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All Journal JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur)
Salma Rita
Universitas Muhammadiyah Sukabumi
Computer Science & IT Electrical & Electronics Engineering

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Journal : Bit (Fakultas Teknologi Informasi Universitas Budi Luhur)

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Using Support Vector Machine for Sentiment Analysis of Truecaller and Getcontact App Reviews Salma Rita; Didik Indrayana; Agung Pambudi
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 20, No 2 (2023): SEPTEMBER 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v20i2.2493

Abstract

Spam calls are any calls made without the consent of the recipient and for any reason. These calls can originate from marketing, advertising, notifications, or fraud. The average Indonesian receives 14 spam calls per day. Only half of it comes from contact book numbers. According to the Google Play Store, the Truecaller and Getcontact apps offer a number of advantages as they each help identify callers and prevent spam. However, in this regard, spam call blocking software has a number of drawbacks, including identifying spam calls incorrectly and blocking useless calls. Sentiment analysis can help users choose applications that suit their needs and in this study intends to analyze reviews on the sentiments of the two applications namely Truecaller: Caller Id and Getcontact by analyzing effectiveness based on the application reviews Support Vector Machine classification algorithm which contains basic guidelines for maximizing hyperplane boundaries that separate the two datasets, are used in the classification process of this study. The results showed that the Truecaller application at 10-fold cross validation had an average accuracy of 88.20% and the Getcontact application had an average accuracy of 87.90%. Meanwhile, the sentiment aspect of the Truecaller application has an average accuracy value of 60.20%, while the Getcontact application has an average accuracy of 63.30%.
Co-Authors Agung Pambudi Didik Indrayana