ANALISIS OPINI TERHADAP KEBIJAKAN PEMERINTAH INDONESIA TERKAIT COVID-19 PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES SERTA LEXICON BASED

SA'BANNA, FADDLY (2021) ANALISIS OPINI TERHADAP KEBIJAKAN PEMERINTAH INDONESIA TERKAIT COVID-19 PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES SERTA LEXICON BASED. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

This analysis was carried out to obtain public opinion regarding the LargeScale Social Restrictions (PSBB), a policy by the government due to Covid-19. In this study, the data used are data obtained from a social media, Twitter, which will be processed and analyzed in the opinion analysis process using the Naive Bayes algorithm and lexicon based method. The implementation of this policy has affected the society and caused concern to all Indonesian people, which can be seen from both pros and cons opinions regarding PSBB expressed in Twitter. Therefore the analysis is carried out to determine the community's side regarding the PSBB policy. Previous research related to opinion analysis regarding policies distinguishes only in the algorithms and datasets used but all have the same purpose, which is an opinion analysis. What distinguishes this research from previous research is the topic is the current issue, Covid-19, which was focused on public responses to the PSBB as a policy by the government to handle Covid-19. The algorithms used in this analysis were the Naive Bayes and the Lexicon based. This research was conducted through several steps: the data collection process, the data cleaning process (preprocessing stage), implementing the related algorithms, and lastly presenting the results both in visual form and accuracy. Key words: Covid-19, Sentiment Analysis, Classification, Lexicon Based, Naïve Bayes Analisis ini dilakukan untuk mendapatkan opini masyarakat terkait Pembatasan Sosial Berskala Besar (PSBB), sebuah kebijakan yang dikeluarkan pemerintah untuk penanganan Covid-19. Diberlakukannya kebijakan ini telah memberikan dampak dan menjadi perhatian seluruh masyarakat Indonesia. Hal ini dapat dilihat dari adanya pendapat pro dan kontra terkait kebijakan ini di media sosial Twitter. Oleh karena itu, analisis ini dilakukan untuk mengetahui yang mana pro dan kontra dengan kebijakan PSBB dari pemerintah. Penelitian ini menggunakan data yang didapat dari media sosial Twitter, dimana data tersebut diolah dan dianalisis dalam proses analisis opini menggunakan algoritma Naive Bayes serta Lexicon Based. Penelitian sebelumnya terkait analisis opini mengenai kebijakan berbeda hanya di algoritma serta dataset yang digunakan saja, namun memiliki tujuan penelitian yang sama yaitu analisis opini. Yang membedakan penelitian ini dengan penelitian sebelumnya adalah topik yang diambil merupakan isu terkini, Covid-19, yang difokuskan ke tanggapan masyarakat terhadap kebijakan PSBB pemerintah. Algoritma yang digunakan pada analisis ini adalah algoritma Naive Bayes dan Lexicon Based. Penelitian ini dilakukan dengan beberapa tahapan yaitu proses pengumpulan data, pembersihan data (tahap preprocessing), penerapan algoritma terkait, serta menampilkan hasilnya dalam bentuk visual dan hasil akurasi dari analisa dengan hasil. Kata kunci: Analisis Sentimen kebijakan Covid-19, Klasifikasi, Lexicon Based, Naive Bayes

Item Type: Thesis (S1)
NIM/NIDN Creators: 41516120111
Uncontrolled Keywords: Analisis Sentimen kebijakan Covid-19, Klasifikasi, Lexicon Based, Naive Bayes
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 154 Subconscious and Altered States and Process/Psikologi Bawah Sadar > 154.6 Sleep Phenomena/Fenomena Tidur > 154.63 Dreams/Mimpi > 154.634 Analysis/Analisis
300 Social Science/Ilmu-ilmu Sosial > 300. Social Science/Ilmu-ilmu Sosial
300 Social Science/Ilmu-ilmu Sosial > 300. Social Science/Ilmu-ilmu Sosial > 303 Social Process/Proses Sosial > 303.3 Coordination and Control/Koordinasi dan Kontrol > 303.38 Public Opinion/Opini Publik
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 05 Dec 2023 06:06
Last Modified: 05 Dec 2023 06:06
URI: http://repository.mercubuana.ac.id/id/eprint/84577

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