Sistem Diagnosis Penyakit Bulai Pada Jagung Menggunakan Metode Fuzzy Tsukamoto

Hema Prasetya Antar Nusa (Fakultas Ilmu Komputer, Universitas Brawijaya)
Nurul Hidayat (Fakultas Ilmu Komputer, Universitas Brawijaya)
Ratih Kartika Dewi (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 3 No 7 (2019): Juli 2019

Bulai disease disease that infects of a corn plant and sorghum .Bulai caused by fungi peronosclerospora spp. Bulai disease caused by fungi peronosclerospora spp .Is one of the problems that have frequently afflicted by grower of corn , not only in indonesia but also all over the world. In indonesia bulai disease causing loss of field 50-80 %.Even in south sulawesi, bulai disease can result in loss of the reached 90 %. Climate factors as humidity and air temperature significantly impacted on the development of peronosclerospora spp . Especially on the wetness in over 80 % and temperature 28- 30°C and the existence of dew. But many farmers are still experience crop failure because of the trees did not notice that the trees were infected by bulai or late know if their plants bulai and do not know how to handle bulai .Hence there is a need for the tools to diagnose a disease of plants bulai early. data onBased on the background detailed, in this study author choose a method of fuzzy tsukamoto to build a system in diagnosing disease bulai in corn. uses the fuzzy tsukamoto”. The data used in the application is the data on symptoms of disease of bulai. in cornThe output of application be diagnosis information detected disease bulai in corn or not. The results of the system in the form of output for it easy for users in knowing about of illnesses suffered by the. The fuzzy tsukamoto to research it uses rule and degrees membership dissimilar to any symptoms depend on the maximum and minimum membership than degrees set user and the best result obtained when the inputan are at the limit below the value minimal or above the maximum. The result of reckoning or accuracy of value system as much as 88,33 % accuracy.tsukamoto to research it uses rule and degrees membership dissimilar to any symptoms depend on the maximum and minimum membership than degrees set user and the best result obtained when the inputan are at the limit below the value minimal or above the maximum. The result of reckoning or accuracy of value system as much as 88,33 % accuracy.