KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Vol. 9 No. 3 (2023): Kalbisiana

Pengembangan Aplikasi Analisis Sentimen Aplikasi PeduliLindungi Menggunakan Metode Naïve Bayes

Edsel Jayadi (INSTITUT TEKNOLOGI DAN BISNIS KALBIS)

Article Info

Publish Date
23 Oct 2023

Abstract

This study aims to build sentiment analysis application using Naïve Bayes method to analyze public view about an application called PeduliLindungi, and measure it’s accuracy by using twitter dataset. PeduliLindungi is an application developed by the government in order to track and stop Coronavirus Disease (COVID-19). The dataset used in this study is collected by using crawling method with Tweepy. Collected dataset will then go through data pre-processing and labeled by using VADER in order to separate it into positive and negative sentiments. The data will be weighted based on the frequency of its occurrence in all tweets using the TF-IDF method. The weighted data will then be classified using the Naïve Bayes method. This research used the incremental method both in model and software development. The results obtained in this study is a model with an accuracy score of 85% and an average precision, recall, and f1-score of 85%.

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Journal Info
KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Website

Abbrev

kalbisiana

Publisher

UNIVERSITAS KALBIS

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

Description

KALBISIANA Jurnal Sains, Bisnis dan Teknologi adalah jurnal akses terbuka akademik yang bertujuan untuk mempromosikan integrasi sains, bisnis dan teknologi. Fokusnya adalah menerbitkan makalah tentang sains, bisnis dan teknologi. Makalah yang dikirimkan akan ditinjau oleh komite teknis jurnal. Semua ...