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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)
Yosef Alfredo Khawarga
Universitas Katolik Darma Cendika, Surabaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Prediksi Spesies Burung Menggunakan Random Forest Anisha Dwi Nur Fadlilah; Yulia Wahyuningsih; Yosef Alfredo Khawarga
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 6, No 1 (2022): Challenge and Opportunity For Z Generation in Metaverse Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v6i1.5783

Abstract

Randomforest is a supervised learning algorithm that uses ensemble learning methods for classification and regression. Random forest is a modeling using pocketing technique and not increasing technique. trees in random forests run in parallel. It operates by constructing multiple decision trees at the time of training and class output which is the mode of class (classification) or mean prediction (regression) of each tree. In this journal we will explain how to make a prediction about bird species using performance data from bird species for which we make predictions using the Random forest method and also using a confusion matrix. The first thing to do is to have a dataset of bird species. For the dataset, we will include it in the results and discussion. The results of this study show that the use of the random forest is good enough to predict bird species with output 45% for random forest, 26% for Decision Tree, and 48% for SVM, based on the characteristics and characteristics of each bird.
Co-Authors Anisha Dwi Nur Fadlilah Yulia Wahyuningsih