Tugas Metode Penelitian dengan judul
"Perbandingan Model Convolutional Neural Network(CNN) dan Model Support Vector Machine(SVM) untuk Mendeteksi Penyakit Daun Mangga".
Saya mengambil Data set dari Kaggle
Menggunakan Python library CNN
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import Adam, Adamax
from tensorflow.keras.metrics import categorical_crossentropy
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Activation, Dropout, BatchNormalization
from tensorflow.keras import regularizersMenggunakan Python Library SVM
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import OneHotEncoderData set yang di training
Class Anthracnose: 348 samples
Class Bacterial Canker: 354 samples
Class Cutting Weevil: 322 samples
Class Die Back: 343 samples
Class Gall Midge: 350 samples
Class Healthy: 353 samples
Class Powdery Mildew: 365 samples
Class Sooty Mould: 365 samplesData set yang di Valid
Class Anthracnose: 78 samples
Class Bacterial Canker: 67 samples
Class Cutting Weevil: 95 samples
Class Die Back: 84 samples
Class Gall Midge: 75 samples
Class Healthy: 70 samples
Class Powdery Mildew: 70 samples
Class Sooty Mould: 61 samples
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