PENGGUNAAN METODE SUPPORT VECTOR MACHINE UNTUK KLASIFIKASI SENTIMEN E-WALLET

Article Sidebar

PDF
DOI: https://doi.org/10.24912/jiksi.v10i1.17824
Keywords:
Confussion Matrix Google Play Store preprocessing Support Vector Machine

Main Article Content

Bryan Filemon
Viny Christanti Mawardi
Novario Jaya Perdana

Abstract

In Google Play Store there are lots of application ready to be explored and downloaded. Google Play Store is a place where many developers can sell applications that they have made. Apart from being a place for searching and downloading applications, Google Play Store can also be used to conduct a research. E-Wallet is one of a technological development that can be used to do many transactions. Doing transaction with e-wallet can be done anywhere you want. E-wallet in Indonesia is growing very rapidly especially in the present time where covid-19 is growing rapidly. This is one of the reasons why many people now using e-wallet for doing transcations. Many interesting promotions that were given is also one of the reason why people start using e-wallet. This research had the objective to visualize  people’s emotion on e-wallet based on user opinion in Google Play Store. The research stage starts from scrapping data from Google Play Store, preprocessing data, classification with Support Vector Machine, evaluation with confusion matrix. Data were scrapped from google play store using google_play_scrapper API. This research uses OVO review of 500 data, DANA review of 500 data, LinkAja review of 500 data. The classification results will then be evaluated using a confusion matrix. The highest accuracy results will be used as a model for the classification stage. The classification results will be displayed in the form of tables and pie charts that describe the percentage results of sentiment classification.

Article Details

Issue
Vol. 10 No. 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Section
Articles

This work is licensed under a Jurnal Komunikasi Creative Commons Attribution-ShareAlike 4.0 International License.

References

Wino, Adi Putra, dan Susanti, Erlin, dan Herwin. “Analisis Sentimen Dompet Elektronik Pada Media Sosial Twitter Menggunakan Naïve Bayess Classifier”, IT Journal Research and Development. Vol.5, No.1 2020.

Kristiyanti, Dinar Ajeng. “E-Wallet Sentiment Analysis Using Naïve Bayes and Support Vector Machine”. Journal of Physics:Conference Series. Vol.1641, No.2 ,(Agustus 2020)

Saidah, Siti dan Joanna, Mary. “Analisis Sentimen Pengguna Twitter Terhadap Dompet Elektronik Dengan Metode Lexicon Based Dan K-Nearest Neighbor”. Jurnal Ilmiah Informatika Komputer. Vol. 25 , No.1 (April 2020).

Mahendrajaya, Rachmad ,dan Buntoro, Asrofi Ghulam, dan Setyawan, Bhanu Muhammad. “Analisis Sentimen Pengguna Gopay Menggunakan Metode Lexicon Based Dan K-Nearest Neighbor”. Jurnal Teknik Universitas Muhammadiyah Ponorogo. Vol.3 , No.2 (Oktober 2019)