JTH: Journal of Technology and Health
Vol. 1 No. 4 (2024): April: JTH: Journal of Technology and Health

SENTIMENT ANALYSIS OF COFFEE SHOP REVIEWS USING RANDOM FOREST CLASSIFIER METHOD

Berliana Nur Isnayni (Unknown)
Nurirwan Saputra (Unknown)
Tri Hastono (Unknown)



Article Info

Publish Date
12 May 2024

Abstract

A Coffee shop is a place that serves drinks made from processed coffee grains, various drinks and various snacks to accompany coffee to consumers. Coffee shop reviews can help owners to find out how the community responds to the coffee shop and its services. The data used in this study was 2000 data taken on the old Google Maps Kopi Ampirono by sraping data using Instant Data Sraper. From the abundance of review data, it takes a long time to fully understand the polarity of positive, negative, and neutral reviews manually. Because of this, an accurate sentiment analysis model is needed to classify customer reviews into positive, negative, or neutral reviews. In this study, sentiment analysis used coffee shop reviews using the Random Forest Classifier method. The Preprocessing stage involves the process of case folding, tokenization, stopword removal and stemming. The results of this study are coffee shop reviews of the Random Forest Classifier method classification with an accuracy rate of 79% and a Precision value of 81%, Recall of 97% and while the F1 Score of 88%.

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Journal Info

Abbrev

jth

Publisher

Subject

Health Professions Medicine & Pharmacology Nursing

Description

The journal publishes writings on: Electrical Engineering such as: Signal Processing, Electronics, Electrical, Telecommunication, Instrumentation & Control, and Computing and Informatics. Automotive Engineering and Automotive Vocational Education such as: Automotive Engines (Petrol, Diesel, ...