Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2020
Prediksi Rating Aplikasi Playstore Menggunakan Xgboost
Dublin Core
Title
Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2020
Prediksi Rating Aplikasi Playstore Menggunakan Xgboost
Prediksi Rating Aplikasi Playstore Menggunakan Xgboost
Subject
playstore, rating aplikasi, XGBoost
playstore, application rating, XGBoost
playstore, application rating, XGBoost
Description
Masyarakat mempunyai kebiasaan berinteraksi dengan smartphone. Aplikasi yang tersedia pada platform plasytore berjumlah banyak. Jenis yang bermacam-macam membuat masyarakat menjadi lebih selektif terhadap pemilihan penggunaan aplikasi. Aplikasi yang mempunyai rating tinggi biasanya dibarengi dengan jumlah user. Developer aplikasi perlu mencari cara untuk melakukan prediksi rating terhadap aplikasi yang akan di publish di plasystore untuk tetap menjaga performa pelayanan. Oleh karena itu penelitian in melakukan Analisa terhadap dataset rincian aplikasi playstore yang tersedia secara publik di Kaggle. Analisa dilakukan dengan berbagai tahapan yakni dataset collection, data preprocessing, data modelling. Penelitian ini berhasil menggunakan algoritma XGBoost untuk melakukan prediksi rating aplikasi playsotre dengan tingkat akurasi mencapai 77,5%.
People have a habit of interacting with smartphones. There are many applications available on the plasytore platform. Various types make people more selective in choosing the use of applications. Applications that have a high rating are usually accompanied by a number of users. Application developers need to find ways to predict the ratings of applications that will be published on the Plasystore to maintain service performance. Therefore, this research conducted an analysis of the detailed dataset of the playstore application that is publicly available in Kaggle. The analysis was carried out in various stages, namely dataset collection, data preprocessing, data modeling. This research is successful in using the XGBoost algorithm to predict the rating of the playsotre application with an accuracy rate of 77.5%.
People have a habit of interacting with smartphones. There are many applications available on the plasytore platform. Various types make people more selective in choosing the use of applications. Applications that have a high rating are usually accompanied by a number of users. Application developers need to find ways to predict the ratings of applications that will be published on the Plasystore to maintain service performance. Therefore, this research conducted an analysis of the detailed dataset of the playstore application that is publicly available in Kaggle. The analysis was carried out in various stages, namely dataset collection, data preprocessing, data modeling. This research is successful in using the XGBoost algorithm to predict the rating of the playsotre application with an accuracy rate of 77.5%.
Creator
Dwika Ananda Agustina Pertiwi, Tanzilal Mustaqim, Much Aziz Muslim
Publisher
Universitas Semarang
Date
27 Oktober 2020
Contributor
Sri Wahyuni
Rights
ISSN: 2614-1205
Format
PDF
Language
Indonesian
Type
Text
Coverage
Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2020
Files
Citation
Dwika Ananda Agustina Pertiwi, Tanzilal Mustaqim, Much Aziz Muslim
, “Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2020
Prediksi Rating Aplikasi Playstore Menggunakan Xgboost,” Repository Horizon University Indonesia, accessed April 19, 2025, https://repository.horizon.ac.id/items/show/3481.
Prediksi Rating Aplikasi Playstore Menggunakan Xgboost,” Repository Horizon University Indonesia, accessed April 19, 2025, https://repository.horizon.ac.id/items/show/3481.