Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop

Abstract

In the interest of Moviegoers with trendy films,
cinemas also play a major role in attracting audiences to
watch films they like. But changes that are quite dynamic
from audience interest take turns, sometimes it is
sometimes not crowded. Thus sometimes the cinema
manager experiences an error in placing the film to be
aired, so the number of viewers in the cinema is not as
expected. From this problem, researchers are interested in
analyzing data relating to film audiences in the cinema.
By using CART classification, NBC (Naive Bayes
Classifier) algorithm, SVM (Support Vector Machine), LR
(Logis Text Regression) and LDA (Linear Discriminant
Analysis) which will be compared which accuracy is the
best for predicting the absence or absence of the
audience. Researchers use Anaconda to compare six
algorithms and will see the highest results from the
Confusion Matrix and ROC Curve