Analisis Sentimen Pendapat Masyarakat Terhadap Isu Resesi Tahun 2023 Di Indonesia Menggunakan Algoritma Naive Bayes

Fakhri Zakaria, Naufal (2023) Analisis Sentimen Pendapat Masyarakat Terhadap Isu Resesi Tahun 2023 Di Indonesia Menggunakan Algoritma Naive Bayes. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Recession is a phenomenon in which the real GDP (gross domestic product) decreases for two consecutive quarters, meaning that economic activities such as distribution, investment, consumption, and production will decrease, causing a domino effect that is detrimental to various parties, one of which is layoffs (termination of employment). The recession was initiated by the weakening of the global economy which had an impact on the domestic economy and countries in the world. The stronger the dependence of a country's economy on the global economy, the faster a recession will occur in that country. Indonesian President Joko Widodo predicts that in 2023 Indonesia will be a dark year due to the economic and energy crisis due to Covid-19 and the war between Russia and Ukraine Therefore a sentiment analysis is needed to see public opinion regarding the issue of the 2023 recession in Indonesia. The method used in this study is the Naïve Bayes classification method. Naïve Bayes is a classification algorithm that is widely used in Data Mining or Text Mining. This study aims to search for negative, positive, and neutral comments and to find out the accuracy of the Naïve Bayes method. Sentiment analysis was obtained using data crawling, data cleaning, tokenization, labelling, Naïve Bayes classification, and evaluation. Based on the results of the research conducted, the results of the accuracy using the Naïve Bayes method with 3 labels are 92% with a precision value of 0.78, a recall value of 0.70, and an f1-score of 0.73. Keyword: sentiment analysist, data mining, Naïve Bayes, recession, text mining

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