Implementasi Metode Lexicon-Based dalam Menganalisis Sentimen Ulasan Pengguna Aplikasi di Google PlayStore melalui Platform Analitik Appsentix.com : Studi Kasus Aplikasi Netflix

RAMADHAN, ADE GUNTUR (2024) Implementasi Metode Lexicon-Based dalam Menganalisis Sentimen Ulasan Pengguna Aplikasi di Google PlayStore melalui Platform Analitik Appsentix.com : Studi Kasus Aplikasi Netflix. S1 thesis, Universitas Mercu Buana-Menteng.

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Abstract

Penelitian ini bertujuan mengimplementasikan metode Lexicon-Based untuk menganalisis sentimen ulasan pengguna aplikasi Netflix di Google PlayStore melalui platform analitik Appsentix.com. Variabel yang diteliti mencakup komentar atau ulasan pengguna terkait dengan kepuasan, kualitas aplikasi, dan masalah yang dihadapi oleh pengguna. Untuk mencapai tujuan ini, kami menjalankan serangkaian langkah sebagai berikut: (1) Pengumpulan data ulasan aplikasi Netflix dari Google PlayStore sebagai studi kasus, (2) Data ulasan yang berhasil dikumpulkan diubah ke dalam format CSV dan diunggah ke platform Appsentix.com untuk pengolahan lebih lanjut, (3) Selanjutnya, kami mengembangkan script di backend Appsentix.com untuk menerapkan metode Lexicon-Based dengan menggunakan alat analisis sentiment VADER (Valence Aware Dictionary and sEntiment Reasoner), (4) Hasil analisis sentimen dari setiap metode dipresentasikan dalam bentuk grafik pada antarmuka pengguna Appsentix.com. Grafik-grafik ini memberikan informasi tentang tingkat sentimen positif, negatif, dan netral yang terdapat dalam ulasan pengguna. Dalam penelitian ini, kami menjadikan Netflix sebagai studi kasus awal, tetapi fokus utama kami adalah untuk memungkinkan metode ini diterapkan pada seluruh aplikasi yang tersedia di Google PlayStore melalui platform Appsentix.com. Langkah-langkah yang kami ambil diharapkan dapat memberikan wawasan berharga kepada pengembang aplikasi dan pengguna Appsentix.com agar mereka dapat lebih memahami umpan balik pengguna, serta mengambil tindakan yang tepat untuk meningkatkan pengalaman pengguna dan kualitas aplikasi mereka. This research aims to implement the Lexicon-Based method for analyzing user sentiment in reviews of the Netflix application on Google PlayStore through the analytical platform Appsentix.com. The variables under investigation include user comments or reviews related to satisfaction, app quality, and issues faced by users. To attain this objective, we executed a sequence of actions as outlined below: (1) Collecting Netflix application review data from Google PlayStore as a case study, (2) Converting the collected review data into CSV format and uploading it to the Appsentix.com platform for further processing, (3) Following that, we created a backend script for Appsentix.com to implement the Lexicon-Based approach, utilizing the VADER (Valence Aware Dictionary and Sentiment Reasoner) sentiment analysis tool. (4) The outcomes of sentiment analysis using each method are displayed graphically on the interface of Appsentix.com. These graphics provide information about the levels of positive, negative, and neutral sentiment found in user reviews. In this research, we used Netflix as an initial case study, but our primary focus is to enable the application of this method to all applications available on Google PlayStore through the Appsentix.com platform. We anticipate that the measures we've implemented will offer valuable insights to app developers and users of Appsentix.com, enabling them to gain a deeper understanding of user feedback and make informed decisions to improve user experiences and application quality.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41520120037
Uncontrolled Keywords: analisis sentiment, lexicon based, Netflix, Appsentix.com sentiment analysis, lexicon based, Netflix, Appsentix.com
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: WIDYA AYU PUSPITA NINGRUM
Date Deposited: 09 Jul 2024 04:27
Last Modified: 09 Jul 2024 04:27
URI: http://repository.mercubuana.ac.id/id/eprint/89416

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