The Clustering Rice Plant Diseases Using Fuzzy C-Means and Genetic
Algorithm

The Clustering Rice Plant Diseases Using Fuzzy C-Means and Genetic
Algorithm

Clustering, Fuzzy C-Means, Genetic Algorithm, Image Processing, Rice Plants Diseases

Rice is an agricultural sector that is very important for Indonesia's economy. The main problem with rice plants is pest and
disease control which has a very dangerous impact as well as economic losses for farmers. The characteristics that are very
visible on rice leaves have a greater area than other plant structures, rice leaves can be applied for early diagnosis of rice
plant diseases. Fuzzy C-Means (FCM) and Genetic Algorithm-Fuzzy C-Means are the approaches employed (GA-FCM). The
center of the cluster is obtained while adopting genetic algorithms for optimization. The primary dataset used in this research
is Teaching Sawah Farm IPB, and the secondary dataset is UCI Rice Leaf Diseases. According to the results of the comparison
the GA-FCM optimization results in a higher level of clustering precision with a 65% optimal cluster center point on the
silhoutte coefficient value compared to just 60% for FCM. This research shows the results that the proposed method can add
5% accuracy to the clustering results in terms of identifying the types of rice plant diseases properly

Faza Adhzima1
, Yandra Arkeman2
, Irman Hermadi

IPB University

20-04-2022

Fajar agus W

PDF

Indonesia

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