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ANALISIS SENTIMEN ULASAN APLIKASI LINKEDIN DALAM GOOGLE PLAY STORE DENGAN MODEL NAÏVE BAYES Sukiman, Leni Kusneti; Dolok Saribu, Anggitta Ratu; Wiajaya, Andri
Djtechno: Jurnal Teknologi Informasi Vol 4, No 2 (2023): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v4i2.3907

Abstract

In the era of digitalization, mobile applications have become a basic necessity in individual lives, especially in the work context. LinkedIn, as a mobile application that focuses on providing job and recruitment information. With the significant growth of LinkedIn users in 2023 with 930 registered users, many users will provide reviews on the Google Play Store regarding their experiences. The aim of this research is to collect information on reviews on the Google Play Store regarding the LinkedIn application service through sentiment analysis using the data mining classification method with the Naïve Bayes model. Through previous research, this method is considered better than other classification methods. After applying this model through testing on test data, test results were obtained which showed that the majority of LinkedIn application reviews had negative sentiment with an accuracy value of 84% which was presented in bar charts and wordcloud.