Analisis Sentimen Pada Data Ulasan Aplikasi Bareksa, Bibit Dan Tanamduit Menggunakan Metode Naive Bayes Classifier

Rachmadewi, Sindu Adelia Ayu (2021) Analisis Sentimen Pada Data Ulasan Aplikasi Bareksa, Bibit Dan Tanamduit Menggunakan Metode Naive Bayes Classifier. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Perkembangan literasi keuangan di Indonesia semakin meningkat dari tahun ke tahun. Instrumen pasar modal yang mengalami peningkatan paling tinggi adalah reksa dana. Hal tersebut tentu berdampak bagi industri teknologi finansial di Indonesia. Beberapa start-up teknologi finansial berlisensi di Indonesia adalah PT Bareksa Portal Inveastasi dengan aplikasi bernama Bareksa, PT Bibit Tumbuh Bersama dengan aplikasi bernama Bibit dan PT Star Mercato Capitale dengan aplikasi bernama Tanamduit yang baru berdiri beberapa tahun terakhir. Sebagai perusahaan start-up yang baru berdiri, citra dan reputasi yang baik dari masyarakat adalah sesuatu yang sangat penting. Evaluasi berkala juga diperlukan untuk menjaga kualitas jasa yang diberikan kepada pelanggan. Oleh karena itu, perlu dilakukan penelitian analisis sentimen pada data ulasan aplikasi bibit di google play store untuk mengetahui sentimen masyarakat terhadap aplikasi tersebut dan untuk membandingkan aplikasi yang memiliki sentimen paling baik di antara ketiga aplikasi tersebut. Penelitian dilakukan dengan menggunakan metode Naïve Bayes Classifier. Dari ketiga aplikasi, aplikasi bareksa merupakan aplikasi yang memiliki sentiment positif paling tinggi disbandingkan yang lain dan ketepatan klasifikasi yang lebih tinggi dibandingkan dengan yang lain yaitu sebesar 72,45%.
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The development of financial literacy in Indonesia is increasing from year to year. The capital market instruments that have increased the most are mutual funds. This certainly has an impact on the financial technology industry in Indonesia. Some licensed financial technology start-ups in Indonesia are PT Bareksa Portal Inveastasi with an application called Bareksa, PT Bibit Tumbuh Bersama with an application called Bibit and PT Star Mercato Capitale with an application called Tanamduit which has only been established in recent years. As a newly established start-up company, the image and good reputation of the community is something very important. Periodic evaluation is also needed to maintain the quality of services provided to customers. Therefore, it is necessary to conduct sentiment analysis research on seed app review data in google play store to know people's sentiment towards the app and to compare the apps that have the best sentiment among the three apps. The research was conducted using the Naïve Bayes Classifier method. Of the three applications, bareksa application is the application that has the highest positive sentiment compared to others and higher classification accuracy compared to others which is 72.45%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Analisis Sentimen, Naïve Bayes Clasiffer, Naïve Bayes Classifier, Sentiment Analysis
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HD Industries. Land use. Labor > HD108 Classification (Theory. Method. Relation to other subjects ) Q Science
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Sindu Adelia Ayu Rachmadewi
Date Deposited:	26 Aug 2021 03:27
Last Modified:	26 Aug 2021 03:33
URI:	http://repository.its.ac.id/id/eprint/87541

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