Sentiment Analysis Pelaksanaan Work From Home di Indonesia pada Masa Pandemi COVID-19 Menggunakan IndoBERT

Rahmatullah, Bella (2021) Sentiment Analysis Pelaksanaan Work From Home di Indonesia pada Masa Pandemi COVID-19 Menggunakan IndoBERT. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pembatasan Sosial Berskala Besar (PSBB) yang sekarang berubah nama menjadi Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) pada masa pandemi COVID-19 oleh Pemerintah Republik Indonesia membuat perusahaan, instansi, maupun organisasi memberlakukan kebijakan bekerja dari rumah atau yang sering disebut Work From Home (WFH). Pelaksanaan WFH pada masa pandemi tentunya memiliki keuntungan dan tantangan tersendiri bagi setiap pekerja. Opini mengenai pelaksanaan WFH kerap diungkapkan masyarakat melalui media sosial Twitter. Data opini dianalisis untuk mengetahui kecenderungan sentimen masyarakat sebagai pertimbangan kelanjutan pelaksanaan WFH pasca pandemi. Model pre-trained Bidirectional Encoder Representations from Transformers (BERT) merupakan model yang sedang popular di kalangan peneliti. Pada penelitian ini data opini dianalisis menggunakan pre-trained model BERT bahasa Indonesia, IndoBERT untuk analisis sentimen. Model yang digunakan menunjukkan performasi pembelajaran sebesar 95 % dan 68% pada saat pengujian. Dari hasil penelitian ini diketahui bahwa masyarakat Indonesia cenderung memiliki sentimen positif terhadap pelaksanaan work from home pada masa pandemi COVID-19
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The Large-Scale Social Restrictions (PSBB) which was now changed its name to Enforcement of Restriction on Community (PPKM) policy during the COVID-19 pandemic by Indonesia’s government make companies, agencies, or organizations enforce a policy of Work From Home (WFH). The implementation of WFH has its own advantages and challenges for each worker. Opinions regarding the implementation of WFH are often expressed by public through social media Twitter. Opinion data was analyzed to determine the tendency of public statement as a concideration for the continuation of post-pandemic WFH implementation. The pre-trained model Bidirectional Encoder Representations of Transformers (BERT)is currently popular among researchers. In this study, opinion data were analyzed using pre-trained Indonesian BERT-based model,IndoBERT for sentiment analysis. The model showslearning performance in95% for training phase and 68% for testing phase. From this study, it is known that Indonesian people tend to have positive sentiments towards implementation of work from home during COVID-19 pandemic

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Analisis Sentimen, BERT, IndoBERT, WFH, Sentiment Analysis
Subjects: H Social Sciences > HA Statistics > HA31.38 Data envelopment analysis.
H Social Sciences > HD Industries. Land use. Labor > HD108 Classification (Theory. Method. Relation to other subjects )
H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis.
Q Science > QA Mathematics > QA278.55 Cluster analysis
Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics)
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User: Bella Rahmatullah
Date Deposited: 03 Sep 2021 03:37
Last Modified: 06 Jul 2022 08:34
URI: http://repository.its.ac.id/id/eprint/91493

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