CD Skripsi

Analisis Sentimen Terhadap Layanan Gofood Pada Masa Awal Dan Penurunan Pandemi Covid 19 Menggunakan Metode Naïve Bayes

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Coronavirus is a group of viruses that can infect both animals and humans.
Coronavirus usually causes respiratory tract infections in humans, ranging from
coughs, colds to Middle East Syndrome (MERS), and Severe Acute Respiratory
Syndrome (SARS). Many studies have been conducted to determine sentiment,
especially regarding the effect of delivery services during the COVID-19 period.
This study aims to compare the presentation of public sentiment regarding GoFood
services in the early days of the pandemic and the decline of COVID-19 and to
determine the level of accuracy in conducting sentiment analysis. This study used
the Naïve Bayes method which is useful for classifying data and used a Confusion
Matrix to see how well the accuracy level of the classification results is. In the
process of data classification is divided into two, positive and negative. The final
result of this research is that at the beginning of the pandemic, the sentiment was
in the form of a positive sentiment was 52% and a negative value was 48%. Then
during the pandemic decline, positive sentiment was 74% and a negative value was
26%. Based on this process, the accuracy rate at the beginning of the pandemic
was 82.67% and during the decline in the pandemic, the accuracy level was
70.58%. So analyzing sentiment data using the Naïve Bayes method achieved
satisfactory results.
Keywords: Confusion Matrix, COVID-19, Naïve Bayes, Text Mining.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1703114485

Penerbit

Pekanbaru : Universitas Riau –FMIPA–SISTEM INFORMASI., 2022

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1703114485

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

nadya

Versi lain/terkait

Lampiran Berkas

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