Image of Analisis Sentimen Terhadap Pelaksanaan Pembatasan Sosial Berskala Besar (Psbb) Pada Masa New Normal Menggunakan Metode Support Vector Machine (Svm)
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Analisis Sentimen Terhadap Pelaksanaan Pembatasan Sosial Berskala Besar (Psbb) Pada Masa New Normal Menggunakan Metode Support Vector Machine (Svm)

The spread of the COVID-19 virus has now become a pandemic because it has
spread throughout the world, including Indonesia. The prositive case rate and the
increasing death rate led the Indonesian government to make a regulation limiting
community activities to break the chain of spread of COVID-19 in Indonesia. This
regulation is a Large-Scale Social Restriction (PSBB. This becomes a polemic for
some Indonesian people, especially those who do not have a fixed income. Many
social media users discuss the implementation of PSBB in Indonesia. This study
aims to find out how public’s sentiment towards the implementation of PSBB in
Indonesia during the new normal period through tweets on social media Twitter
using the Support Vector Machine (SVM) method. The data obtained for the
implementation of the PSBB before the new normal was 322 tweet data that had
been labeled while the tweet data for after the new normal was 653 data that had
been labeled. The results obtained using the k-fold cross validation and confusion
matrix method on the model created results in the highest accuracy rate is 81% with
the distribution of data 90% : 10% for data before the new normal and for the data
after the new normal, the highest accuracy value is 71% with the distribution of data
80% : 20%. The use of k-fold cross validation produces the highest accuracy value
of 78% with fold value = 8 for data before new normal, while for data after new
normal, the highest accuracy values is 73% with fold value = 1.
Keywords: Confusion Matrix, K-Fold Cross Validation, PSBB, Sentiment
Analysis, Support Vector Machine, Twitter

Ketersediaan
#
Perpustakaan Universitas Riau 03 05.122 (0010)
03 05.122 (0010)
Tersedia
Informasi Detail
Judul Seri
-
No. Panggil
03 05.122 (00010)
Penerbit
Pekanbaru : Universitas Riau - FMIPA - Sistem Informasi.,
Deskripsi Fisik
xii, 90 hlm.: ill.: 29 cm
Bahasa
Indonesia
ISBN/ISSN
-
Klasifikasi
03 05.122 (00010)
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
-
Subjek
SISTEM INFORMASI
Info Detail Spesifik
-
Pernyataan Tanggungjawab
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Tidak tersedia versi lain

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