Fitur Esktraksi LBP dan Naive Bayes dalam Klasifikasi Jenis Pepaya Berdasarkan Citra Daun

Abstract

Abstrak Tanaman merupakan bagian terpenting dalam kehidupan makhluk hidup sebagai oksigen untuk bernafas, selain itu juga digunakan sumber makanan, bahan bakar, obat-obatan dan masih banyak lagi manfaatnya. Salah satunya tanaman buah pepaya, bisa digunakan untuk bahan makanan maupun obat-obatan. Tanaman buah pepaya ini memiliki banyak jenis dan bisa diklasifikasikan berdasarkan bentuk daunnya. Jenis daun buah papaya yang digunakan dalam penelitian ini, yaitu : daun buah pepaya Sumatera, daun buah pepaya California, daun buah pepaya Hawai, daun buah pepaya cibinong dan daun buah pepaya Bangkok. Abstract Plants are the most important part in the life of living things as oxygen for breathing, besides that they are also used as a source of food, fuel, medicine and many other benefits. One of them is papaya fruit plants, which can be used for food and medicine. This papaya fruit plant has many types and can be classified based on the shape of the leaves. The types of papaya leaves used in this study, namely: Sumatran papaya leaves, California papaya leaves, Hawaiian papaya leaves, Cibinong papaya leaves and Bangkok papaya leaves. The number of datasets used is 150 images and will be divided into 5 classes consisting of 25 training data and 5 testing data for each class. This classification process uses the Local Binary Pattern method for feature extraction and the Naïve Bayes Classifier method as the classification method. The Local Binary Pattern operator method is simple and efficient to describe local image patterns and get good results in shooting textures. Meanwhile, the Naïve Bayes Classifier method is the simplest method using existing opportunities, where it assumes that each variable is independent. Based on the results of the tests carried out, the use of the Naïve Bayes Classifier coupled with the extraction of the Local Binary Pattern feature obtained an accuracy value of 96% in the first experiment and 93% in the second experiment.