attack oil palm plants. It takes an expert system that will incorporate all expert knowledge in a system so that it can diagnose diseases in oil palm anytime and anywhere. The Certainty factor (CF) method is a method to prove whether a fact is certain or uncertain in the form of a metric that is usually used in expert systems. This method is very suitable for expert systems that diagnose something that is not certain. Based on the results of the CF calculation, the highest value was in the type of palm root rot disease with a value of 97.29%. From the results obtained, the system diagnoses the oil palm tree diagnosed with palm root rot disease.
Co-Authors Budi Serasi Ginting Fauzi, Achmad