Klasifikasi Citra Burung Lovebird Menggunakan Decision Tree dengan
Empat Jenis Evaluasi

Klasifikasi Citra Burung Lovebird Menggunakan Decision Tree dengan
Empat Jenis Evaluasi

Lovebird, ANN, Decision Tree, Precision, Recall, F-measure.

Lovebird is a pet that many people in Indonesia have known. The diversity of species, coat color, and body shape gives it its
charm. As well in this lovebird bird has its uniqueness of various rare colors. However, many ordinary people have difficulty
distinguishing the types of lovebirds. This research is needed to improve previous study performance in classifying lovebird
images using the Decision Tree J48 algorithm with 4 types of evaluation. In this case, also to reduce the stage of feature
extraction to speed up the computational process. Based on available comparisons, the results obtained at the same split ratio
with a comparison of 60:40 in Decision Tree J48 have the precision of 1,000, recall of 1,000, f-measure of 1,000, and accuracy
value of 100%. Then the Artificial Neural Network with a split ratio of 60:40 has a precision of 0.854, recall of 0.843, fmeasurement of 0.841, and an accuracy value of 84.25%. These results prove that by testing the first-level extraction on color
features, Decision Tree J48 is superior in classifying images of lovebird species, and Decision Tree J48 can improve
performance and produce the best accuracy

Aviv Yuniar Rahman

Universitas Widyagama Malang

20-08-2021

Fajar bagus W

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Indonesia

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