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All Journal Teknomatika: Jurnal Informatika dan Komputer
GILANG BRILIAN RACHMAT
Universitas Jenderal Achmad Yani Yogyakarta
Computer Science & IT

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ANALISIS SENTIMEN ULASAN BANTUAN SOSIAL (BANSOS) DI TWITTER MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) GILANG BRILIAN RACHMAT; Puji Winar Cahyo; Fajar Syahruddin
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1137

Abstract

Background: Social assistance (bansos) is assistance provided to the community/social institutions in a non-continuous and selective manner in the form of money/goods to the community, aiming to improve the welfare of the community. The purpose of this study is to create an analytical model using the Support Vector Machine method which is used to perform Sentiment analysis regarding social assistance (bansos) on Twitter. Research Method: using the Support Vector Machine (svm) method. Based on the classification results, a lot of negative tweet data and many netizens regret that social assistance is still not evenly distributed and there is still a lot of social assistance corruption by the government itself which is marked by a lot of negative sentiments rather than positive sentiments. Conclusion: This study succeeded in testing the accuracy using the Support Vector Machine (SVM) method with a value of 84% on training data and 97% on testing data.
Co-Authors Fajar Syahruddin Puji Winar Cahyo