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Sistem Pakar Diagnosis Hama-Penyakit Pada Tanaman Sedap Malam Menggunakan Metode Naive Bayes-Certainty Factor Berbasis Android Ali Syahrawardi; Nurul Hidayat; Donald Sihombing
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sedap malam are one of the most popular decorative plants in Indonesia, sedap malam flower's mostly used by Indonesia in many ways such as for flowers of sow, decorative stuff and cosmetic material, because it contains essential oils. In Indonesia, many Indonesian people started to cultivate sedap malam. Sedap malam are mostly cultivated in Bangil and Rembang sub-districts of Pasuruan Regency, as well as other areas such as Banyuwangi, Cianjur, and Magelang. However, sedap malam production levels is still low because of the seeds used are still arbitrary and pest and disease attacks, resulting in an impact on productivity and quality of interest. Nowadays we are lacking amount of the expert systems of sedap malam that is needed to replace the experts to diagnose the pests that cause diseases of sedap malam. This research implements the expert system that can diagnose the pests cause some diseases on sedap malam using Naive Bayes-Certainty Factor method. Based on trials, by using Naive Bayes-Certainty Factor method, the calculation accuracy of the diagnose is good and accurate. The outcome of the calculation of this method is 86,67% and the system level of satisfication is 3,255823.