CD Skripsi

Implementasi Text Mining Dengan Random Forest Untuk Analisis Sentimen Ulasan Pengguna Aplikasi Alodokter Di Google Play Store

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ABSTRACT
During the COVID-19 pandemic, most people relied on the internet to find information, including health information. The process of digitizing the world of health, especially during a pandemic, was actually enough to help people get their right to health. The existence of digital health applications certainly will not replace the function of doctors and medical personnel in the world of health. Alodokter is a health platform in Indonesia. Alodokter application users can provide reviews of these application services through the review feature on the Google Play Store. The existence of this feature is one of the considerations for prospective users to download applications and can be used as an evaluation to improve application performance. Therefore, it is necessary to carry out a sentiment analysis to see an overview of the perceptions of Alodokter application users on the Google Play Store. In this study, data collection was carried out using web scraping techniques using Google Colab. The data used is user review data after it was determined that COVID-19 entered Indonesia, namely from March 2020 to May 2020 with a total of 13,225 review data. The method used in this study is Random Forest, this method produces classification accuracy performance with an accuracy rate of 96.9% as measured using the Confusion Matrix. Based on the accuracy value, it can be seen that Random Forest has good performance in processing big data.
Keywords: Sentiment Analysis, Alodokter Application, Random Forest

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1803123903

Penerbit

Pekanbaru : Universitas Riau - FMIPA - Sistem Informasi., 2022

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1803123903

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Deti

Versi lain/terkait

Lampiran Berkas

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