Klasifikasi Tanaman Terong Sehat Dan Sakit Berdasarkan Citra Daun Menggunakan Metode K-Nearest Neighbors

ARAUJO, Joao Paulo Resi Wae (2024) Klasifikasi Tanaman Terong Sehat Dan Sakit Berdasarkan Citra Daun Menggunakan Metode K-Nearest Neighbors. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

Eggplant (Solanum melongena L.) is a horticultural commodity that is quite popular among Indonesian people at large. Eggplant is a type of vegetable that can produce up to two years and has quite high productivity values. Because of this, eggplant is a type of vegetable that has promising prospects. The relatively stable price of eggplant can be a consideration for widespread cultivation. However, the production of eggplant plants began to decline due to attacks by pests and diseases. Classification is a data mining method that functions to categorize data into different classes. This research aims to detect disease in eggplant plants based on classifier-based leaf images. In this classification process, the K-Nearest Neighbors algorithm is used with the help of the Orange Data Mining Tool as a tool to carry out the data mining process in classifying images of healthy and sick eggplant leaves. This research used 1000 datasets of healthy and sick eggplant leaves that were collected, where the dataset was divided into 2 classes, namely healthy eggplant leaves and sick eggplant leaves. Classification was carried out using the K-fold cross validation method using a number of fold 2, 3, 5, 10, 20. The results obtained from the classification process with the greatest accuracy were 83.6% using a number of fold 5, which means the K-NN method able to classify eggplant leaves as healthy and accurately.

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