SENTIMENT ANALYSIS OF COFFEE SHOP REVIEWS USING RANDOM FOREST CLASSIFIER METHOD

Authors

  • Berliana Nur Isnayni 3Department of Informatics, Universitas PGRI Yogyakarta
  • Nurirwan Saputra Department of Informatics, Universitas PGRI Yogyakarta
  • Tri Hastono Department of Informatics, Universitas PGRI Yogyakarta, Indonesia

DOI:

https://doi.org/10.61677/jth.v2i2.152

Keywords:

Sentiment analysis, coffee shop, random forest

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%.

References

Amaliah, S., & Nusrang, M. (2022). Penerapan Metode Random Forest Untuk Klasifikasi Varian Minuman Kopi Di Kedai Kopi Konijiwa Bantaeng. 4(2), 121–127. https://doi.org/10.35580/variansiunm31

Azhar, N., Adikara, P. P., Adinugroho, S., Studi, P., Informatika, T., Komputer, F. I., Brawijaya, U., & Korespondensi, P. (2021). SENTIMENT ANALYSIS FOR COFFEE SHOP REVIEWS USING NAÏVE BAYES. 8(3), 609–618. https://doi.org/10.25126/jtiik.202184436

Bano, N. J., Sukwadi, R., & Park, A. (2022). Analisis Perbaikan Kualitas Layanan Bluemoon Container Café: Model Integrasi Analisis Sentimen dan Quality Function Deployment. Jurnal INTECH Teknik Industri Universitas Serang Raya, 8(1), 75–82. https://doi.org/10.30656/intech.v8i1.4569

Elbagir, S., & Yang, J. (2019). Language Toolkit and VADER Sentiment. Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS), 0958, 12–16.

Habibi, M., & Cahyo, P. W. (2019). Clustering User Characteristics Based on the influence of Hashtags on the Instagram Platform. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 13(4), 399. https://doi.org/10.22146/ijccs.50574

Saputra, N., Nurbagja, K., & Turiyan, T. (2022). Sentiment Analysis of Presidential Candidates Anies Baswedan and Ganjar Pranowo Using Naïve Bayes Method. JURNAL SISFOTEK GLOBAL, 12(2), 114. https://doi.org/10.38101/sisfotek.v12i2.552

Wiraguna, A., Faraby, S. Al, & Adiwijaya. (2019). Klasifikasi Topik Multi Label pada Hadis Bukhari dalam Terjemahan Bahasa Indonesia Menggunakan Random Forest. E-Proceeding of Engineering, 6(1), 2144–2153. https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/8507%0Ahttps://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/download/8507/8377

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Published

2024-05-10 — Updated on 2024-05-12

How to Cite

Berliana Nur Isnayni, Nurirwan Saputra, & Tri Hastono. (2024). SENTIMENT ANALYSIS OF COFFEE SHOP REVIEWS USING RANDOM FOREST CLASSIFIER METHOD. JTH: Journal of Technology and Health, 1(4), 233 ~ 244. https://doi.org/10.61677/jth.v2i2.152

Issue

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

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Articles

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