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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Fatihah Rahmadayana
Telkom University
Computer Science & IT Engineering

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Sentiment Analysis of Work from Home Activity using SVM with Randomized Search Optimization Fatihah Rahmadayana; Yuliant Sibaroni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.651 KB) | DOI: 10.29207/resti.v5i5.3457

Abstract

Government policy on a problematic topic can lead to pros and cons, including the implementation of work from home during the COVID-19 pandemic in Indonesia. Lots of social media users express their opinions through social media, such as Twitter. Using Twitter API, data on Twitter can be obtained freely, so it can be utilized for sentiment analysis. Therefore, this study contains an analysis of public sentiment on the work from home policy using various preprocessing methods and Support Vector Machine with randomized search optimization. The result shows that the use of the acronym expansion method, slang word translation, and emoji translation in the preprocessing stage can increase the F1 Score value. The best F1 score results obtained were 83.362%. The results of the preprocessing method are used to predict unlabeled data. Prediction results show that 62.35% of tweets have positive sentiments, on the contrary, 37.65% of tweets have negative sentiments. So, it can conclude that most netizens support the policy of work from home.
Co-Authors Yuliant Sibaroni