dc.contributor.advisor | Masjkur, Mohammad | |
dc.contributor.advisor | Indahwati | |
dc.contributor.author | Putri, Dea Fisyahri Akhilah | |
dc.date.accessioned | 2023-01-02T05:38:05Z | |
dc.date.available | 2023-01-02T05:38:05Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/115813 | |
dc.description.abstract | Online food delivery merupakan salah satu pendorong pertumbuhan ekonomi
digital yang semakin digemari masyarakat saat ini. Tren penggunaan layanan ini
semakin meningkat seiring terjadinya perubahan perilaku dan gaya hidup
masyarakat sebagai adaptasi pandemi Covid-19. Mayoritas platform digital layanan
pesan-antar makanan di Indonesia yang sering digunakan, seperti GoFood,
ShopeeFood, dan GrabFood yang memberikan kemudahan dalam bertransaksi
dengan berbagai pilihan bagi konsumen. Peningkatan penggunaan layanan ini
memunculkan beragam ulasan dan opini publik, salah satunya melalui cuitan di
twitter. Penelitian ini bertujuan melakukan analisis sentimen terhadap ulasan
pengguna layanan online food delivery menggunakan algoritma Bernoulli Naïve
Bayes dengan membagi sentimen menjadi kelas positif dan negatif. Mayoritas
ulasan pada periode 15 Maret 2022 hingga 30 Maret 2022 ini termasuk dalam
sentimen positif yang mengindikasikan bahwa masyarakat memberikan kesan
positif selama menggunakan layanan online food delivery. Hasil penelitian ini
menunjukkan pemodelan Bernoulli Naïve Bayes dengan seleksi fitur information
gain menghasilkan performa yang cukup baik dalam mengklasifikasikan label
sentimen dengan nilai akurasi yang didapatkan sebesar 89%, 87%, 86%, dan 85%
untuk seluruh data maupun setiap platform GoFood, ShopeeFood, dan GrabFood. | id |
dc.description.abstract | Online food delivery is one of the drivers of the digital economy that all
societies today are interested in. The trend of these services has intensified as
changes in people's behavior and lifestyle in the Covid-19 pandemic. The digital
platforms of food delivery services in Indonesia are GoFood, ShopeeFood, and
GrabFood, present ease in both competitive transactions and multiple options by
consumers. Its widespread use of these platforms certainly generates a variety of
reviews and public opinion; one is through tweets on Twitter. This study aims to
classify the sentiments on the various reviews into the label of positive and negative
sentiments using the Bernoulli Naïve Bayes algorithm. The majority of reviews
from March 15, 2022 to March 30, 2022 were positive sentiments, which indicated
that people gave a positive impression during these online food delivery service.
The results of this study show that Bernoulli Naïve Bayes with the feature selection
of information gain generates a good performance in classifying sentiment labels
based on accuracy scores obtained at 89%, 87%, 86%, and 85% in all data and each
online food delivery platform (GoFood, ShopeeFood, and GrabFood). | id |
dc.language.iso | id | id |
dc.publisher | IPB University | id |
dc.title | Penerapan Bernoulli Naïve Bayes untuk Analisis Sentimen Pengguna Twitter Terhadap Layanan Online Food Delivery di Indonesia | id |
dc.title.alternative | Application of Bernoulli Naïve Bayes for Twitter User’s Sentiment Analysis Towards Online Food Delivery Service in Indonesia | id |
dc.type | Undergraduate Thesis | id |
dc.subject.keyword | Bernoulli Naïve Bayes | id |
dc.subject.keyword | information gain | id |
dc.subject.keyword | online food delivery | id |
dc.subject.keyword | sentiment analysis | id |
dc.subject.keyword | Twitter | id |