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

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 pla...

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Bibliographic Details
Main Author: Rano Agustino
Format: Article
Language:English
Published: LPPM Universitas Mohammad Husni Thamrin 2019-03-01
Series:Jurnal Teknologi Informatika & Komputer
Online Access:https://journal.thamrin.ac.id/index.php/jtik/article/view/220
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Summary: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
ISSN:2656-9957
2622-8475