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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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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author Rano Agustino
author_facet Rano Agustino
author_sort Rano Agustino
collection DOAJ
description 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
format Article
id doaj-art-3801feecbcef4d2095f9c909993fc0aa
institution Kabale University
issn 2656-9957
2622-8475
language English
publishDate 2019-03-01
publisher LPPM Universitas Mohammad Husni Thamrin
record_format Article
series Jurnal Teknologi Informatika & Komputer
spelling doaj-art-3801feecbcef4d2095f9c909993fc0aa2025-08-20T03:50:12ZengLPPM Universitas Mohammad Husni ThamrinJurnal Teknologi Informatika & Komputer2656-99572622-84752019-03-0151242810.37012/jtik.v5i1.220174Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di BioskopRano Agustino0Universitas Mohammad Husni ThamrinIn 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 Curvehttps://journal.thamrin.ac.id/index.php/jtik/article/view/220
spellingShingle Rano Agustino
Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop
Jurnal Teknologi Informatika & Komputer
title Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop
title_full Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop
title_fullStr Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop
title_full_unstemmed Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop
title_short Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop
title_sort komparasi algoritma klasifikasi dengan menggunakan anaconda untuk memprediksi ramai penonton film di bioskop
url https://journal.thamrin.ac.id/index.php/jtik/article/view/220
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